Lapidarium notes

Science and a New Kind of Prediction: An Interview with Stephen Wolfram

“I think Computation is destined to be the defining idea of our future.”

—  Stephen Wolfram in Computing a Theory of Everything

“Better living through data? When a pioneer of data collection and organization turned his analytical tools on himself, he revealed the complexity of automating human judgment and the difficulty of predicting just what is predictable.

So, what can one of the world’s foremost mathematical minds learn about life by examining his own computational data? (…)

Q: In your blog, you write that “in time I’m looking forward to being able to ask Wolfram|Alpha all sorts of things about my life and times—and have it immediately generate reports about them. Not only being able to act as an adjunct to my personal memory, but also to be able to do automatic computational history—explaining how and why things happened—and then making projections and predictions.” What sort of things have you been able to predict based on this data set you released?

Stephen Wolfram: One thing I found out is that I’m much more habitual than I ever imagined. It’s amazing to see oneself turned into full distribution. It got me thinking about lots of different ways that I could improve my life and times with data. What I realized is that one of the more important things is to have quick feedback about what’s going on, so you don’t have to wait for a year to go back and look at what happened. You can just see it quickly.

I was actually embarrassed that I hadn’t had a real-time display of the history of my unread e-mail, as a function of time. We built that after this blog post, and I have found it’s quite amazing. By having this feedback, I’m able to work more efficiently. It’s also telling me things like, Gosh, if I ignore my e-mail for four days, or five days, or ten days, or something, it will get totally out of hand, and it would take me weeks and weeks to recover from that. Those sound like very mundane [insights], but in terms of how one actually spends one’s time, they can be quite significant effects.

Q: Nobel Prize–winning economist Daniel Kahneman tells us that people, even particularly smart people in extremely high-performing situations, will consistently underestimate how much time it takes them to complete a certain task. So now that you’ve been able to rid yourself of subjective bias in terms of how long it takes to complete tasks, it sounds like you’ve actually been able to see efficiency improvements, just based on taking a look at what you can get done, how long it actually takes, versus how long you think and that sort of thing.

Wolfram: I have pretty good metrics now. If I’m going to write out something for some talk I’m going to give, or something like this, I know how long it takes me now to give the talk, or to write it out. I know how long to set aside. I have learned that there’s no point in starting early, because I won’t finish it until just in time anyway. I have to know how long it’s actually going to take to finish so that I can get it done in an efficient way. If I start it too early, it takes me longer. The task expands into the space available, so to speak. (…)

Q: Your seminal book, A New Kind of Science, is ten years old. You recently wrote a blog post on the anniversary. Can you talk a little bit about the future of science?

Wolfram: The main idea of A New Kind of Science was to introduce a new way to model things in the world. Three hundred years ago, there was this big transformation in science when it was realized that one could use math, and the formal structure of math, to talk about the natural world. Using math, one could actually compute what should happen in the world—how planets should move, how comets should move, and all those kinds of things.

That has been the dominant paradigm for the last 300 years for the exact sciences. Essentially it says, Let’s find a math equation that represents what we’re talking about, and let’s use that math equation to predict what a system will do. That paradigm has also been the basis for most of our engineering: Let’s figure out how this bridge should work using calculus equations, and so on. Or, Let’s work out this electric circuit using some other kind of differential equation, or algebraic equation or whatever.

That approach has been pretty successful for lots of things. It’s led to a certain choice of subject matter for science, because the science has tended to choose subject matter where it can be successful.

The same is true with engineering. We’ve pursued the particular directions of engineering because we know how to make them work. My goal was to look at the things that science has not traditionally had so much to say about—typically, systems that are more complex in their behavior, and so on—and to ask what we can do with these.

It’s a great approach, but it’s limited. The question is, what’s the space with all possible models that you can imagine using?

A good way to describe that space is to think about computer programs. Any program is [a set of] defined rules for how a system works. For example, when we look at nature, we would ask what kinds of programs nature is using to do what it does, to grow the biological organisms it grows, how fluids flow the way they do—all those kinds of things.

I’ve discovered that very simple programs can serve as remarkably accurate models for lots of things that happen in nature. In natural science, that gives us a vastly better pool of possible models to use than we had from just math. We then see that these may be good models for how nature works. They tell us something about how nature is so easily able to make all this complicated stuff that would be very hard for us to make if we just imagined that nature worked according to math.

Now we realize that there’s a whole different kind of engineering that we can do, and we can look at all of these possible simple programs and use those to create our engineering systems.

This is different from the traditional approach, where I would say, I know these things that work. I know about levers. I know about pulleys. I know about this. I know about that. Let me incrementally build the system where I, as an engineer, know every step of how the thing is going to work as I construct it.

Q: One of the key themes of A New Kind of Science, and also a key theme in your TED talk, is this notion of irreducibility. There are certain things that can’t really be predicted, no matter what. You can’t model them in advance. They have to be experienced. And I wonder, given the future of digitized knowledge, the exponential growth in structured and unstructured data that we can look forward to over the coming decades, is it possible that the space of irreducible knowledge, of unpredictable knowledge—while it will still always exist—is shrinking? Would this mean that the space of predictable knowledge is in fact growing?

Wolfram: Interesting question. Once we know enough, will we just be able to predict everything? In Wolfram|Alpha, for example, we know how to compute lots of things that you might have imagined weren’t predictable. You have a tree in your backyard. It’s such and such a size right now. How big will it be in 10 years? It’s now more or less predictable.

As we accumulate more data, there will certainly be patterns that can be seen, and things that one can readily see that are predictable. You can expect to have a dashboard—with certain constraints—showing how things are likely to evolve for you. You then get to make decisions: Should I do this? Should I do that?

But some part of the world is never going to be predictable. It just has this kind of computational irreducibility. We just have to watch it unfold, so to speak. There’s no way we can outrun it. I suspect that, in lots of practical situations, things will become a lot more predictable. That’s a big part of what we’re trying to address with Wolfram|Alpha. Take the corpus of knowledge that our civilization has accumulated and set it up so that you can automatically make use of it.

There are three reasons why one can’t predict the things that can’t be predicted. The first reason is not enough underlying data. The second is computational irreducibility—it’s just hard to predict. The third is simply not knowing enough to be able to predict something. You, as an individual, don’t happen to know enough about that particular area to be able to do it. I’m trying to solve that problem.

We’re seeing a transition happening right now, and more and more things can be figured out in an automatic way. We’re seeing computation that is finally impinging on our lives in a very direct way. There are lots of things that used to be up to us to estimate, but now they’re just being computed for us: a camera that auto focuses, for example, or that picks out faces and figures what to do, or automatically clicks the shutter when it sees a smile—those kinds of things. Those are all very human judgment activities, and now they’re automated.

I think this is the trend of technology. It’s the one thing, I suppose, in human history that has actually had a progression: There’s more technology; there are more layers of automation about what we do.”

— Stephen Wolfram, renowned British scientist and the chief designer of the Mathematica software application and the Wolfram Alpha answer engine, interviewed by Patrick Tucker in Science and a New Kind of Prediction: An Interview with Stephen Wolfram, IEET, Apr 26, 2013  (Photo source)

Stephen Wolfram: Computing a theory of everything

— Stephen Wolfram: Computing a theory of everything, TED, Feb 2010.

See also:

☞ The Rise of Big Data. How It’s Changing the Way We Think About the World
☞ Dirk Helbing on A New Kind Of Socio-inspired Technology
☞ Information tag on Lapidarium notes

The Rise of Big Data. How It’s Changing the Way We Think About the World

“In the third century BC, the Library of Alexandria was believed to house the sum of human knowledge. Today, there is enough information in the world to give every person alive 320 times as much of it as historians think was stored in Alexandria’s entire collection — an estimated 1,200 exabytes’ worth. If all this information were placed on CDs and they were stacked up, the CDs would form five separate piles that would all reach to the moon. (…)

Using big data will sometimes mean forgoting the quest for why in return for knowing what. (…)

There will be a special need to carve out a place for the human: to reserve space for intuition, common sense, and serendipity. (…)

Datafication is not the same as digitization, which takes analog content — books, films, photographs — and converts it into digital information, a sequence of ones and zeros that computers can read. Datafication is a far broader activity: taking all aspects of life and turning them into data. Google’s augmented-reality glasses datafy the gaze. Twitter datafies stray thoughts. LinkedIn datafies professional networks.

Once we datafy things, we can transform their purpose and turn the information into new forms of value. For example, IBM was granted a U.S. patent in 2012 for “securing premises using surface-based computing technology” — a technical way of describing a touch-sensitive floor covering, somewhat like a giant smartphone screen. Datafying the floor can open up all kinds of possibilities. The floor could be able to identify the objects on it, so that it might know to turn on lights in a room or open doors when a person entered. Moreover, it might identify individuals by their weight or by the way they stand and walk. (…)

This misplaced trust in data can come back to bite. Organizations can be beguiled by data’s false charms and endow more meaning to the numbers than they deserve. That is one of the lessons of the Vietnam War. U.S. Secretary of Defense Robert McNamara became obsessed with using statistics as a way to measure the war’s progress. He and his colleagues fixated on the number of enemy fighters killed. Relied on by commanders and published daily in newspapers, the body count became the data point that defined an era. To the war’s supporters, it was proof of progress; to critics, it was evidence of the war’s immorality. Yet the statistics revealed very little about the complex reality of the conflict. The figures were frequently inaccurate and were of little value as a way to measure success. Although it is important to learn from data to improve lives, common sense must be permitted to override the spreadsheets. (…)

Ultimately, big data marks the moment when the “information society” finally fulfills the promise implied by its name. The data take center stage. All those digital bits that have been gathered can now be harnessed in novel ways to serve new purposes and unlock new forms of value. But this requires a new way of thinking and will challenge institutions and identities. In a world where data shape decisions more and more, what purpose will remain for people, or for intuition, or for going against the facts? If everyone appeals to the data and harnesses big-data tools, perhaps what will become the central point of differentiation is unpredictability: the human element of instinct, risk taking, accidents, and even error. If so, then there will be a special need to carve out a place for the human: to reserve space for intuition, common sense, and serendipity to ensure that they are not crowded out by data and machine-made answers.

This has important implications for the notion of progress in society. Big data enables us to experiment faster and explore more leads. These advantages should produce more innovation. But at times, the spark of invention becomes what the data do not say. That is something that no amount of data can ever confirm or corroborate, since it has yet to exist. If Henry Ford had queried big-data algorithms to discover what his customers wanted, they would have come back with “a faster horse,” to recast his famous line. In a world of big data, it is the most human traits that will need to be fostered — creativity, intuition, and intellectual ambition — since human ingenuity is the source of progress.

Big data is a resource and a tool. It is meant to inform, rather than explain; it points toward understanding, but it can still lead to misunderstanding, depending on how well it is wielded. And however dazzling the power of big data appears, its seductive glimmer must never blind us to its inherent imperfections. Rather, we must adopt this technology with an appreciation not just of its power but also of its limitations.”

— Kenneth Neil Cukier and Viktor Mayer-Schoenberger, The Rise of Big Data, Foreign Affairs, May/June 2013. (Photo: John Elk)

See also:

☞ Dirk Helbing on A New Kind Of Socio-inspired Technology
☞ Information tag on Lapidarium notes

Philosophers and the age of their influential contributions

(source)

Hilary Putnam - ‘A philosopher in the age of science’

                  

“Imagine two scientists are proposing competing theories about the motion of the moon. One scientist argues that the moon orbits the earth at such and such a speed due to the effects of gravity and other Newtonian forces. The other, agreeing to the exact same observations, argues that behind Newtonian forces there are actually undetectable space-aliens who are using sophisticated tractor beams to move every object in the universe. No amount of observation will resolve this conflict. They agree on every observation and measurement. One just has a more baroque theory than the other. Reasonably, most of us think the simpler theory is better.

But when we ask why this theory is better, we find ourselves resorting to things that are patently non-factual. We may argue that theories which postulate useless entities are worse than simpler ones—citing the value of simplicity. We may argue that the space-alien theory contradicts too many other judgements—citing the value of coherence. We can give a whole slew of reasons why one theory is better than another, but there is no rulebook out there for scientists to point to which resolves the matter objectively. Even appeals to the great pragmatic value of the first theory or arguments that point out the lack of explanatory and predictive power of the space-alien theory, are still appeals to a value. No amount of observation will tell you why being pragmatic makes one theory better—it is something for which you have to argue. No matter what kind of fact we are trying to establish, it is going to be inextricably tied to the values we hold. (…)

In [Hilary Putnam’s] view, there is no reason to suppose that a complete account of reality can be given using a single set of concepts. That is, it is not possible to reduce all types of explanation to one set of objective concepts. Suppose I say, “Keith drove like a maniac” and you ask me why. We would usually explain the event in terms of value-laden concepts like intention, emotion, and so on—“Keith was really stressed out”—and this seems to work perfectly fine. Now we can also take the exact same event and describe it using an entirely different set of scientific concepts— say “there was a chain of electrochemical reactions from this brain to this foot” or “there was x pressure on the accelerator which caused y torque on the wheels.” These might be true descriptions, but they simply don’t give us the whole or even a marginally complete picture of Keith driving like a maniac. We could describe every single relevant physical detail of that event and still have no explanation. Nor, according to Putnam, should we expect there to be. The full scope of reality is simply too complex to be fully described by one method of explanation.

The problem with all of this, and one that Putnam has struggled with, is what sort of picture of reality we are left with once we accept these three central arguments: the collapse of the fact-value dichotomy, the truth of semantic externalism and conceptual relativity. (…)

We could—like Putnam before the 1970s—become robust realists and simply accept that values and norms are no less a part of the world than elementary particles and mathematical objects. We could—like Putnam until the 1990s—become “internal realists” and, in a vaguely Kantian move define reality in terms of mind-dependent concepts and idealised rational categories. Or we could adopt Putnam’s current position—a more modest realism which argues that there is a mind-independent world out there and that it is compatible with our ordinary human values. Of course Putnam has his reasons for believing what he does now, and they largely derive from his faith in our ability to represent reality correctly. But the strength of his arguments convincing us to be wary of the scientific stance leave us with little left of trust in it.”

— Malcolm Thorndike Nicholson, A philosopher in the age of science, Prospect, March, 14, 2013. [Hilary Putnam — American philosopher, mathematician and computer scientist who has been a central figure in analytic philosophy since the 1960s, currently Cogan University Professor Emeritus at Harvard University.]

Rolf Fobelli: News is to the mind what sugar is to the body

“We humans seem to be natural-born signal hunters, we’re terrible at regulating our intake of information. We’ll consume a ton of noise if we sense we may discover an added ounce of signal. So our instinct is at war with our capacity for making sense.”

— Nicholas Carr, A little more signal, a lot more noise, Rough Type, May 30, 2012.

“When people struggle to describe the state that the Internet puts them in they arrive at a remarkably familiar picture of disassociation and fragmentation. Life was once whole, continuous, stable; now it is fragmented, multi-part, shimmering around us, unstable and impossible to fix. The world becomes Keats’s “waking dream,” as the writer Kevin Kelly puts it.”

— Adam Gopnik on The Information and How the Internet gets inside us, 2011

“Our brains are wired to pay attention to visible, large, scandalous, sensational, shocking, peoplerelated, story-formatted, fast changing, loud, graphic onslaughts of stimuli. Our brains have limited attention to spend on more subtle pieces of intelligence that are small, abstract, ambivalent, complex, slow to develop and quiet, much less silent. News organizations systematically exploit this bias. News media outlets, by and large, focus on the highly visible. They display whatever information they can convey with gripping stories and lurid pictures, and they systematically ignore the subtle and insidious, even if that material is more important. News grabs our attention; that’s how its business model works. Even if the advertising model didn’t exist, we would still soak up news pieces because they are easy to digest and superficially quite tasty. The highly visible misleads us. (…)

• Terrorism is overrated. Chronic stress is underrated.
• The collapse of Lehman Brothers is overrated. Fiscal irresponsibility is underrated.
• Astronauts are overrated. Nurses are underrated.
• Britney Spears is overrated. IPCC reports are underrated.
• Airplane crashes are overrated. Resistance to antibiotics is underrated.

(…)

Afraid you will miss “something important”? From my experience, if something really important happens, you will hear about it, even if you live in a cocoon that protects you from the news. Friends and colleagues will tell you about relevant events far more reliably than any news organization. They will fill you in with the added benefit of meta-information, since they know your priorities and you know how they think. You will learn far more about really important events and societal shifts by reading about them in specialized journals, in-depth magazines or good books and by talking to the people who know. (…)

The more “news factoids” you digest, the less of the big picture you will understand. (…)

Thinking requires concentration. Concentration requires uninterrupted time. News items are like free-floating radicals that interfere with clear thinking. News pieces are specifically engineered to interrupt you. They are like viruses that steal attention for their own purposes. (…)

This is about the inability to think clearly because you have opened yourself up to the disruptive factoid stream. News makes us shallow thinkers. But it’s worse than that. News severely affects memory. (…)

News is an interruption system. It seizes your attention only to scramble it. Besides a lack of glucose in your blood stream, news distraction is the biggest barricade to clear thinking. (…)

In the words of Professor Michael Merzenich (University of California, San Francisco), a pioneer in the field of neuroplasticity: “We are training our brains to pay attention to the crap.” (…)

Good professional journalists take time with their stories, authenticate their facts and try to think things through. But like any profession, journalism has some incompetent, unfair practitioners who don’t have the time – or the capacity – for deep analysis. You might not be able to tell the difference between a polished professional report and a rushed, glib, paid-by-the-piece article by a writer with an ax to grind. It all looks like news.

My estimate: fewer than 10% of the news stories are original. Less than 1% are truly investigative. And only once every 50 years do journalists uncover a Watergate.

Many reporters cobble together the rest of the news from other people’s reports, common knowledge, shallow thinking and whatever the journalist can find on the internet. Some reporters copy from each other or refer to old pieces, without necessarily catching up with any interim corrections. The copying and the copying of the copies multiply the flaws in the stories and their irrelevance. (…)

Overwhelming evidence indicates that forecasts by journalists and by experts in finance, social development, global conflicts and technology are almost always completely wrong. So, why consume that junk?

Did the newspapers predict World War I, the Great Depression, the sexual revolution, the fall of the Soviet empire, the rise of the Internet, resistance to antibiotics, the fall of Europe’s birth rate or the explosion in depression cases? Maybe, you’d find one or two correct predictions in a sea of millions of mistaken ones. Incorrect forecast are not only useless, they are harmful.

To increase the accuracy of your predictions, cut out the news and roll the dice or, if you are ready for depth, read books and knowledgeable journals to understand the invisible generators that affect our world. (…)

I have now gone without news for a year, so I can see, feel and report the effects of this freedom first hand: less disruption, more time, less anxiety, deeper thinking, more insights. It’s not easy, but it’s worth it.”

Table of Contents:

No 1 – News misleads us systematically
No 2 – News is irrelevant
No 3 – News limits understanding
No 4 – News is toxic to your body
No 5 – News massively increases cognitive errors
No 6 – News inhibits thinking
No 7 – News changes the structure of your brain
No 8 – News is costly
No 9 – News sunders the relationship between reputation and achievement
No 10 – News is produced by journalists
No 11 – Reported facts are sometimes wrong, forecasts always
No 12 – News is manipulative
No 13 – News makes us passive
No 14 – News gives us the illusion of caring
No 15 – News kills creativity

— Rolf Dobelli, Swiss novelist, writer, entrepreneur and curator of zurich.minds, to read full essay click Avoid News. Towards a Healthy News Diet (pdf), 2010. (Illustration: Information Overload by taylorboren)

See also:

☞ The Difference Between Online Knowledge and Truly Open Knowledge. In the era of the Internet facts are not bricks but networks
☞ Nicholas Carr on the evolution of communication technology and our compulsive consumption of information
☞ Does Google Make Us Stupid?
☞ Nicholas Carr on what the internet is doing to our brains?
☞ How the Internet Affects Our Memories: Cognitive Consequences of Having Information at Our Fingertips
☞ Dr Paul Howard-Jones, The impact of digital technologies on human wellbeing (pdf), University of Bristol
☞ William Deresiewicz on multitasking and the value of solitude
☞ Information tag on Lapidarium

Albert Bandura on social learning, the origins of morality, and the impact of technological change on human nature

“Technology has changed the speed and the scope of social influence and has really transformed our realities. Social cognitive theory is very compatible with that. Other learning theories were linked to learning by direct experience, but when I look around today, I see that most of our learning is by social modeling and through indirect experiences. Errors can be very costly and you can’t afford to develop our values, our competences, our political systems, our religious systems through trial and error. Modeling shortcuts this process. (…)

With new technologies, we’re essentially transcending our physical environment and more and more of our values and attitudes and behavior are now shaped in the symbolic environment – the symbolic environment is the big one rather than the actual one. The changes are so rapid that there are more and more areas of life now in which the cyber world is really essential. One model can affect millions of people worldwide, it can shape their experiences and behaviors. We don’t have to rely on trial and error.

There’s a new challenge now: When I was growing up, we didn’t have all this technology, so we were heavily involved in personal relationships. Now the cyber world is available, and it’s hard to maintain a balance in the priorities of life. (…)

The internet can provide you with fantastic globalized information – but the problem is this: It undermines our ability for self-regulation or self-management. The first way to undermine productivity is temporizing, namely we’re going to put off what we need to do until tomorrow, when we have the illusion that we’ll have more time. So we’re dragging the stuff with us. But the really big way is detouring, and wireless devices are now giving an infinite detour. They create the illusion of business. I talked to the author of a beststeller and I asked him about his writing style. He said: ‘Well, I have to check my e-mails and then I get down to serious writing, but then I get back to the e-mails.’ The challenge of the cyber world is establishing a balance between our digital life and life in the real world. (…)

The origins of morality

Originally our behavior was pretty much shaped by control, by the external consequences of our lives. So the question is: How did we acquire some standards? There are about three or four ways. One: We evaluate reactions to our behavior. We behave in certain ways, in good ways, in bad ways, and then we receive feedback. We begin to adopt standards from how the social environment reacts to our behavior. Two: We see others behaving in certain ways and we are either self-critical or self-approving. Three: We have precepts that tell us what is good and bad. And once we have certain self-sanctions, we have two other potent factors that can influence our behavior: People will behave in certain ways because they want to avoid legal sanctions to their behavior or the social sanctions in their environment. (…)

Many of our theories of morality are abstract. But the primary concern about the acquisition of morality and about the modes of moral reasoning is only one half of the story, the less interesting half. We adopt standards, but we have about eight mechanisms by which we selectively disengage from those standards. So the challenge to explain is not why do people behave in accordance with these standards, but how is it that people can behave cruelly and still feel good about themselves. Our problem is good people doing bad things – and not evil people doing bad things. (…)

Everyday people can behave very badly. In the book I’m writing on that topic I have a long chapter on moralist disengagement in the media, in the gun industry, in the tobacco industry, in the corporate world, in the finance industry – there’s fantastic data from the last few years – in terrorism and as an impediment to environmental sustainability. That’s probably the most important area of moralist disengagement. We have about forty or fifty years, and if we don’t get our act together, we’ll have a very hard time. It’s going to be awfully crowded on earth and a good part of our cities will be under water. And what are we doing? We don’t have the luxury of time anymore. (…)

Human nature is capable of vindicating behavior. It isn’t that people are bad by nature. But they have a very playful and rewarding lifestyle, filled with gadgets and air conditioning, and they don’t want to give it up. (…)

Q: ‘The story of men is a story about violence, love, power, victory and defeat’ – that’s how poets talk about the course of history. But from an analystic point of view…

A. Bandura: That’s not true for all societies. We assume that aggression is inbred, but some societies are remarkably pacifistic. And we can also see large variations within a society. But the most striking example might be the transformation from warrior societies into peaceful societies. Switzerland is one example. Sweden is another: Those vikings were out mugging everyone and people would pray for protection: “Save our souls from the fury of the Norsemen!” And now, if you look at that society, it’s hard to find child abuse or domestic violence. Sweden has become a mediator of peace.

Q: In German, there’s the term “Schicksalsgemeinschaft,” which translates as “community of fate”: It posits that a nation is bound together by history. Do you think that’s what defines a society: A common history? Or is it religion, or the language we speak?

A. Bandura: All of the above. We put a lot of emphasis on biological evolution, but what we don’t emphasize is that cultures evolve, too. These changes are transmitted from one generation to another. A few decades ago, the role of women was to be housewives and it was considered sinful to co-habit without being married. If you look at the role of women today, there’s a fantastic transformation in a short period of time; change is accelerated. Homogenization is important, picking things from different cultures, cuisines, music traditions, forms of behavior, and so on. But we have also polarization: Bin Laden’s hate of the West, for example. And there’s hybridization as well. (…)

And society is changing, too. Now it’s considered completely normal to live with your partner without being married. In California, it was only about 40 years ago that homosexuality was treated as a disease. Then people protested, and eventually they got the state to change the diagnostic category to sexual orientation rather than a disease. Psychiatry, under public pressure, changed the diagnostic system. (…)

Q: It’s quite interesting to compare Russia and China. Russia has a free internet, so the reaction to protests is very different than in China. If social networks become increasingly global, do you foresee something like a global set of values as well?

A. Bandura: Yes, but there is another factor here, namely the tremendous power of multinational corporations. They now shape global culture. A lot of these global forces are undermining the collective African society, for example. The society does no longer have much control over the economy. In order to restore some power in leverage, societies are going to be organized in unions. We will see more partnerships around the world. (…)

The revolutionary tendency of technology has increased our sense of agency. If I have access to all global knowledge, I would have fantastic capacities to educate myself. (…) The important thing in psychology is that we need a theory of human agency, rather than arguing that we’re controlled by neural networks. In every aspect of our lives we now have a greater capacity for exercicing agency. (…)

Q: But at the same time globalization removes us from the forces that shape our environment.

A. Bandura: The problems are powerful transnational forces. They can undermine the capacity to run our own society: Because of what happens in Iran, gas prices might soon hit five dollars per gallon in the US. That’s where the pressure comes from for systems and societies to form blocks or build up leverage to protect the quality of life of their citizens. But we can see that a global culture is emerging. One example is the transformation of the status of women. Oppressive regimes see that women are able to drive cars, and they cannot continue to deny that right to them. We’re really changing norms. Thanks to the ubiquity of television, we’re motivating them and showing them that they have the capability to initiate change. It’s about agency: Change is deeply rooted in the belief that my actions can have an effect in the world.”

— Albert Bandura, a psychologist who is the David Starr Jordan Professor Emeritus of Social Science in Psychology at Stanford University. For almost six decades, he has been responsible for contributions to many fields of psychology, including social cognitive theory, therapy and personality psychology, and was also influential in the transition between behaviorism and cognitive psychology, “We have transcended our biology”, The European, 18.02.2013. (Photo: Linda A. Cicero / Stanford News Service)

See also:

☞ ‘Human beings are learning machines,’ says philosopher (nature vs. nurture), Lapidarium notes
☞ What Neuroscience Tells Us About Morality: ‘Morality is a form of decision-making, and is based on emotions, not logic’

Universality: In Mysterious Pattern, Math and Nature Converge

“In 1999, while sitting at a bus stop in Cuernavaca, Mexico, a Czech physicist named Petr Šeba noticed young men handing slips of paper to the bus drivers in exchange for cash. It wasn’t organized crime, he learned, but another shadow trade: Each driver paid a “spy” to record when the bus ahead of his had departed the stop. If it had left recently, he would slow down, letting passengers accumulate at the next stop. If it had departed long ago, he sped up to keep other buses from passing him. This system maximized profits for the drivers. And it gave Šeba an idea. (…)

The interaction between drivers caused the spacing between departures to exhibit a distinctive pattern previously observed in quantum physics experiments. (…) “We felt here some kind of similarity with quantum chaotic systems.” (…) A “spy” network makes the decentralized bus system more efficient. As a consequence, the departure times of buses exhibit a ubiquitous pattern known as “universality.” (…)

Subatomic particles have little to do with decentralized bus systems. But in the years since the odd coupling was discovered, the same pattern has turned up in other unrelated settings. Scientists now believe the widespread phenomenon, known as “universality,” stems from an underlying connection to mathematics, and it is helping them to model complex systems from the internet to Earth’s climate. (…)

The red pattern exhibits a precise balance of randomness and regularity known as “universality,” which has been observed in the spectra of many complex, correlated systems. In this spectrum, a mathematical formula called the “correlation function” gives the exact probability of finding two lines spaced a given distance apart. (…)

The pattern was first discovered in nature in the 1950s in the energy spectrum of the uranium nucleus, a behemoth with hundreds of moving parts that quivers and stretches in infinitely many ways, producing an endless sequence of energy levels. In 1972, the number theorist Hugh Montgomery observed it in the zeros of the Riemann zeta function, a mathematical object closely related to the distribution of prime numbers. In 2000, Krbálek and Šeba reported it in the Cuernavaca bus system. And in recent years it has shown up in spectral measurements of composite materials, such as sea ice and human bones, and in signal dynamics of the Erdös–Rényi model, a simplified version of the internet named for Paul Erdös and Alfréd Rényi. (…)

Each of these systems has a spectrum — a sequence like a bar code representing data such as energy levels, zeta zeros, bus departure times or signal speeds. In all the spectra, the same distinctive pattern appears: The data seem haphazardly distributed, and yet neighboring lines repel one another, lending a degree of regularity to their spacing. This fine balance between chaos and order, which is defined by a precise formula, also appears in a purely mathematical setting: It defines the spacing between the eigenvalues, or solutions, of a vast matrix filled with random numbers. (…)

It seems to be a law of nature,” said Van Vu, a mathematician at Yale University who, with Terence Tao of the University of California, Los Angeles, has proven universality for a broad class of random matrices.

Universality is thought to arise when a system is very complex, consisting of many parts that strongly interact with each other to generate a spectrum. The pattern emerges in the spectrum of a random matrix, for example, because the matrix elements all enter into the calculation of that spectrum. But random matrices are merely “toy systems” that are of interest because they can be rigorously studied, while also being rich enough to model real-world systems, Vu said. Universality is much more widespread. Wigner’s hypothesis (named after Eugene Wigner, the physicist who discovered universality in atomic spectra) asserts that all complex, correlated systems exhibit universality, from a crystal lattice to the internet.

     

Mathematicians are using random matrix models to study and predict some of the internet’s properties, such as the size of typical computer clusters. (Illustration: Matt Britt)

The more complex a system is, the more robust its universality should be, said László Erdös of the University of Munich, one of Yau’s collaborators. “This is because we believe that universality is the typical behavior.”

— Natalie Wolchover, In Mysterious Pattern, Math and Nature Converge, Wired, Feb 6, 2013. (Photo: Marco de Leija)

See also:

☞ Mathematics of Disordered Quantum Systems and Matrices, IST Austria.

‘Elegance,’ ‘Symmetry,’ and ‘Unity’: Is Scientific Truth Always Beautiful?

“Today the grandest quest of physics is to render compatible the laws of quantum physics—how particles in the subatomic world behave—with the rules that govern stars and planets. That’s because, at present, the formulas that work on one level implode into meaninglessness at the other level. This is deeply ungainly, and significant when the two worlds collide, as occurs in black holes. The quest to unify quantum physics (micro) and general relativity (macro) has spawned heroic efforts, the best-known candidate for a grand unifying concept presently being string theory. String theory proposes that subatomic particles are not particles at all but closed or open vibrating strings, so tiny, a hundred billion billion times shorter than an atomic nucleus’s diameter, that no human instrument can detect them. It’s the “music of the spheres”—think vibrating harp strings—made literal.

A concept related to string theory is “supersymmetry.” Physicists have shown that at extremely high energy levels, similar to those that existed a micro-blink after the big bang, the strength of the electromagnetic force, and strong and weak nuclear forces (which work only on subatomic levels), come tantalizingly close to converging. Physicists have conceived of scenarios in which the three come together precisely, an immensely intellectually and aesthetically pleasing accomplishment. But those scenarios imply the existence of as-yet-undiscovered “partners” for existing particles: The electron would be joined by a “selectron,” quarks by “squarks,” and so on. There was great hope that the $8-billion Large Hadron Collider would provide indirect evidence for these theories, but so far it hasn’t. (…)

[Marcelo Gleiser]: “We look out in the world and we see a very complicated pattern of stuff, and the notion of symmetry is an important way to make sense of the mess. The sun and moon are not perfect spheres, but that kind of approximation works incredibly well to simulate the behavior of these bodies.”

But the idea that what’s beautiful is true and that “symmetry rules,” as Gleiser puts it, “has been catapulted to an almost religious notion in the sciences,” he says. In his own book A Tear at the Edge of Creation (Free Press), Gleiser made a case for the beauty inherent in asymmetry—in the fact that neutrinos, the most common particles in the universe, spin only in one direction, for example, or that amino acids can be produced in laboratories in “left-handed” or “right-handed” forms, but only the “left-handed” form appears in nature. These are nature’s equivalent of Marilyn Monroe’s mole, attractive because of their lopsidedness, and Orrell also makes use of those examples.

But Weinberg, the Nobel-winning physicist at the University of Texas at Austin, counters: “Betting on beauty works remarkably well.” The Large Hadron Collider’s failure to produce evidence of supersymmetry is “disappointing,” he concedes, but he notes that plenty of elegant theories have waited years, even decades, for confirmation. Copernicus’s theory of a Sun-centered universe was developed entirely without experiment—he relied on Ptolemy’s data—and it was eventually embraced precisely because his description of planetary motion was simply more economical and elegant than those of his predecessors; it turned out to be true.

Closer to home, Weinberg says his own work on the weak nuclear force and electromagnetism had its roots in remarkably elegant, purely abstract theories of researchers who came before him, theories that, at first, seemed to be disproved by evidence but were too elegant to stop thinking about. (…)

To Orrell, it’s not just that many scientists are too enamored of beauty; it’s that their notion of beauty is ossified. It is “kind of clichéd,” Orrell says. “I find things like perfect symmetry uninspiring.” (In fairness, the Harvard theoretical physicist Lisa Randall has used the early unbalanced sculptures of Richard Serra as an example of how the asymmetrical can be as fascinating as the symmetrical, in art as in physics. She finds this yin-yang tension perfectly compatible with modern theorizing.)

Orrell also thinks it is more useful to study the behavior of complex systems rather than their constituent elements. (…)

Outside of physics, Orrell reframes complaints about “perfect-model syndrome” in aesthetic terms. Classical economists, for instance, treat humans as symmetrical in terms of what motivates decision-making. In contrast, behavioral economists are introducing asymmetry into that field by replacing Homo economicus with a quirkier, more idiosyncratic and human figure—an aesthetic revision, if you like. (…)

The broader issue, though, is whether science’s search for beautiful, enlightening patterns has reached a point of diminishing returns. If science hasn’t yet hit that point, might it be approaching it? The search for symmetry in nature has had so many successes, observes Stephon Alexander, a Dartmouth physicist, that “there is a danger of forgetting that nature is the one that decides where that game ends.”

— Christopher Shea, American writer and editor, Is Scientific Truth Always Beautiful?, The Chronicle of Higher Education, Jan 28, 2013.

The Asymmetry of Life

                
                                     Image courtesy of Ben Lansky

“Look into a mirror and you’ll simultaneously see the familiar and the alien: an image of you, but with left and right reversed.

Left-right inequality has significance far beyond that of mirror images, touching on the heart of existence itself. From subatomic physics to life, nature prefers asymmetry to symmetry. There are no equal liberties when neutrinos and proteins are concerned. In the case of neutrinos, particles that spill out of the sun’s nuclear furnace and pass through you by the trillions every second, only leftward-spinning ones exist. Why? No one really knows.

Proteins are long chains of amino acids that can be either left- or right-handed. Here, handedness has to do with how these molecules interact with polarized light, rotating it either to the left or to the right. When synthesized in the lab, amino acids come out fifty-fifty. In living beings, however, all proteins are made of left-handed amino acids. And all sugars in RNA and DNA are right-handed. Life is fundamentally asymmetric.

Is the handedness of life, its chirality (think chiromancer, which means “palm reader”), linked to its origins some 3.5 billion years ago, or did it develop after life was well on its way? If one traces life’s origins from its earliest stages, it’s hard to see how life began without molecular building blocks that were “chirally pure,” consisting solely of left- or right-handed molecules. Indeed, many models show how chirally pure amino acids may link to form precursors of the first protein-like chains. But what could have selected left-handed over right-handed amino acids?

My group’s research suggests that early Earth’s violent environmental upheavals caused many episodes of chiral flip-flopping. The observed left-handedness of terrestrial amino acids is probably a local fluke. Elsewhere in the universe, perhaps even on other planets and moons of our solar system, amino acids may be right-handed. But only sampling such material from many different planetary platforms will determine whether, on balance, biology is lefthanded, right-handed, or ambidextrous.”

— Marcelo Gleiser, The Asymmetry of Life, § SEEDMAGAZINE, Sep 7, 2010.

“One of the deepest consequences of symmetries of any kind is their relationship with conservation laws. Every symmetry in a physical system, be it balls rolling down planes, cars moving on roads, planets orbiting the Sun, a photon hitting an electron, or the expanding Universe, is related to a conserved quantity, a quantity that remains unchanged in the course of time. In particular, external (spatial and temporal) symmetries are related to the conservation of momentum and energy, respectively: the total energy and momentum of a system that is temporally and spatially symmetric remains unchanged.

The elementary particles of matter live in a reality very different from ours. The signature property of their world is change: particles can morph into one another, changing their identities. […] One of the greatest triumphs of twentieth-century particle physics was the discovery of the rules dictating the many metamorphoses of matter particles and the symmetry principles behind them. One of its greatest surprises was the realization that some of the symmetries are violated and that these violations have very deep consequences. (…) p.27

Even though matter and antimatter appear in equal footing on the equations describing relativistic particles, antimatter occurs only rarely. […] Somehow, during its infancy, the cosmos selected matter over antimatter. This imperfection is the single most important factor dictating our existence. (…)

Back to the early cosmos: had there been an equal quantity of antimatter particles around, they would have annihilated the corresponding particles of matter and all that would be left would be lots of gamma-ray radiation and some leftover protons and antiprotons in equal amounts. Definitely not our Universe. The tiny initial excess of matter particles is enough to explain the overwhelming excess of matter over antimatter in today’s Universe. The existence of mattter, the stuff we and everything else are made of, depends on a primordial imperfection, the matter-antimatter asymmetry. (…) p.29.

We have seen how the weak interactions violate a series of internal symmetries: charge conjugation, parity, and even the combination of the two. The consequences of these violations are deeply related to our existence: they set the arrow of time at the microscopic level, providing a viable mechanism to generate the excess of matter over antimatter. […] The message from modern particle physics and cosmology is clear: we are the products of imperfections in Nature. (…)

It is not symmetry and perfection that should be our guiding principle, as it has been for millennia. We don’t have to look for the mind of God in Nature and try to express it through our equations. The science we create is just that, our creation. Wonderful as it is, it is always limited, it is always constrained by what we know of the world. […] The notion that there is a well-defined hypermathematical structure that determines all there is in the cosmos is a Platonic delusion with no relationship to physical reality. (…) p. 35.

The critics of this idea miss the fact that a meaningless cosmos that produced humans (and possibly other intelligences) will never be meaningless to them (or to the other intelligences). To exist in a purposeless Universe is even more meaningful than to exist as the result of some kind of mysterious cosmic plan. Why? Because it elevates the emergence of life and mind to a rare event, as opposed to a ubiquitous and premeditated one. For millennia, we believed that God (or gods) protected us from extinction, that we were chosen to be here and thus safe from ultimate destruction. […]

When science proposes that the cosmos has a sense of purpose where in life is a premeditated outcome of natural events, a similar safety blanket mechanism is at play: if life fails here, it will succeed elsewhere. We don’t really need to preserve it. To the contrary, I will argue that unless we accept our fragility and cosmic loneliness, we will never act to protect what we have. (…)

The laws of physics and the laws of chemistry as presently understood have nothing to say about the emergence of life. As Paul Davies remarked in Cosmic Jackpot, notions of a life principle suffer from being teleologic, explaining life as the end goal, a purposeful cosmic strategy. The human mind, of course, would be the crown jewel of such creative drive. Once again we are “chosen” ones, a dangerous proposal. […] Arguments shifting the “mind of God” to the “mind of the cosmos” perpetuate our obsession with the notion of Oneness. Our existence need not be planned to be meaningful.” (…) p.49.

Unified theories, life principles, and self-aware universes are all expressions of our need to find a connection between who we are and the world we live in. I do not question the extreme importance of understanding the connection between man and the cosmos. But I do question that it has to derive from unifying principles. (…) p.50.

My point is that there is no Final Truth to be discovered, no grand plan behind creation. Science advances as new theories engulf or displace old ones. The growth is largely incremental, punctuated by unexpected, worldview-shattering discoveries about the workings of Nature. […]

Once we understand that science is the creation of human minds and not the pursuit of some divine plan (even if metaphorically) we shift the focus of our search for knowledge from the metaphysical to the concrete. (…) p.51.

For a clever fish, water is “just right“ for it to swim in. Had it been too cold, it would freeze; too hot, it would boil. Surely the water temperature had to be just right for the fish to exist. “I’m very important. My existence cannot be an accident,” the proud fish would conclude. Well, he is not very important. He is just a clever fish. The ocean temperature is not being controlled with the purpose of making it possible for it to exist. Quite the opposite: the fish is fragile. A sudden or gradual temperature swing would kill it, as any trout fisherman knows. We so crave for meaningful connections that we see them even when they are not there.

We are soulful creatures in a harsh cosmos. This, to me, is the essence of the human predicament. The gravest mistake we can make is to think that the cosmos has plans for us, that we are somehow special from a cosmic perspective. (…) p.52

We are witnessing the greatest mass extinction since the demise of the dinosaurs 65 million years ago. The difference is that for the first time in history, humans, and not physical causes, are the perpetrators. […] Life recovered from the previous five mass extinctions because the physical causes eventually ceased to act. Unless we understand what is happening and start acting toghether as a species we may end up carving the path toward our own destruction. (…)” p.56

— Marcelo Gleiser is the Appleton Professor of Natural Philosophy at Dartmouth College, A Tear at the Edge of Creation, Free Press, 2010.

See also:

☞ Symmetry in Physics - Bibliography - PhilPapers
☞ The Concept of Laws. The special status of the laws of mathematics and physics, Lapidarium notes
☞ Universe tag on Lapidarium notes

Daniel C. Dennett on an attempt to understand the mind; autonomic neurons, culture and computational architecture

“What Darwin and Turing had both discovered, in their different ways, was the existence of competence without comprehension.”

— Daniel C. Dennett, What Darwin’s theory of evolution teaches us about Alan Turing and artificial intelligence, Lapidarium

“I’m trying to undo a mistake I made some years ago, and rethink the idea that the way to understand the mind is to take it apart into simpler minds and then take those apart into still simpler minds until you get down to minds that can be replaced by a machine. This is called homuncular functionalism, because you take the whole person. You break the whole person down into two or three or four or seven sub persons that are basically agents. They’re homunculi, and this looks like a regress, but it’s only a finite regress, because you take each of those in turn and you break it down into a group of stupider, more specialized homunculi, and you keep going until you arrive at parts that you can replace with a machine, and that’s a great way of thinking about cognitive science. It’s what good old-fashioned AI tried to do and still trying to do.

The idea is basically right, but when I first conceived of it, I made a big mistake. I was at that point enamored of the McCulloch-Pitts logical neuron. McCulloch and Pitts had put together the idea of a very simple artificial neuron, a computational neuron, which had multiple inputs and a single branching output and a threshold for firing, and the inputs were either inhibitory or excitatory. They proved that in principle a neural net made of these logical neurons could compute anything you wanted to compute. So this was very exciting. It meant that basically you could treat the brain as a computer and treat the neuron as a sort of basic switching element in the computer, and that was certainly an inspiring over-simplification. Everybody knew is was an over-simplification, but people didn’t realize how much, and more recently it’s become clear to me that it’s a dramatic over-simplification, because each neuron, far from being a simple logical switch, is a little agent with an agenda, and they are much more autonomous and much more interesting than any switch.

The question is, what happens to your ideas about computational architecture when you think of individual neurons not as dutiful slaves or as simple machines but as agents that have to be kept in line and that have to be properly rewarded and that can form coalitions and cabals and organizations and alliances? This vision of the brain as a sort of social arena of politically warring forces seems like sort of an amusing fantasy at first, but is now becoming something that I take more and more seriously, and it’s fed by a lot of different currents.

Evolutionary biologist David Haig has some lovely papers on intrapersonal conflicts where he’s talking about how even at the level of the genetics, even at the level of the conflict between the genes you get from your mother and the genes you get from your father, the so-called madumnal and padumnal genes, those are in opponent relations and if they get out of whack, serious imbalances can happen that show up as particular psychological anomalies.

We’re beginning to come to grips with the idea that your brain is not this well-organized hierarchical control system where everything is in order, a very dramatic vision of bureaucracy. In fact, it’s much more like anarchy with some elements of democracy. Sometimes you can achieve stability and mutual aid and a sort of calm united front, and then everything is hunky-dory, but then it’s always possible for things to get out of whack and for one alliance or another to gain control, and then you get obsessions and delusions and so forth.

You begin to think about the normal well-tempered mind, in effect, the well-organized mind, as an achievement, not as the base state, something that is only achieved when all is going well, but still, in the general realm of humanity, most of us are pretty well put together most of the time. This gives a very different vision of what the architecture is like, and I’m just trying to get my head around how to think about that. (…)

The vision of the brain as a computer, which I still champion, is changing so fast. The brain’s a computer, but it’s so different from any computer that you’re used to. It’s not like your desktop or your laptop at all, and it’s not like your iPhone except in some ways. It’s a much more interesting phenomenon. What Turing gave us for the first time (and without Turing you just couldn’t do any of this) is a way of thinking in a disciplined way about phenomena that have, as I like to say, trillions of moving parts. Until late 20th century, nobody knew how to take seriously a machine with a trillion moving parts. It’s just mind-boggling.

You couldn’t do it, but computer science gives us the ideas, the concepts of levels, virtual machines implemented in virtual machines implemented in virtual machines and so forth. We have these nice ideas of recursive reorganization of which your iPhone is just one example and a very structured and very rigid one at that.

We’re getting away from the rigidity of that model, which was worth trying for all it was worth. You go for the low-hanging fruit first. First, you try to make minds as simple as possible. You make them as much like digital computers, as much like von Neumann machines, as possible. It doesn’t work. Now, we know why it doesn’t work pretty well. So you’re going to have a parallel architecture because, after all, the brain is obviously massively parallel.

It’s going to be a connectionist network. Although we know many of the talents of connectionist networks, how do you knit them together into one big fabric that can do all the things minds do? Who’s in charge? What kind of control system? Control is the real key, and you begin to realize that control in brains is very different from control in computers. Control in your commercial computer is very much a carefully designed top-down thing.

You really don’t have to worry about one part of your laptop going rogue and trying out something on its own that the rest of the system doesn’t want to do. No, they’re all slaves. If they’re agents, they’re slaves. They are prisoners. They have very clear job descriptions. They get fed every day. They don’t have to worry about where the energy’s coming from, and they’re not ambitious. They just do what they’re asked to do and do it brilliantly with only the slightest tint of comprehension. You get all the power of computers out of these mindless little robotic slave prisoners, but that’s not the way your brain is organized.

Each neuron is imprisoned in your brain. I now think of these as cells within cells, as cells within prison cells. Realize that every neuron in your brain, every human cell in your body (leaving aside all the symbionts), is a direct descendent of eukaryotic cells that lived and fended for themselves for about a billion years as free-swimming, free-living little agents. They fended for themselves, and they survived.

They had to develop an awful lot of know-how, a lot of talent, a lot of self-protective talent to do that. When they joined forces into multi-cellular creatures, they gave up a lot of that. They became, in effect, domesticated. They became part of larger, more monolithic organizations. My hunch is that that’s true in general. We don’t have to worry about our muscle cells rebelling against us, or anything like that. When they do, we call it cancer, but in the brain I think that (and this is my wild idea) maybe only in one species, us, and maybe only in the obviously more volatile parts of the brain, the cortical areas, some little switch has been thrown in the genetics that, in effect, makes our neurons a little bit feral, a little bit like what happens when you let sheep or pigs go feral, and they recover their wild talents very fast.

Maybe a lot of the neurons in our brains are not just capable but, if you like, motivated to be more adventurous, more exploratory or risky in the way they comport themselves, in the way they live their lives. They’re struggling amongst themselves with each other for influence, just for staying alive, and there’s competition going on between individual neurons. As soon as that happens, you have room for cooperation to create alliances, and I suspect that a more free-wheeling, anarchic organization is the secret of our greater capacities of creativity, imagination, thinking outside the box and all that, and the price we pay for it is our susceptibility to obsessions, mental illnesses, delusions and smaller problems.

We got risky brains that are much riskier than the brains of other mammals even, even more risky than the brains of chimpanzees, and that this could be partly a matter of a few simple mutations in control genes that release some of the innate competitive talent that is still there in the genomes of the individual neurons. But I don’t think that genetics is the level to explain this. You need culture to explain it.

‘Culture creates a whole new biosphere’

This, I speculate, is a response to our invention of culture; culture creates a whole new biosphere, in effect, a whole new cultural sphere of activity where there’s opportunities that don’t exist for any other brain tissues in any other creatures, and that this exploration of this space of cultural possibility is what we need to do to explain how the mind works.

Everything I just said is very speculative. I’d be thrilled if 20 percent of it was right. It’s an idea, a way of thinking about brains and minds and culture that is, to me, full of promise, but it may not pan out. I don’t worry about that, actually. I’m content to explore this, and if it turns out that I’m just wrong, I’ll say, “Oh, okay. I was wrong. It was fun thinking about it,” but I think I might be right.

I’m not myself equipped to work on a lot of the science; other people could work on it, and they already are in a way. The idea of selfish neurons has already been articulated by Sebastian Seung of MIT in a brilliant keynote lecture he gave at Society for Neuroscience in San Diego a few years ago. I thought, oh, yeah, selfish neurons, selfish synapses. Cool. Let’s push that and see where it leads. But there are many ways of exploring this. One of the still unexplained, so far as I can tell, and amazing features of the brain is its tremendous plasticity.

Mike Merzenich sutured a monkey’s fingers together so that it didn’t need as much cortex to represent two separate individual digits, and pretty soon the cortical regions that were representing those two digits shrank, making that part of the cortex available to use for other things. When the sutures were removed, the cortical regions soon resumed pretty much their earlier dimensions. If you blindfold yourself for eight weeks, as Alvaro Pascual-Leone does in his experiments, you find that your visual cortex starts getting adapted for Braille, for haptic perception, for touch.

The way the brain spontaneously reorganizes itself in response to trauma of this sort, or just novel experience, is itself one of the most amazing features of the brain, and if you don’t have an architecture that can explain how that could happen and why that is, your model has a major defect. I think you really have to think in terms of individual neurons as micro-agents, and ask what’s in it for them?

Why should these neurons be so eager to pitch in and do this other work just because they don’t have a job? Well, they’re out of work. They’re unemployed, and if you’re unemployed, you’re not getting your neuromodulators. If you’re not getting your neuromodulators, your neuromodulator receptors are going to start disappearing, and pretty soon you’re going to be really out of work, and then you’re going to die.

In this regard, I think of John Holland’s work on the emergence of order. His example is New York City. You can always find a place where you can get gefilte fish, or sushi, or saddles or just about anything under the sun you want, and you don’t have to worry about a state bureaucracy that is making sure that supplies get through. No. The market takes care of it. The individual web of entrepreneurship and selfish agency provides a host of goods and services, and is an extremely sensitive instrument that responds to needs very quickly.

Until the lights go out. Well, we’re all at the mercy of the power man. I am quite concerned that we’re becoming hyper-fragile as a civilization, and we’re becoming so dependent on technologies that are not as reliable as they should be, that have so many conditions that have to be met for them to work, that we may specialize ourselves into some very serious jams. But in the meantime, thinking about the self-organizational powers of the brain as very much like the self-organizational powers of a city is not a bad idea. It just reeks of over-enthusiastic metaphor, though, and it’s worth reminding ourselves that this idea has been around since Plato.

Plato analogizes the mind of a human being to the state. You’ve got the rulers and the guardians and the workers. This idea that a person is made of lots of little people is comically simpleminded in some ways, but that doesn’t mean it isn’t, in a sense, true. We shouldn’t shrink from it just because it reminds us of simpleminded versions that have been long discredited. Maybe some not so simpleminded version is the truth.

There are a lot of cultural fleas

My next major project will be trying to take another hard look at cultural evolution and look at the different views of it and see if I can achieve a sort of bird’s eye view and establish what role, if any, is there for memes or something like memes and what are the other forces that are operating. We are going to have to have a proper scientific perspective on cultural change. The old-fashioned, historical narratives are wonderful, and they’re full of gripping detail, and they’re even sometimes right, but they only cover a small proportion of the phenomena. They only cover the tip of the iceberg.

Basically, the model that we have and have used for several thousand years is the model that culture consists of treasures, cultural treasures. Just like money, or like tools and houses, you bequeath them to your children, and you amass them, and you protect them, and because they’re valuable, you maintain them and prepare them, and then you hand them on to the next generation and some societies are rich, and some societies are poor, but it’s all goods. I think that vision is true of only the tip of the iceberg.

Most of the regularities in culture are not treasures. It’s not all opera and science and fortifications and buildings and ships. It includes all kinds of bad habits and ugly patterns and stupid things that don’t really matter but that somehow have got a grip on a society and that are part of the ecology of the human species in the same way that mud, dirt and grime and fleas are part of the world that we live in. They’re not our treasures. We may give our fleas to our children, but we’re not trying to. It’s not a blessing. It’s a curse, and I think there are a lot of cultural fleas. There are lots of things that we pass on without even noticing that we’re doing it and, of course, language is a prime case of this, very little deliberate intentional language instruction goes on or has to go on.

Kids that are raised with parents pointing out individual objects and saying, “See, it’s a ball. It’s red. Look, Johnny, it’s a red ball, and this is a cow, and look at the horsy” learn to speak, but so do kids who don’t have that patient instruction. You don’t have to do that. Your kids are going to learn ball and red and horsy and cow just fine without that, even if they’re quite severely neglected. That’s not a nice observation to make, but it’s true. It’s almost impossible not to learn language if you don’t have some sort of serious pathology in your brain.

Compare that with chimpanzees. There are hundreds of chimpanzees who have spent their whole lives in human captivity. They’ve been institutionalized. They’ve been like prisoners, and in the course of the day they hear probably about as many words as a child does. They never show any interest. They never apparently get curious about what those sounds are for. They can hear all the speech, but it’s like the rustling of the leaves. It just doesn’t register on them as worth attention.

But kids are tuned for that, and it might be a very subtle tuning. I can imagine a few small genetic switches, which, if they were just in a slightly different position, would make chimpanzees just as pantingly eager to listen to language as human babies are, but they’re not, and what a difference it makes in their world! They never get to share discoveries the way we do and to share our learning. That, I think, is the single feature about human beings that distinguishes us most clearly from all others: we don’t have to reinvent the wheel. Our kids get the benefit of not just what grandpa and grandma and great grandpa and great grandma knew. They get the benefit of basically what everybody in the world knew in the years when they go to school. They don’t have to invent calculus or long division or maps or the wheel or fire. They get all that for free. It just comes as part of the environment. They get incredible treasures, cognitive treasures, just by growing up. (…)

A lot of naïve thinking by scientists about free will

“Moving Naturalism Forward” was a nice workshop that Sean Carroll put together out in Stockbridge a couple of weeks ago, and it was really interesting. I learned a lot. I learned more about how hard it is to do some of these things and that’s always useful knowledge, especially for a philosopher.

If we take seriously, as I think we should, the role that Socrates proposed for us as midwives of thinking, then we want to know what the blockades are, what the imagination blockades are, what people have a hard time thinking about, and among the things that struck me about the Stockbridge conference were the signs of people really having a struggle to take seriously some ideas which I think they should take seriously. (…)

I realized I really have my work cut out for me in a way that I had hoped not to discover. There’s still a lot of naïve thinking by scientists about free will. I’ve been talking about it quite a lot, and I do my best to undo some bad thinking by various scientists. I’ve had some modest success, but there’s a lot more that has to be done on that front. I think it’s very attractive to scientists to think that here’s this several-millennia-old philosophical idea, free will, and they can just hit it out of the ballpark, which I’m sure would be nice if it was true.

It’s just not true. I think they’re well intentioned. They’re trying to clarify, but they’re really missing a lot of important points. I want a naturalistic theory of human beings and free will and moral responsibility as much as anybody there, but I think you’ve got to think through the issues a lot better than they’ve done, and this, happily, shows that there’s some real work for philosophers.

Philosophers have done some real work that the scientists jolly well should know. Here’s an area where it was one of the few times in my career when I wanted to say to a bunch of scientists, “Look. You have some reading to do in philosophy before you hold forth on this. There really is some good reading to do on these topics, and you need to educate yourselves.”

A combination of arrogance and cravenness

The figures about American resistance to evolution are still depressing, and you finally have to realize that there’s something structural. It’s not that people are stupid, and I think it’s clear that people, everybody, me, you, we all have our authorities, our go-to people whose word we trust. If you want to question about the economic situation in Greece, for instance, you need to check it out with somebody whose opinion on that we think is worth taking seriously. We don’t try to work it out for ourselves. We find some expert that we trust, and right around the horn, whatever the issues are, we have our experts, and so a lot of people have as their experts on matters of science, they have their pastors. This is their local expert.

I don’t blame them. I wish they were more careful about vetting their experts and making sure that they found good experts. They wouldn’t choose an investment advisor, I think, as thoughtlessly as they go along with their pastor. I blame the pastors, but where do they get their ideas? Well, they get them from the hierarchies of their churches. Where do they get their ideas? Up at the top, I figure there’s some people that really should be ashamed of themselves. They know better.

They’re lying, and when I get a chance, I try to ask them that. I say, “Doesn’t it bother you that your grandchildren are going to want to know why you thought you had to lie to everybody about evolution?” I mean, really. They’re lies. They’ve got to know that these are lies. They’re not that stupid, and I just would love them to worry about what their grandchildren and great grandchildren would say about how their ancestors were so craven and so arrogant. It’s a combination of arrogance and cravenness.

We now have to start working on that structure of experts and thinking, why does that persist? How can it be that so many influential, powerful, wealthy, in-the-public people can be so confidently wrong about evolutionary biology? How did that happen? Why does it happen? Why does it persist? It really is a bit of a puzzle if you think about how they’d be embarrassed not to know that the world is round. I think that would be deeply embarrassing to be that benighted, and they’d realize it. They’d be embarrassed not to know that HIV is the vector of AIDS. They’d be embarrassed to not understand the way the tides are produced by the gravitational forces of the moon and the sun. They may not know the details, but they know that the details are out there. They could learn them in 20 minutes if they wanted to. How did they get themselves in the position where they could so blithely trust people who they’d never buy stocks and bonds from? They’d never trust a child’s operation to a doctor that was as ignorant and as ideological as these people. It is really strange. I haven’t got to the bottom of that. (…)

This pernicious sort of lazy relativism

[T]here’s a sort of enforced hypocrisy where the pastors speak from the pulpit quite literally, and if you weren’t listening very carefully, you’d think: oh my gosh, this person really believes all this stuff. But they’re putting in just enough hints for the sophisticates in the congregation so that the sophisticates are supposed to understand: Oh, no. This is all just symbolic. This is all just metaphorical. And that’s the way they want it, but of course, they could never admit it. You couldn’t put a little neon sign up over the pulpit that says, “Just metaphor, folks, just metaphor.” It would destroy the whole thing.

You can’t admit that it’s just metaphor even when you insist when anybody asks that it’s just metaphor, and so this professional doubletalk persists, and if you study it for a while the way Linda [pdf] and I have been doing, you come to realize that’s what it is, and that means they’ve lost track of what it means to tell the truth. Oh, there are so many different kinds of truth. Here’s where postmodernism comes back to haunt us. What a pernicious bit of intellectual vandalism that movement was! It gives license to this pernicious sort of lazy relativism.

One of the most chilling passages in that great book by William James, The Varieties of Religious Experience, is where he talks about soldiers in the military: “Far better is it for an army to be too savage, too cruel, too barbarous, thant to possess too much sentimentality and human reasonableness.” This is a very sobering, to me, a very sobering reflection. Let’s talk about when we went into Iraq. There was Rumsfeld saying, “Oh, we don’t need a big force. We don’t need a big force. We can do this on the cheap,” and there were other people, retrospectively we can say they were wiser, who said, “Look, if you’re going to do this at all, you want to go in there with such overpowering, such overwhelming numbers and force that you can really intimidate the population, and you can really maintain the peace and just get the population to sort of roll over, and that way actually less people get killed, less people get hurt. You want to come in with an overwhelming show of force.”

The principle is actually one that’s pretty well understood. If you don’t want to have a riot, have four times more police there than you think you need. That’s the way not to have a riot and nobody gets hurt because people are not foolish enough to face those kinds of odds. But they don’t think about that with regard to religion, and it’s very sobering. I put it this way.

Suppose that we face some horrific, terrible enemy, another Hitler or something really, really bad, and here’s two different armies that we could use to defend ourselves. I’ll call them the Gold Army and the Silver Army; same numbers, same training, same weaponry. They’re all armored and armed as well as we can do. The difference is that the Gold Army has been convinced that God is on their side and this is the cause of righteousness, and it’s as simple as that. The Silver Army is entirely composed of economists. They’re all making side insurance bets and calculating the odds of everything.

Which army do you want on the front lines? It’s very hard to say you want the economists, but think of what that means. What you’re saying is we’ll just have to hoodwink all these young people into some false beliefs for their own protection and for ours. It’s extremely hypocritical. It is a message that I recoil from, the idea that we should indoctrinate our soldiers. In the same way that we inoculate them against diseases, we should inoculate them against the economists’—or philosophers’—sort of thinking, since it might lead to them to think: am I so sure this cause is just? Am I really prepared to risk my life to protect? Do I have enough faith in my commanders that they’re doing the right thing? What if I’m clever enough and thoughtful enough to figure out a better battle plan, and I realize that this is futile? Am I still going to throw myself into the trenches? It’s a dilemma that I don’t know what to do about, although I think we should confront it at least.”

— Daniel C. Dennett is University Professor, Professor of Philosophy, and Co-Director of the Center for Cognitive Studies at Tufts University, The normal well-tempered mind, Edge, Jan 8, 2013.

‘The Intentional Stance’

“Dennett favours the theory (first suggested by Richard Dawkins) that our social learning has given us a second information highway (in addition to the genetic highway) where the transmission of variant cultural information (memes) takes place via differential replication. Software viruses, for example, can be understood as memes, and as memes evolve in complexity, so does human cognition: “The mind is the effect, not the cause.” (…)

Daniel Dennett: “Natural selection is not gene centrist and nor is biology all about genes, our comprehending minds are a result of our fast evolving culture. Words are memes that can be spoken and words are the best example of memes. Words have a genealogy and it’s easier to trace the evolution of a single word than the evolution of a language.” (…)

I don’t like theory of mind. I coined the phrase The Intentional Stance. [Dennett’s Intentional Stance encompasses attributing feelings, memories and beliefs to others as well as mindreading and predicting what someone will do next.] Do you need a theory to ride a bike? (…)

Riding a bike is a craft – you don’t need a theory. Autistic people might need a theory with which to understand other minds, but the rest of us don’t. If a human is raised without social interaction and without language they would be hugely disabled and probably lacking in empathy.”

— Daniel C. Dennett, Daniel Dennett: ‘I don’t like theory of mind’ – interview, The Guardian, 22 March 2013.

See also:

☞ Steven Pinker on the mind as a system of ‘organs of computation’, Lapidarium notes
☞ Quantum minds: Why we think like quarks - ‘To be human is to be quantum’, Lapidarium notes
☞ Human Connectome Project: understanding how different parts of the brain communicate to each other
☞ How Free Is Your Will?, Lapidarium notes
☞ Susan Blackmore on memes and “temes”
☞ Mind & Brain tag on Lapidarium notes

Kevin Slavin: How algorithms shape our world

“But the Turing test cuts both ways. You can’t tell if a machine has gotten smarter or if you’ve just lowered your own standards of intelligence to such a degree that the machine seems smart. If you can have a conversation with a simulated person presented by an AI program, can you tell how far you’ve let your sense of personhood degrade in order to make the illusion work for you?

People degrade themselves in order to make machines seem smart all the time. Before the crash, bankers believed in supposedly intelligent algorithms that could calculate credit risks before making bad loans. We ask teachers to teach to standardized tests so a student will look good to an algorithm. We have repeatedly demonstrated our species’ bottomless ability to lower our standards to make information technology look good. Every instance of intelligence in a machine is ambiguous.

The same ambiguity that motivated dubious academic AI projects in the past has been repackaged as mass culture today. Did that search engine really know what you want, or are you playing along, lowering your standards to make it seem clever? While it’s to be expected that the human perspective will be changed by encounters with profound new technologies, the exercise of treating machine intelligence as real requires people to reduce their mooring to reality.”

— Jaron Lanier, You are Not a Gadget (2010)

Kevin Slavin argues that we’re living in a world designed for — and increasingly controlled by — algorithms. In this riveting talk from TEDGlobal, he shows how these complex computer programs determine: espionage tactics, stock prices, movie scripts, and architecture.

“We’re writing things (…) that we can no longer read. And we’ve rendered something illegible, and we’ve lost the sense of what’s actually happening in this world that we’ve made. (…)

“We’re running through the United States with dynamite and rock saws so that an algorithm can close the deal three microseconds faster, all for a communications framework that no human will ever know; that’s a kind of manifest destiny.”

— Kevin Slavin, Entrepreneur, Raconteur Assistant Professor of Media Arts and Sciences, MIT Media Lab, Kevin Slavin: How algorithms shape our world, TED, July 2011.

See also:

☞ Jane Wakefield, When algorithms control the world, BBC, Aug 23, 2011.

Nicholas Carr on the meaning of ‘searching’ these days

“All collected data had come to a final end. Nothing was left to be collected. But all collected data had yet to be completely correlated and put together in all possible relationships. A timeless interval was spent doing that.”

— Isaac Asimov, “The Last Question”, cited in John Battelle’s The Search

“When we talk about “searching” these days, we’re almost always talking about using Google to find something online. That’s quite a twist for a word that has long carried existential connotations, that has been bound up in our sense of what it means to be conscious and alive. We don’t just search for car keys or missing socks. We search for truth and meaning, for love, for transcendence, for peace, for ourselves. To be human is to be a searcher.

In its highest form, a search has no well-defined object. It’s open-ended, an act of exploration that takes us out into the world, beyond the self, in order to know the world, and the self, more fully. T. S. Eliot expressed this sense of searching in his famously eloquent lines from “Little Gidding”:

We shall not cease from exploration

And the end of all our exploring

Will be to arrive where we started

And know the place for the first time.

Google searches have always been more cut and dried, keyed as they are to particular words or phrases. But in its original conception, the Google search engine did transport us into a messy and confusing world—the world of the web—with the intent of helping us make some sense of it. It pushed us outward, away from ourselves. It was a means of exploration. That’s much less the case now. Google’s conception of searching has changed markedly since those early days, and that means our own idea of what it means to search is changing as well.

Google’s goal is no longer to read the web. It’s to read us. Ray Kurzweil, the inventor and AI speculator, recently joined the company as its director of research. His general focus will be on machine learning and natural language processing. But his particular concern, as he said in a recent interview, will entail reconfiguring the company’s search engine to focus not outwardly on the world but inwardly on the user:

“I envision some years from now that the majority of search queries will be answered without you actually asking. It’ll just know this is something that you’re going to want to see.” While it may take some years to develop this technology, Kurzweil added that he personally thinks it will be embedded into what Google offers currently, rather than as a stand-alone product necessarily.

(…) Back in 2006, Eric Schmidt, then the company’s CEO, said that Google’s “ultimate product” would be a service that would “tell me what I should be typing.” It would give you an answer before you asked a question, obviating the need for searching entirely. (…)

In its new design, Google’s search engine doesn’t push us outward; it turns us inward. It gives us information that fits the behavior and needs and biases we have displayed in the past, as meticulously interpreted by Google’s algorithms. Because it reinforces the existing state of the self rather than challenging it, it subverts the act of searching. We find out little about anything, least of all ourselves, through self-absorption. (…)

To be turned inward, to listen to speech that is only a copy, or reflection, of our own speech, is to keep the universe alone. To free ourselves from that prison — the prison we now call personalization — we need to voyage outward to discover “counter-love,” to hear “original response.” As Frost understood, a true search is as dangerous as it is essential. It’s about breaking the shackles of the self, not tightening them.

There was a time, back when Larry Page and Sergey Brin were young and naive and idealistic, that Google spoke to us with the voice of original response. Now, what Google seeks to give us is copy speech, our own voice returned to us.”

— Nicholas Carr, American writer who has published books and articles on technology, business, and culture, The searchers, Rough Type, Jan 13, 2013.

See also:

☞ The Filter Bubble: Eli Pariser on What the Internet Is Hiding From You
☞ Tim Adams, Google and the future of search: Amit Singhal and the Knowledge Graph, The Observer, 19 January 2013.

Researchers discover surprising complexities in the way the brain makes mental maps

                    
Spatial location is closely connected to the formation of new memories. Until now, grid cells were thought to be part of a single unified map system. New findings from the Norwegian University of Science and Technology demonstrate that the grid system is in fact composed of a number of independent grid maps, each with unique properties. Each map displays a particular resolution (mesh size), and responds independently to changes in the environment. A system of several distinct grid maps (illustrated on left) can support a large number of unique combinatorial codes used to associate new memories formed with specific spatial information (illustrated on right).

“Your brain has at least four different senses of location – and perhaps as many as 10. And each is different, according to new research from the Kavli Institute for Systems Neuroscience, at the Norwegian University of Science and Technology. (…)

The findings, published in the 6 December 2012 issue of Nature, show that rather than just a single sense of location, the brain has a number of “modules” dedicated to self-location. Each module contains its own internal GPS-like mapping system that keeps track of movement, and has other characteristics that also distinguishes one from another.

“We have at least four senses of location,” says Edvard Moser, director of the Kavli Institute. “Each has its own scale for representing the external environment, ranging from very fine to very coarse. The different modules react differently to changes in the environment. Some may scale the brain’s inner map to the surroundings, others do not. And they operate independently of each other in several ways.”

This is also the first time that researchers have been able to show that a part of the brain that does not directly respond to sensory input, called the association cortex, is organized into modules. The research was conducted using rats. (…)

Technical breakthroughs

A rat’s brain is the size of a grape, while the area that keeps track of the sense of location and memory is comparable in size to a small grape seed. This tiny area holds millions of nerve cells.

A research team of six people worked for more than four years to acquire extensive electrophysiological measurements in this seed-sized region of the brain. New measurement techniques and a technical breakthrough made it possible for Hanne Stensola and her colleagues to measure the activity in as many as 186 grid cells of the same rat brain. A grid cell is a specialized cell named for its characteristic of creating hexagonal grids in the brain’s mental map of its surroundings.

“We knew that the ‘grid maps’ in this area of the brain had resolutions covering different scales, but we did not know how independent the scales were of each other,” Stensola said. “We then discovered that the maps were organized in four to five modules with different scales, and that each of these modules reacted slightly differently to changes in their environment. This independence can be used by the brain to create new combinations - many combinations - which is a very useful tool for memory formation.”

After analysing the activity of nearly 1000 grid cells, researchers were able to conclude that the brain has not just one way of making an internal map of its location, but several. Perhaps 10 different senses of location.

Perhaps 10 different senses of location

The entorhinal cortex is a part of the neocortex that represents space by way of brain cells that have GPS-like properties. Each cell describes the environment as a hexagonal grid mesh, earning them the name ‘grid cells’. The panels show a bird’s-eye view of a rat’s recorded movements (grey trace) in a 2.2x2.2 m box. Each panel shows the activity of one grid cell (blue dots) with a particular map resolution as the animal moved through the environment. Credit: Kavli Institute for Systems Neuroscience, NTNU

Institute director Moser says that while researchers are able to state with confidence that there are at least four different location modules, and have seen clear evidence of a fifth, there may be as many as 10 different modules.

He says, however, that researchers need to conduct more measurements before they will have covered the entire grid-cell area. “At this point we have measured less than half of the area,” he says.

Aside from the time and challenges involved in making these kinds of measurements, there is another good reason why researchers have not yet completed this task. The lower region of the sense of location area, the entorhinal cortex, has a resolution that is so coarse or large that it is virtually impossible to measure it.

“The thinking is that the coordinate points for some of these maps are as much as ten metres apart,” explains Moser. “To measure this we would need to have a lab that is quite a lot larger and we would need time to test activity over the entire area. We work with rats, which run around while we make measurements from their brain. Just think how long it would take to record the activity in a rat if it was running back and forth exploring every nook and cranny of a football field. So you can see that we have some challenges here in scaling up our experiments.”

New way to organize

Part of what makes the discovery of the grid modules so special is that it completely changes our understanding of how the brain physically organizes abstract functions. Previously, researchers have shown that brain cells in sensory systems that are directly adjacent to each other tend to have the same response pattern. This is how they have been able to create detailed maps of which parts of the sensory brain do what.

The new research shows that a modular organization is also found in the highest parts of the cortex, far away from areas devoted to senses or motor outputs. But these maps are different in the sense that they overlap or infiltrate other. It is thus not possible to locate the different modules with a microscope, because the cells that work together are intermingled with other modules in the same area.

“The various components of the grid map are not organized side by side,” explains Moser. “The various components overlap. This is the first time a brain function has been shown to be organized in this way at separate scales. We have uncovered a new way for neural network function to be distributed.”

A map and a constant

The researchers were surprised, however, when they started calculating the difference between the scales. They may have discovered an ingenious mathematical coding system, along with a number, a constant. (Anyone who has read or seen “The Hitchhiker’s Guide to the Galaxy” may enjoy this.) The scale for each sense of location is actually 42% larger than the previous one. “

We may not be able to say with certainty that we have found a mathematical constant for the way the brain calculates the scales for each sense of location, but it’s very funny that we have to multiply each measurement by 1.42 to get the next one. That is approximately equal to the square root of the number two,” says Moser.

Maps are genetically encoded

Moser thinks it is striking that the relationship between the various functional modules is so orderly. He believes this orderliness shows that the way the grid map is organized is genetically built in, and not primarily the result of experience and interaction with the environment.

So why has evolution equipped us with four or more senses of location?

Moser believes the ability to make a mental map of the environment arose very early in evolution. He explains that all species need to navigate, and that some types of memory may have arisen from brain systems that were actually developed for the brain’s sense of location.

“We see that the grid cells that are in each of the modules send signals to the same cells in the hippocampus, which is a very important component of memory,” explains Moser. “This is, in a way, the next step in the line of signals in the brain. In practice this means that the location cells send a different code into the hippocampus at the slightest change in the environment in the form of a new pattern of activity. So every tiny change results in a new combination of activity that can be used to encode a new memory, and, with input from the environment, becomes what we call memories.”

— Researchers discover surprising complexities in the way the brain makes mental maps, Medical press, Dec 5, 2012.

The article is a part of doctoral research conducted by Hanne and Tor Stensola, and has been funded through an Advanced Investigator Grant that Edvard Moser was awarded by the European Research Council (ERC).

See also:

☞ Hanne Stensola, Tor Stensola, Trygve Solstad, Kristian Frøland, May-Britt Moser & Edvard I. Moser, The entorhinal grid map is discretized, Nature, 5 Dec 2012.
☞ Mind & brain tag on Lapidarium notes

Cargo cult science by Richard Feynman
 

Adapted from the Caltech commencement address given in 1974.

“During the Middle Ages there were all kinds of crazy ideas, such as that a piece of rhinoceros horn would increase potency. Then a method was discovered for separating the ideas—which was to try one to see if it worked, and if it didn’t work, to eliminate it. This method became organized, of course, into science. And it developed very well, so that we are now in the scientific age. It is such a scientific age, in fact that we have difficulty in understanding how witch doctors could ever have existed, when nothing that they proposed ever really worked—or very little of it did.
 
But even today I meet lots of people who sooner or later get me into a conversation about UFOS, or astrology, or some form of mysticism, expanded consciousness, new types of awareness, ESP, and so forth. And I’ve concluded that it’s not a scientific world.
 
Most people believe so many wonderful things that I decided to investigate why they did. And what has been referred to as my curiosity for investigation has landed me in a difficulty where I found so much junk that I’m overwhelmed. First I started out by investigating various ideas of mysticism, and mystic experiences. I went into isolation tanks and got many hours of hallucinations, so I know something about that. Then I went to Esalen, which is a hotbed of this kind of thought (it’s a wonderful place; you should go visit there). Then I became overwhelmed. I didn’t realize how much there was.
 
At Esalen there are some large baths fed by hot springs situated on a ledge about thirty feet above the ocean. One of my most pleasurable experiences has been to sit in one of those baths and watch the waves crashing onto the rocky shore below, to gaze into the clear blue sky above, and to study a beautiful nude as she quietly appears and settles into the bath with me.
 
One time I sat down in a bath where there was a beautiful girl sitting with a guy who didn’t seem to know her. Right away I began thinking, “Gee! How am I gonna get started talking to this beautiful nude babe?”
 
I’m trying to figure out what to say, when the guy says to her, I’m, uh, studying massage. Could I practice on you?”
 
“Sure,” she says. They get out of the bath and she lies down on a massage table nearby.
 
I think to myself, “What a nifty line! I can never think of anything like that!” He starts to rub her big toe. “I think I feel it, “he says. “I feel a kind of dent—is that the pituitary?”
 
I blurt out, “You’re a helluva long way from the pituitary, man!”
 
They looked at me, horrified—I had blown my cover—and said, “It’s reflexology!”
 
I quickly closed my eyes and appeared to be meditating.
 
That’s just an example of the kind of things that overwhelm me. I also looked into extrasensory perception and PSI phenomena, and the latest craze there was Uri Geller, a man who is supposed to be able to bend keys by rubbing them with his finger. So I went to his hotel room, on his invitation, to see a demonstration of both mindreading and bending keys. He didn’t do any mindreading that succeeded; nobody can read my mind, I guess. And my boy held a key and Geller rubbed it, and nothing happened. Then he told us it works better under water, and so you can picture all of us standing in the bathroom with the water turned on and the key under it, and him rubbing the key with his finger. Nothing happened. So I was unable to investigate that phenomenon.
 
But then I began to think, what else is there that we believe? (And I thought then about the witch doctors, and how easy it would have been to cheek on them by noticing that nothing really worked.) So I found things that even more people believe, such as that we have some knowledge of how to educate. There are big schools of reading methods and mathematics methods, and so forth, but if you notice, you’ll see the reading scores keep going down—or hardly going up in spite of the fact that we continually use these same people to improve the methods. There’s a witch doctor remedy that doesn’t work. It ought to be looked into; how do they know that their method should work? Another example is how to treat criminals. We obviously have made no progress—lots of theory, but no progress— in decreasing the amount of crime by the method that we use to handle criminals.
 
Yet these things are said to be scientific. We study them. And I think ordinary people with commonsense ideas are intimidated by this pseudoscience. A teacher who has some good idea of how to teach her children to read is forced by the school system to do it some other way—or is even fooled by the school system into thinking that her method is not necessarily a good one. Or a parent of bad boys, after disciplining them in one way or another, feels guilty for the rest of her life because she didn’t do “the right thing,” according to the experts.
 
So we really ought to look into theories that don’t work, and science that isn’t science.
 
I think the educational and psychological studies I mentioned are examples of what I would like to call cargo cult science. In the South Seas there is a cargo cult of people. During the war they saw airplanes land with lots of good materials, and they want the same thing to happen now. So they’ve arranged to imitate things like runways, to put fires along the sides of the runways, to make a wooden hut for a man to sit in, with two wooden pieces on his head like headphones and bars of bamboo sticking out like antennas—he’s the controller—and they wait for the airplanes to land. They’re doing everything right. The form is perfect. It looks exactly the way it looked before. But it doesn’t work. No airplanes land. So I call these things cargo cult science, because they follow all the apparent precepts and forms of scientific investigation, but they’re missing something essential, because the planes don’t land.
 
Now it behooves me, of course, to tell you what they’re missing. But it would be just about as difficult to explain to the South Sea Islanders how they have to arrange things so that they get some wealth in their system. It is not something simple like telling them how to improve the shapes of the earphones. But there is one feature I notice that is generally missing in cargo cult science. That is the idea that we all hope you have learned in studying science in school—we never explicitly say what this is, but just hope that you catch on by all the examples of scientific investigation. It is interesting, therefore, to bring it out now and speak of it explicitly. It’s a kind of scientific integrity, a principle of scientific thought that corresponds to a kind of utter honesty—a kind of leaning over backwards. For example, if you’re doing an experiment, you should report everything that you think might make it invalid—not only what you think is right about it: other causes that could possibly explain your results; and things you thought of that you’ve eliminated by some other experiment, and how they worked—to make sure the other fellow can tell they have been eliminated.
 
Details that could throw doubt on your interpretation must be given, if you know them. You must do the best you can—if you know anything at all wrong, or possibly wrong—to explain it. If you make a theory, for example, and advertise it, or put it out, then you must also put down all the facts that disagree with it, as well as those that agree with it. There is also a more subtle problem. When you have put a lot of ideas together to make an elaborate theory, you want to make sure, when explaining what it fits, that those things it fits are not just the things that gave you the idea for the theory; but that the finished theory makes something else come out right, in addition.
 
In summary, the idea is to try to give all of the information to help others to judge the value of your contribution; not just the information that leads to judgment in one particular direction or another.
 
The easiest way to explain this idea is to contrast it, for example, with advertising. Last night I heard that Wesson oil doesn’t soak through food. Well, that’s true. It’s not dishonest; but the thing I’m talking about is not just a matter of not being dishonest, it’s a matter of scientific integrity, which is another level. The fact that should be added to that advertising statement is that no oils soak through food, if operated at a certain temperature. If operated at another temperature, they all will— including Wesson oil. So it’s the implication which has been conveyed, not the fact, which is true, and the difference is what we have to deal with.
 
We’ve learned from experience that the truth will come out. Other experimenters will repeat your experiment and find out whether you were wrong or right. Nature’s phenomena will agree or they’ll disagree with your theory. And, although you may gain some temporary fame and excitement, you will not gain a good reputation as a scientist if you haven’t tried to be very careful in this kind of work. And it’s this type of integrity, this kind of care not to fool yourself, that is missing to a large extent in much of the research in cargo cult science.
 
A great deal of their difficulty is, of course, the difficulty of the subject and the inapplicability of the scientific method to the subject. Nevertheless it should be remarked that this is not the only difficulty. That’s why the planes didn’t land—but they don’t land.
 
We have learned a lot from experience about how to handle some of the ways we fool ourselves. One example: Millikan measured the charge on an electron by an experiment with falling oil drops, and got an answer which we now know not to be quite right. It’s a little bit off, because he had the incorrect value for the viscosity of air. It’s interesting to look at the history of measurements of the charge of the electron, after Millikan. If you plot them as a function of time, you find that one is a little bigger than Millikan’s, and the next one’s a little bit bigger than that, and the next one’s a little bit bigger than that, until finally they settle down to a number which is higher.
 
Why didn’t they discover that the new number was higher right away? It’s a thing that scientists are ashamed of—this history—because it’s apparent that people did things like this: When they got a number that was too high above Millikan’s, they thought something must be wrong—and they would look for and find a reason why something might be wrong. When they got a number closer to Millikan’s value they didn’t look so hard. And so they eliminated the numbers that were too far off, and did other things like that. We’ve learned those tricks nowadays, and now we don’t have that kind of a disease.
 
But this long history of learning how not to fool ourselves—of having utter scientific integrity—is, I’m sorry to say, something that we haven’t specifically included in any particular course that I know of. We just hope you’ve caught on by osmosis.
 
The first principle is that you must not fool yourself—and you are the easiest person to fool. So you have to be very careful about that. After you’ve not fooled yourself, it’s easy not to fool other scientists. You just have to be honest in a conventional way after that.
 
I would like to add something that’s not essential to the science, but something I kind of believe, which is that you should not fool the layman when you’re talking as a scientist. I am not trying to tell you what to do about cheating on your wife, or fooling your girlfriend, or something like that, when you’re not trying to be a scientist, but just trying to be an ordinary human being. We’ll leave those problems up to you and your rabbi. I’m talking about a specific, extra type of integrity that is not lying, but bending over backwards to show how you are maybe wrong, that you ought to have when acting as a scientist. And this is our responsibility as scientists, certainly to other scientists, and I think to laymen.
 
For example, I was a little surprised when I was talking to a friend who was going to go on the radio. He does work on cosmology and astronomy, and he wondered how he would explain what the applications of this work were. “Well,” I said, “there aren’t any.” He said, “Yes, but then we won’t get support for more research of this kind.” I think that’s kind of dishonest. If you’re representing yourself as a scientist, then you should explain to the layman what you’re doing—and if they don’t want to support you under those circumstances, then that’s their decision.
 
One example of the principle is this: If you’ve made up your mind to test a theory, or you want to explain some idea, you should always decide to publish it whichever way it comes out. If we only publish results of a certain kind, we can make the argument look good. We must publish both kinds of results.
 
I say that’s also important in giving certain types of government advice. Supposing a senator asked you for advice about whether drilling a hole should be done in his state; and you decide it would be better in some other state. If you don’t publish such a result, it seems to me you’re not giving scientific advice. You’re being used. If your answer happens to come out in the direction the government or the politicians like, they can use it as an argument in their favor; if it comes out the other way, they don’t publish it at all. That’s not giving scientific advice.
 
Other kinds of errors are more characteristic of poor science. When I was at Cornell, I often talked to the people in the psychology department. One of the students told me she wanted to do an experiment that went something like this—it had been found by others that under certain circumstances, X, rats did something, A. She was curious as to whether, if she changed the circumstances to Y, they would still do A. So her proposal was to do the experiment under circumstances Y and see if they still did A.
 
I explained to her that it was necessary first to repeat in her laboratory the experiment of the other person—to do it under condition X to see if she could also get result A, and then change to Y and see if A changed. Then she would know that the real difference was the thing she thought she had under control.
 
She was very delighted with this new idea, and went to her professor. And his reply was, no, you cannot do that, because the experiment has already been done and you would be wasting time. This was in about 1947 or so, and it seems to have been the general policy then to not try to repeat psychological experiments, but only to change the conditions and see what happens.
 
Nowadays there’s a certain danger of the same thing happening, even in the famous (?) field of physics. I was shocked to hear of an experiment done at the big accelerator at the National Accelerator Laboratory, where a person used deuterium. In order to compare his heavy hydrogen results to what might happen with light hydrogen” he had to use data from someone else’s experiment on light hydrogen, which was done on different apparatus. When asked why, he said it was because he couldn’t get time on the program (because there’s so little time and it’s such expensive apparatus) to do the experiment with light hydrogen on this apparatus because there wouldn’t be any new result. And so the men in charge of programs at NAL are so anxious for new results, in order to get more money to keep the thing going for public relations purposes, they are destroying—possibly—the value of the experiments themselves, which is the whole purpose of the thing. It is often hard for the experimenters there to complete their work as their scientific integrity demands.
 
All experiments in psychology are not of this type, however. For example, there have been many experiments running rats through all kinds of mazes, and so on—with little clear result. But in 1937 a man named Young did a very interesting one. He had a long corridor with doors all along one side where the rats came in, and doors along the other side where the food was. He wanted to see if he could train the rats to go in at the third door down from wherever he started them off. No. The rats went immediately to the door where the food had been the time before.
 
The question was, how did the rats know, because the corridor was so beautifully built and so uniform, that this was the same door as before? Obviously there was something about the door that was different from the other doors. So he painted the doors very carefully, arranging the textures on the faces of the doors exactly the same. Still the rats could tell. Then he thought maybe the rats were smelling the food, so he used chemicals to change the smell after each run. Still the rats could tell. Then he realized the rats might be able to tell by seeing the lights and the arrangement in the laboratory like any commonsense person. So he covered the corridor, and still the rats could tell.
 
He finally found that they could tell by the way the floor sounded when they ran over it. And he could only fix that by putting his corridor in sand. So he covered one after another of all possible clues and finally was able to fool the rats so that they had to learn to go in the third door. If he relaxed any of his conditions, the rats could tell.
 
Now, from a scientific standpoint, that is an A-number-one experiment. That is the experiment that makes rat-running experiments sensible, because it uncovers the clues that the rat is really using—not what you think it’s using. And that is the experiment that tells exactly what conditions you have to use in order to be careful and control everything in an experiment with rat-running.
 
I looked into the subsequent history of this research. The next experiment, and the one after that, never referred to Mr. Young. They never used any of his criteria of putting the corridor on sand, or being very careful. They just went right on running rats in the same old way, and paid no attention to the great discoveries of Mr. Young, and his papers are not referred to, because he didn’t discover anything about the rats. In fact, he discovered all the things you have to do to discover something about rats. But not paying attention to experiments like that is a characteristic of cargo cult science.
 
Another example is the ESP experiments of Mr. Rhine, and other people. As various people have made criticisms—and they themselves have made criticisms of their own experiments—they improve the techniques so that the effects are smaller, and smaller, and smaller until they gradually disappear. All the parapsychologists are looking for some experiment that can be repeated—that you can do again and get the same effect—statistically, even. They run a million rats no, it’s people this time they do a lot of things and get a certain statistical effect. Next time they try it they don’t get it any more. And now you find a man saying that it is an irrelevant demand to expect a repeatable experiment. This is science?
 
This man also speaks about a new institution, in a talk in which he was resigning as Director of the Institute of Parapsychology. And, in telling people what to do next, he says that one of the things they have to do is be sure they only train students who have shown their ability to get PSI results to an acceptable extent— not to waste their time on those ambitious and interested students who get only chance results. It is very dangerous to have such a policy in teaching—to teach students only how to get certain results, rather than how to do an experiment with scientific integrity.
 
So I have just one wish for you—the good luck to be somewhere where you are free to maintain the kind of integrity I have described, and where you do not feel forced by a need to maintain your position in the organization, or financial support, or so on, to lose your integrity. May you have that freedom.”     

— Richard Feynman, American theoretical physicist known for his work in the path integral formulation of quantum mechanics, the theory of quantum electrodynamics, and the physics of the superfluidity of supercooled liquid helium, as well as in particle physics (he proposed the parton model), Laureate of the Nobel Prize in Physics, (1918-1988), Cargo cult science, Caltech commencement address given in 1974. (Pictures source: 1) Scientific American, 2) Richard Feynman at Caltech giving his famous lecture he entitled “There’s Plenty of Room at the Bottom.” (credit: California Institute of Technology))

See also:

☞ Richard Feynman on how we would look for a new law (the key to science)
☞ Richard Feynman on the way nature work: “You don’t like it? Go somewhere else!”
☞ Richard Feynman on the likelihood of Flying Saucers
☞ Richard Feynman tag on Lapidarium

Human Brain Is Wired for Harmony

Musical score based on the neurological activity of a 31-year-old woman. Image: Lu et al./PLoS One

“Since the days of the ancient Greeks, scientists have wondered why the ear prefers harmony. Now, scientists suggest that the reason may go deeper than an aversion to the way clashing notes abrade auditory nerves; instead, it may lie in the very structure of the ear and brain, which are designed to respond to the elegantly spaced structure of a harmonious sound. (…) If the chord is harmonic, or “consonant,” the notes are spaced neatly enough so that the individual fibers of the auditory nerve carry specific frequencies to the brain. By perceiving both the parts and the harmonious whole, the brain responds to what scientists call harmonicity. (…)

“Beating is the textbook explanation for why people don’t like dissonance, so our study is the first real evidence that goes against this assumption” (…) It suggests that consonance rests on the perception of harmonicity, and that, when questioning the innate nature of these preferences, one should study harmonicity and not beating.” (…)

Sensitivity to harmonicity is important in everyday life, not just in music,” he notes. For example, the ability to detect harmonic components of sound allows people to identify different vowel sounds, and to concentrate on one conversation in a noisy crowd.”

See also:

☞ M.Cousineaua, J. H. McDermottb, I. Peretz, The basis of musical consonance as revealed by congenital amusia (2012)
☞ S.Leinoa, E. Bratticob, M.Tervaniemib, P. Vuust, Representation of harmony rules in the humanbrain: Further evidence from event-related potentials, 2007
☞ Brandon Keim, Listen: The Music of a Human Brain, Wired Science, Nov 15, 2012.

A Book is Technology: An Interview with Tan Lin — “Reading is a kind of integrated software”

“People forget that a book or codex is a technology. My interest with HEATH and 7CV was to treat the book as a distinct medial platform through which a lot of ancillary information passes, much like a broadcast medium like TV or a narrow-cast medium like Twitter or Tumblr. Reading is information control, just as a metadata tag is a bibliographic control. So I wanted to highlight the book’s medial and time-based underpinnings. (…)

A book in Google Books, like someone’s search history, isn’t really a book; it’s data connected to other data, and it’s searchable. Reading, like autobiography, is a subset of a search function. (…)

“Reading is a kind of integrated software.”

Integrated software is a genre of software that combines word processing, database management, and spreadsheet applications, and communications platforms. This genre has been superseded by various full-function office suites, but I was interested in reading modelled in that way, i.e., different kinds of reading, each with specific functions. I mean, you read Harlequin romances differently than recipes, and you read Lotus 1-2-3 spreadsheets differently than you read Excel, and you read experimental Japanese novels differently than you read text messages, and in terms of documents processed by software, you have distinctions between, say, end-user manuals, bills of sales, Unified Modeling Language models, and legal contracts. These are genres of reading, and they’re housed or processed in the same generic platform that I call “reading.” So reading is an application that processes or assembles varied kinds of material. I was interested in creating works of literature that could be read like recipes or spreadsheets or PowerPoint presentations.  (…)

I think it’s a way to talk about new modalities of reading. In software engineering, the authoring is sometimes implemented with what are called frames, where kinds of (reading or processing) functionality are packed into frames, and where a frame is “a generic component in a hierarchy of nested subassemblies” (Wikipedia). You’ll have word processing frames and graphics frames, etc., and these individual frames can be linked in a unified programming system. This enables you to embed graphics and spreadsheet functions into a text document, or you can have shared graphical contexts, where material pops up in multiple frames at the same time—this, I think, is what is happening in 7CV with its graphical elements, text elements, processing text instructions in the form of prefaces (so-called “source” material) and meta data tags. I also inserted other languages: Chinese and machine codes. 7CV has various things in it that look like captions or interfaces or even bits of source code, and I was interested in the difference between a caption and bit of machine code in a book. If you look at the handwritten Chinese text in 7CV (it was written by my mother) you’ll notice that it was put in upside down by the typesetter! This is not true of the machine-generated Chinese, provided by Google Translate. But at any rate you have a complex ecosystem of different languages in single publishing/reading platform.

I assembled both PowerPoint works similarly. Bibliographic Sound Track was compiled from SMS, IM chats, video game walk-throughs, Tweets, Tumblr entries, PowerPoint bullet points, photographic slides, the overhead transparency, the text box, the couplet, the book page, the fading film titling sequence, etc. PowerPoint is a multimedia ecosystem that encompasses a wide variety of reading practices, and where each slide or page is a frame: modular, linked to other frames, and encompassing various platform specific reading or communications functions. So here was a generic poem, where a poem is the most varied collection of different material that could be read continuously in a time-based manner with a definite run time. Reading can be looped. That, I think, is the definition of a poem today!

Q: What are the differences between your PowerPoint works and your print books?  

The most obvious difference is that when you read a book or codex, the only thing moving is your eye; with the PowerPoint works, both text and eye are moving. In this sense, PowerPoint makes reading autonomous and it sets it in motion, literally: Individual slides are animated, slide transitions are animated, and the piece overall is software that is processing information. That’s why we turned out the lights during the screening and projected large: No one expects to go to the cinema and read a book on the screen, one word at a time, but that’s kind of what I wanted to do. The most beautiful thing is a book that could read itself! So reading is a kind of integrated software or the frame technology that manufactures software, and a book is the software application that is manufactured.

But I think there are a lot of similarities between digital and print-based reading experiences. The PowerPoint pieces, like my books, all bracket reading in a larger perceptual (and social) field that includes smells and sounds, i.e., they situate reading in a larger geography or reading environment. People tend to forget that reading is a kind of all-over experience, and it takes place in a particular room or in a particular moment of childhood. So the idea was to not confine reading to a particular object (book) or platform (PowerPoint) but allow it to expand outwards into the social space around it. I was more interested in what might be called the general mood of reading: the overall atmosphere or medium in which we experience our daily thoughts and perform actions—what Heidegger termed Stimmung and the psychologist Daniel Stern calls affective or amodal attunements. Bibliographic Sound Track is a mood-based system, but so is HEATH. And these mood-based systems, which are common to Zen meditative states, are bottom-up, non-directed, allotropic modes of general receptiveness rather than top-down, attention-based focus on specific objects or things. A book, at bottom, is a very general and very generic thing (that we happen to be reading). (…)

I’m not so interested in knowledge in that teleological sense; I’m more interested in the dissipation of knowledge, unfocused attention, and generic receptiveness. It would be nice if a book could reduce the amount of knowledge in the air. I’m equally interested in the public and communal architecture of reading practices as they intersect with individuals and park benches, the subway and the seminar room. Why can’t a book be more like a perfume? Or a door? Or the year after we graduated from college? A perfume is a communications medium just as literature is. Moods, furniture, restaurants, and books are communications mediums. What is it that Warhol said? “I think the right hormones can make Chanel No. 5 smell very butch.” (…)

For me, I think of reading as data management rather than passive absorption on a couch, though these dichotomies are ultimately false. Reading is and probably always will be a bit of both. At any rate, ideas about information processing are altering the contours of printed and digital works. Suddenly the book is just one element in a larger system of textual controls, distribution models, and controlled vocabulary systems. This is certainly true of the two PowerPoint works. I mean what are they? Are they poems or are they more like Twitter feeds? They don’t seem like PowerPoint presentations because they’re weak didactically and they don’t make a point. They are inflected by communications devices, but they do have a rhythm, which poems tend to have! And likewise with Twitter. Is it a broadcast medium using a pull system much like an RSS feed? Or is it more of a storage device, like a scroll or a poem? The idea of a network as a platform for collaborative work (rather than software housed on an individual’s desktop) might be applied to a book, no longer regarded as discrete, stand-alone object but as something that gets updated on a periodic basis in a social network. But this may not be that new an idea. After all, David Hume praised the printing press because it made it possible to issue countless emendations, revisions, and new editions.

Q: Can you state briefly what you see as the future of the book?

Let’s return for a moment to the bootleg by Westphalie Verlag in Vienna. Did the publisher David Jourdan in this case create what, under U.S. copyright law, would be termed “strong” copyleft where the derivative work is “based on the program” and has a “clear will to extend it to “dynamic linkage”? At this point, we are talking about software development licensing, shared libraries, primary access to source code, site linkages, share and share alike provisions, and software pools. My question is: Can a book be made to look like the authoring of such software, caught in a complicated licensing and development system? I think so! Maybe that’s the future of the book: to look like a licensing agreement regarding the future dissemination of its own information.”

— Tan Lin, Associate Professor of English and Creative Writing, New Jersey City University, A Book is Technology: An Interview with Tan Lin, Rhizome, Oct 24th, 2012. (Illustration source)