Limits of Knowledge

Scientific Singularity?

A couple of weeks ago Kevin and I went around on the topic of whether or not science is “broken”.  We came to the point of agreeing that we have different basic assumptions of what constitutes “utility”.  And because of this, while we could agree that each of our arguments made sense logically, we ultimately end up with opposite conclusions.  After all, for something to be broken it means that it once served a purpose that it no longer is able to serve due to mechanical/structural failure.  And to have a purpose means that it has value (i.e. utility) to someone.

So whether science is broken or still works depends your definition of utility.  Kevin and I agreed on a measurement for scientific utility, based on (a) how well it explains observed phenomena, (b) how well it predicts new phenomena, and (c) how directly it leads to creation of technologies that improve human lives.  We can call it “explanatory power” or EP for short.  …

Is Science Broken?

By this I mean just what you think I mean.

Is science dysfunctional (i.e. functioning against its stated purpose) and could it be fixed?  I will leave it to you to determine what science’s stated purpose is, though by any standardly accepted definition, I claim that science is broken.  I’d like to run an experiment here to try to either change my belief or solidify it.

In the comments below, I invite you use the Like buttons to vote on what you believe.  You have only three boxes to choose from: Broken, Not Broken, and Undecided.  I respectfully ask you to first use the appropriate Like button and only then add your arguments/comments/questions if you have them.  Also, please categorize your arguments/comments/questions by making them replies to of one of the three top-level boxes (if you “think outside the boxes” I will delete your comment; sorry it’s my experiment :-)

In order to begin the debate, I will refer you to two blog entries which …

The AI-Box Experiment

Several years ago I became aware of Eliezer Yudkowsky’s “AI-Box Experiment” in which he plays the role of a transhuman “artificial intelligence” and attempts (via dialogue only) to convince a human “gatekeeper” to let him out of a box in which he is being contained (resumably so the AI doesn’t harm humanity).  Yudkowsky ran this experiment twice and both times he convinced the gatekeeper to let the AI out of the box, despite the fact that the gatekeeper swore up and down that there was no way to persuade him to do so.

I have to admit I think this is one of the most fascinating social experiments ever conceived, and I’m dying to play the game as gatekeeper.  The problem though that I realize after reading Yudkowsky’s writeup is that there are (at least) two preconditions which I don’t meet:

Currently, my policy is that I only run the test with people who are actually advocating that an AI Box be used …

The New Scientific Enlightenment

There is a massive paradigm shift occurring: beliefs about the nature of scientific inquiry that have held for hundreds of years are being questioned.

As laypeople, we see the symptoms all around us: climatology, economics, medicine, even fundamental physics; these domains (and more) have all become battlegrounds with mounting armies of Ph.D.s and Nobel Prize winners entrenching in opposing camps.  Here’s what’s at stake:

. . .

Scientific Objectivity

In 1972 Kahneman and Tversky launched the study into human cognitive bias, which later won Kahneman the Nobel.  Even a cursory reading of this now vast literature should make each and every logically-minded scientist very skeptical of their own work.

A few scientists do take bias seriously (c.f. Overcoming Bias and Less Wrong).  Yet, nearly 40 years later, it might be fair to say that its impact on science as a whole has been limited to improving clinical trials and spawning behavioral economics.

In 2008, Farhad Manjoo poignantly illustrates …

Epidemiology vs. Etiology

Over the last several years I’ve been digging into the science of cancer and systems biology, while at the same time looking at the epidemiology of disease and nutrition.  And the more I learn, the more I’m convinced that there’s a gap that our scientific tools and methodologies cannot account for.  While I’ve discussed this generally under the heading of Science 2.0 (also here), I’ve had a hard time putting into language the exact nature of the gap.

I’ve begun a series of posts that I hope will illustrate the gap, which I believe has to do with the fundamental difference between epidemiology (which is based on statistical observation) and etiology (which seeks to find causal mechanisms for observed phenomena):

Once I’ve completed these posts, I’ll attempt to explain the nature of the gap and what it means for the future of scientific inquiry.…

Why Falsifiability is Insufficient for Scientific Reasoning

In my post about The Process it turns out that I stepped on a pedagogical minefield when using describing the Anthropic Principle (AP).  Two preeminent physicists had a very public argument a while ago in which one called the AP unscientific because it’s unfalsifiable.  I will return to that in a moment since it’s the crux of what’s wrong with Science right now, but I need to get the terminology issue out of the way first.

Lee Smolin claims that AP is bad and favors a Cosmological Natural Selection view instead (on grounds of falsifiability).  I believe this is a false dichotomy and that they are really one and the same.  Here’s why:

  1. Normally natural selection requires some form of “replication” or it’s not actually natural selection.   But replication is not needed if you start with an infinity of heterogeneous universes.  In other words replication is simulated via the anthropic lens over the life-supporting subset of all possible universes.
  2. Replication is a red herring anyway

The Process

Imagine a multiverse, infinitely infinite.  There’s just infinity.  Or if you prefer, nothing.   There’s no space, no time, no matter, no energy.  There’s no structure whatsoever, and nothing “in” any of the universes that make up the multiverse.  it’s not even clear whether these individual universes are separate from one another or the same.  But since our minds seem finite and we have to start somewhere, let’s imagine them as separate: an infinite collection of universes with nothing in them, no dimension, and no relationship between them.

Now lets assume there is some process for picking out universes from the multiverse.  Since there’s no time in the multiverse, the process has no beginning and no end.  It’s like a computer program, but it’s infinitely complex.  Let’s call it The Process.

If The Process is infinitely complex and has no beginning and no end, what can we know about it?  We know that it picks some universes but not others, which effectively creates an “in …


How do we know what we know?

If you grew up like me you were brought up in a culture based on a dualist metaphysics, one that asserts that there is an objective reality outside of ourselves (whatever “we” are) and that we know about it indirectly through our senses and conscious reasoning.  This is the basis of the Western traditions of science, liberal arts and symbolic systems (such as mathematics and human language).  Essentially anything that can be studied is part of this metaphysics.  Gödel showed us that this metaphysics will never lead to complete knowing, though everyone agrees we can continually refine our knowledge and thereby at least asymptotically approach enlightenment.

Descartes proved to us that each of us individually do indeed exist, and he tried to argue further that the universe as we perceive it — however imperfectly — does indeed exist too.  But before you drink too deeply from the Cartesian well, keep in mind that his argument for an external

Newcomb's Meta-Paradox

Tweeter, Claus Metzner (@cmetzner) alerted me to this cool area of study with this paper.

Suppose you meet a Wise being (W) who tells you it has put $1,000 in box A, and either $1 million or nothing in box B. This being tells you to either take the contents of box B only, or to take the contents of both A and B. Suppose further that the being had put the $1 million in box B only if a prediction algorithm designed by the being had said that you would take only B. If the algorithm had predicted you would take both boxes, then the being put nothing in box B.  Presume that due to determinism, there exists a perfectly accurate prediction algorithm. Assuming W uses that algorithm, what choice should you make?…

Peer-Review vs. Info Prizes and Markets

I have been having a 140 character discussion with Ciarán Brewster (@macbruski) via twitter.  And while it’s kind of interesting to force complex subject matter into very few characters, it is limiting the discussion, so I will summarize it so far here and hopefully others can weigh in too.…

Stability Through Instability

A friend pointed me to a doubly prescient talk given by George Soros in 1994 about his theory of reflexivity in the markets.  Essentially Soros notes that there’s feedback in terms of what agents believe about the market and how the market behaves.  Not groundbreaking, but he takes this thinking to some logical conclusions which are in contrast to standard economic theory:…

The Good, The Bad & The Ugly

A few articles on the economy that were sent my way recently.

The Good: After Capitalism (Geoff Mulgan)

The era of transition that we are entering will be disruptive—but it may bring a world where markets are servants, not masters.”  I urge you to read this entire article, and leave your ideological biases at the door.  Despite the title, this is no polemic.  Here’s the punchline:

Contemporary biology and social science has confirmed just how much we are social animals—dependent on others for our happiness, our self-respect, our worth and even our life. There is no inherent contradiction between capitalism and community. But we have learned that these connections are not automatic: they have to be cultivated and rewarded, and societies that invest large proportions of their surpluses on advertising to persuade people that individual consumption is the best route to happiness end up paying a high price.

American Recovery and Reinvestment Act of 2009

Has anyone read the entire text of the stimulus package?

The ambiguity of this question is intentional.

Why It's Important to be an Optimist

The optimist proclaims that we live in the best of all possible worlds; and the pessimist fears this is true.  (James Branch Cabell)

I am currently reading What Are You Optimistic About?, a collection of short essays by thought leaders in many different disciplines on the eponymous subject.  I’m also reading True Enough, a compelling argument by Farhad Manjoo for how despite — nay, because of — the fire hose of information that permeates modern society and is available for the asking, the schism between what’s true and what we believe is widening; a polemic on polemics if you will.  Taken together, these two books suggest to me that there is a case, not for being optimistic per se, but for why you should consciously, actively try hard to become an optimist if you aren’t already.…

Making Great Decisions When it Counts

Some friends and I watched the above talk together by Dan Gilbert on the various ways humans made logical errors in decision making.  If you are a behavioral economist or are into psychology literature, you are probably all too familiar with the experiments on this subject, but it’s worth watching anyway.

There was some criticism of the talk in that it does ignore the fact that given limited resources in making decisions, the heuristics that we humans use (i.e. the rules of thumb, like price being a good indicator of quality) serve us very well most of the time.  It’s only under specific circumstances that these heuristics lead to logical errors and bad decisions.  Thus, the talk left some people thinking that the point Gilbert was making is that we’re all pretty bad decision makers and we should learn to transcend these error-prone heuristics.  The critics further suggested that no, we’re not bad decision makers, we are in fact really good 95% of the time, …

Complex Quotes: John Wheeler

“We have to learn how to use our words. It’s a fantastic thing — we humans are so easily trapped in our own words. The word time, for instance — we run into puzzles about the concept of time and then we say, oh, what a terrible thing. We don’t realize we’re the source of the puzzles because we invented the word….”

— John Wheeler…

Hive Mindstein

David Basanta’s blog has an interesting thread (quite a few of them actually).  Here’s the setup but you should read the original post, including the Wired article:

Apparently, some people are seeing some potential in cloud computing not just as an aid to science but as a completely new approach to do it. An article in Wired magazine argues precisely that. With the provocative title of The end of theory, the article concludes that, with plenty of data and clever algorithms (like those developed by Google), it is possible to obtain patterns that could be used to predict outcomes…and all that without the need of scientific models.

Global Warming

A few months ago a friend of mine engaged me in a discussion about the controversy surrounding global warming.  If you are surprised to hear that there is still controversy, read on; I was equally surprised.…

Open Letter to Gotham Prize

The Gotham Prize is a laudable new effort to provide incentive for new approaches to cancer.  In response to their recent announcement of their first awards, I have sent them the following open letter.  If you would like to express your own opinion on the matter, I encourage you to provide your feedback to them directly from their contact page.

Cancer Research Surprises

Many people would admit to not understanding cancer well, but fewer people would admit to not understanding evolution well.  Here are some challenges to our understanding of both.

Starvation may help cancer treatment. “As little as 48 hours of starvation afforded mice injected with brain cancer cells the ability to endure and benefit from extremely high doses of chemotherapy that non-starved mice could not survive.”

Notes from TED

Here are some notes that I took at TED 2008.  I have a bunch more on each of the speakers individually which I may post as time permits.  Let me know if you want me to expand any of the notes below into a full post.

Shermer on Science

Much of what gets published in scientific journals and is help up as “good science” these days is just an excuse for the authors to show off their math skills.  Never mind whether the mathematical models being used correspond to the reality they are supposed to be describing.  There is strong incentive based on the “publish or perish” dictum in academia for this trend to continue.  Michael Shermer wrote a recent Scientific American article which makes the case well and calls for more integrative and narrative scientific publishing.…

Complex Links: TED

I attended the TED Conference this year for the first time.  It was a transformative experience, one that I hope everyone can have in some form or another before too long.  One way to simulate being there is watch as many of these incredible talks from past TED conferences as you can in a short period of time.  If you are inspired, check out the TED Prize and how you can be a part of a growing global meta-movement for positive change in the world.

I will be blogging about things that piqued my interest at TED, but below are some cool links that I came away with:…

Mechanical Turk

A few months ago, on a different blog I posted a method for reading books for free on Amazon. Hopefully they didn’t take offense to this but rather saw it for what I did which was a way to get people interested in a book enough to want to purchase it. But just in case Amazon has any hard feelings, I will make amends here by plugging one of their little-known but extremely powerful services called Mechanical Turk.…

Seeing Sigmoids

One of the most basic but misleading heuristics that the human mind uses is that of linearity. If we see a progression (say 0, 1, 2), our first instinct is that the next step follows linearly (namely 3). But there is no a priori reason to prefer the linear interpretation to any other, say quadratic (which would suggest the next step in the sequence is 4). For whatever reason – probably due to the relative simplicity of linearity – our brains seem wired to prefer linear explanations to non-linear.…