Category: biology

Bats and Belfries

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Thomas Nagel proposes a radical form of skepticism in his new book, Minds and Cosmos, continuing his trajectory through subjective experience and moral realism first began with bats zigging and zagging among the homunculi of dualism reimagined in the form of qualia. The skepticism involves disputing materialistic explanations and proposing, instead, that teleological ones of an unspecified form will likely apply, for how else could his subtitle that paints the “Neo-Darwinian Concept of Nature” as likely false hold true?

Nagel is searching for a non-religious explanation, of course, because just enervating nature through fiat is hardly an explanation at all; any sort of powerful, non-human entelechy could be gaming us and the universe in a non-coherent fashion. But what parameters might support his argument? Since he apparently requires a “significant likelihood” argument to hold sway in support of the origins of life, for instance, we might imagine what kind of thinking could result in highly likely outcomes that begin with inanimate matter and lead to goal-directed behavior while supporting a significant likelihood of that outcome. The parameters might involve the conscious coordination of the events leading towards the emergence of goal-directed life, thus presupposing a consciousness that is not our own. We are back then to our non-human entelechy looming like an alien or like a strange creator deity (which is not desirable to Nagel). We might also consider the possibility that there are properties to the universe itself that result in self-organization and that either we don’t yet know or that we are only beginning to understand. Elliot Sober’s critique suggests that the 2nd Law of Thermodynamics results in what I might call “patterned” behavior while not becoming “goal-directed” per se.… Read the rest

Evolutionary Art and Architecture

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With every great scientific advance there has been a coordinated series of changes in the Zeitgeist. Evolutionary theory has impacted everything from sociology through to literature, but there are some very sophisticated efforts in the arts that deserve more attention.

John Frazer’s Evolutionary Architecture is a great example. Now available as downloadable PDFs since it is out-of-print, Evolutionary Architecture asks the question, without fully answering it (how could it?), about how evolution-like processes can contribute to the design of structures:

And then there is William Latham’s evolutionary art that explores form derived from generative functions dating to 1989:

And the art extends to functional virtual creatures:

… Read the rest

Multitudes and the Mathematics of the Individual

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The notion that there is a path from reciprocal altruism to big brains and advanced cognitive capabilities leads us to ask whether we can create “effective” procedures that shed additional light on the suppositions that are involved, and their consequences. Any skepticism about some virulent kind of scientism then gets whisked away by the imposition of a procedure combined with an earnest interest in careful evaluation of the outcomes. That may not be enough, but it is at least a start.

I turn back to Marcus Hutter, Solomonoff, and Chaitin-Kolmogorov at this point.  I’ll be primarily referencing Hutter’s Universal Algorithmic Intelligence (A Top-Down Approach) in what follows. And what follows is an attempt to break down how three separate factors related to intelligence can be explained through mathematical modeling. The first and the second are covered in Hutter’s paper, but the third may represent a new contribution, though perhaps an obvious one without the detail work that is needed to provide good support.

First, then, we start with a core requirement of any goal-seeking mechanism: the ability to predict patterns in the environment external to the mechanism. This is well-covered since Solomonoff in the 60s who formalized the implicit arguments in Kolmogorov algorithmic information theory (AIT), and that were subsequently expanded on by Greg Chaitin. In essence, given a range of possible models represented by bit sequences of computational states, the shortest sequence that predicts the observed data is also the optimal predictor for any future data also produced by the underlying generator function. The shortest sequence is not computable, but we can keep searching for shorter programs and come up with unique optimizations for specific data landscapes. And that should sound familiar because it recapitulates Occam’s Razor and, in a subset of cases, Epicurus’ Principle of Multiple Explanations.… Read the rest

Reciprocity and Abstraction

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Fukuyama’s suggestion is intriguing but needs further development and empirical support before it can be considered more than a hypothesis. To be mildly repetitive, ideology derived from scientific theories should be subject to even more scrutiny than religious-political ideologies if for no other reason than it can be. But in order to drill down into the questions surrounding how reciprocal altruism might enable the evolution of linguistic and mental abstractions, we need to simplify the problems down to basics, then work outward.

So let’s start with reciprocal altruism as a mere mathematical game. The iterated prisoner’s dilemma is a case study: you and a compatriot are accused of a heinous crime and put in separate rooms. If you deny involvement and so does your friend you will each get 3 years prison. If you admit to the crime and so does your friend you will both get 1 year (cooperation behavior). But if you or your co-conspirator deny involvement while fingering the other, one gets to walk free while the other gets 6 years (defection strategy). Joint fingering is equivalent to two denials at 3 years since the evidence is equivocal. What does one do as a “rational actor” in order to minimize penalization? The only solution is to betray your friend while denying involvement (deny, deny, deny): you get either 3 years (assuming he also denies involvement), or you walk (he denies), or he fingers you also which is the same as dual denials at 3 years each. The average years served are 1/3*3 + 1/3*0 + 1/3*3 = 3 years versus 1/2*1 + 1/2*6 = 3.5 years for admitting to the crime.

In other words it doesn’t pay to cooperate.… Read the rest

Bostrom on the Hardness of Evolving Intelligence

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At 38,000 feet somewhere above Missouri, returning from a one day trip to Washington D.C., it is easy to take Nick Bostrom’s point that bird flight is not the end-all of what is possible for airborne objects and mechanical contrivances like airplanes in his paper, How Hard is Artificial Intelligence? Evolutionary Arguments and Selection Effects. His efforts to try to bound and distinguish the evolution of intelligence as either Hard or Not-Hard runs up against significant barriers, however. As a practitioner of the art, finding similarities between a purely physical phenomena like flying and something as complex as human intelligence falls flat for me.

But Bostrom is not taking flying as more than a starting point for arguing that there is an engineer-able possibility for intelligence. And that possibility might be bounded by a number of current and foreseeable limitations, not least of which is that computer simulations of evolution require a certain amount of computing power and representational detail in order to be a sufficient simulation. His conclusion is that we may need as much as another 100 years of improvements in computing technology just to get to a point where we might succeed at a massive-scale evolutionary simulation (I’ll leave to the reader to investigate his additional arguments concerning convergent evolution and observer selection effects).

Bostrom dismisses as pessimistic the assumption that a sufficient simulation would, in fact, require a highly detailed emulation of some significant portion of the real environment and the history of organism-environment interactions:

A skeptic might insist that an abstract environment would be inadequate for the evolution of general intelligence, believing instead that the virtual environment would need to closely resemble the actual biological environment in which our ancestors evolved … However, such extreme pessimism seems unlikely to be well founded; it seems unlikely that the best environment for evolving intelligence is one that mimics nature as closely as possible.

… Read the rest

From Smith to Darwin

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The notion that all the contingencies of human history can be rendered down into law-like principles is the greatest reflection of the human desire for order and understanding. Adam Smith appears in that mirrored pool alongside Karl Marx and, in his original form, even Charles Darwin. That’s only the beginning: Freud, Machiavelli, Rousseau, Hegel, and a host of others are reflected there in varying, and transitory clarity.

Adam Smith is a iconic case, as I discovered reading Adam Smith’s View of History: Consistent or Paradoxical? by James Alvey. The paradoxical component arises from a merger of a belief in the inevitability of commercial society and, at various points in Smith’s intellectual development, a cynicism about the probability of forward progress towards that goal. Ever behind the curtain, however, was the invisible hand represented by a kind of teleological divine presence moving history and economics forward.

The paper uncovers some of the idiosyncrasies of Smith’s economic history:

[T]he burghers felt secure enough to import ‘improved manufactures and expensive luxuries’. The lords now had something beside hospitality for which they could exchange the whole of their agricultural surplus. Previously they had to share, but ‘frivolous and useless’ things, such as ‘a pair of diamond [shoe] buckles’, and ‘trinkets and baubles’, could be consumed by the lords alone. The lords were fascinated with such finely crafted items and wanted to own and vainly display them. As the lords ‘eagerly purchased’ these luxury items they were forced to reduce the number of their dependents and eventually dismiss them entirely.

The lords ultimately have to trade off economic freedom of the artisans in exchange for more diamond shoe buckles. Odd, but perhaps reflective of the excesses of the wealthy in Smith’s era–something that needed explanation.… Read the rest

The Sooner We Are All Mongrels, the Better

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E.O. Wilson charges across the is-ought barrier with a zeal undiminished by his advancing years and promotes genetic diversity as a moral good in The Social Conquest of Earth:

Perhaps it is time…to adopt a new ethic of racial and hereditary variation, one that places value on the whole of diversity rather than on the differences composing the diversity. It would give proper measure to our species’ genetic variation as an asset, prized for the adaptability it provides all of us during an increasingly uncertain future. Humanity is strengthened by a broad portfolio of genes that can generate new talents, additional resistance to diseases, and perhaps even new ways of seeing reality. For scientific as well as moral reasons, we should learn to promote human biological diversity for its own sake instead of using it to justify prejudice and conflict.

This follows an analysis of the relative genetic differences between various racial groups of humans, concluding that subsaharan Africa contains the highest genetic diversity among human groups. Yet almost everything in our social and biological history suggests that we have formed social structures specifically to prevent out-breeding and limit the expansion of our genetic pool. This has always been a thorny subject for selfish genetics: why risk pairing your alleles with unknowns guessed at through proximal sexual clues like body symmetry or the quality of giant peacock tails? The risk of outbreeding is apparently lower than the risk of diverse infectious agents according to a common current theory, but we also see culture as overriding even the strongest outbreeding motivation by imposing mating rules based on familial and tribal power struggles. At the worst, we even see inbreeding depression in populations that consolidate power through close marriages (look at the sex-linked defect lineages in European royal families) or through long religious prohibitions on marrying outside of relatively small populations of the faithful.… Read the rest

John Gray on Jonathan Haidt

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Excellent discussion (and review) of Jonathan Haidt’s The Righteous Mind: Why Good People are Divided by Politics and Religion by John Gray in The New Republic. Gray is skeptical of intellectual history but even more skeptical of scientism, or the attempt to apply scientific reasoning to the complexities of human politics. Summing up concerning evolutionary psychology:

Haidt’s attempt to apply evolutionary psychology is yet one more example of the failures of scientism. There is no line of evolutionary development that connects our hominid ancestors with the emergence of the Tea Party. Human beings are not amoebae that have somehow managed to turn themselves into clever primates. They are animals with a history, part of which consists of creating cultures that are widely divergent. Using evolutionary psychology to explain current political conflicts represents local and ephemeral differences as perennial divisions in the human mind. It is hard to think of a more stultifying exercise in intellectual parochialism.

E.O. Wilson, Sam Harris, and David Sloan Wilson undoubtedly also included. The trouble arises in trying to connect the dots in too simple a contour. Haidt’s observations about flavors of moral feelings among liberals and conservatives is interesting and perhaps useful. But, as Gray suggests, it is where this naturalism ignores the cascading complexities of history that trouble arises. And when it tries to crawl onto the shores of policy and normative ethics, Gray takes even greater exception; the is-ought barrier is unassailable.

There are some assumptions by Gray that could use some critiquing. He quotes Haidt’s favorable perspective on utilitarianism and contrasts it with Berlin’s values pluralism. Gray is skeptical that culture war topics like abortion or gay rights can be cast into a utilitarian form and are better entertained through a recognition that a divergent moral landscape is the inevitable product of the complexities that culture hath wrought.… Read the rest

On the Non-Simulation of Human Intelligence

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There is a curious dilemma that pervades much machine learning research. The solutions that we are trying to devise are supposed to minimize behavioral error by formulating the best possible model (or collection of competing models). This is also the assumption of evolutionary optimization, whether natural or artificial: optimality is the key to efficiently outcompeting alternative structures, alternative alleles, and alternative conceptual models. The dilemma is whether such optimality is applicable to the notoriously error prone, conceptual flexible, and inefficient reasoning of people. In other words, is machine learning at all like human learning?

I came across a paper called “Multi-Armed Bandit Bayesian Decision Making” while trying to understand what Ted Dunning is planning to talk about at the Big Data Science Meetup at SGI in Fremont, CA a week from Saturday (I’ll be talking, as well) that has a remarkable admission concerning this point:

Human behaviour is after all heavily influenced by emotions, values, culture and genetics; as agents operating in a decentralised system humans are notoriously bad at coordination. It is this fact that motivates us to develop systems that do coordinate well and that operate outside the realms of emotional biasing. We use Bayesian Probability Theory to build these systems specifically because we regard it as common sense expressed mathematically, or rather `the right thing to do’.

The authors continue on to suggest that therefore such systems should instead be seen as corrective assistants for the limitations of human cognitive processes! Machines can put the rational back into reasoned decision-making. But that is really not what machine learning is used for today. Instead, machine learning is used where human decision-making processes are unavailable due to the physical limitations of including humans “in the loop,” or the scale of the data involved, or the tediousness of the tasks at hand.… Read the rest

Eusociality, Errors, and Behavioral Plasticity

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I encountered an error in E.O. Wilson’s The Social Conquest of Earth where the authors intended to assert an alternative to “kin selection” but instead repeated “multilevel selection,” which is precisely what the authors wanted to draw a distinction with. I am sympathetic, however, if for no other reason than I keep finding errors and issues with my own books and papers.

The critical technical discussion from Nature concerning the topic is available here. As technical discussion, the issues debated are fraught with details like how halictid bees appear to live socially, but are in fact solitary animals that co-exist in tunnel arrangements.

Despite the focus on “spring-loaded traits” as determiners for haplodiploid animals like bees and wasps, the problem of big-brained behavioral plasticity keeps coming up in Wilson’s book. Humanity is a pinnacle because of taming fire, because of the relative levels of energy available in animal flesh versus plant matter, and because of our ability to outrun prey over long distances (yes, our identity emerges from marathon running). But these are solutions that correlate with the rapid growth of our craniums.

So if behavioral plasticity is so very central to who we are, we are faced with an awfully complex problem in trying to simulate that behavior. We can expect that there must be phalanxes of genes involved in setting our developmental path (our nature and the substrate for our nurture). We should, indeed, expect that almost no cognitive capacity is governed by a small set of genes, and that all the relevant genes work in networks through polygeny, epistasis, and related effects (pleiotropy). And we can expect no easy answers as a result, except to assert that AI is exactly as hard as we should have expected, and progress will be inevitably slow in understanding the mind, the brain, and the way we interact.… Read the rest