Category: Evolutionary

The Abnormal Normal

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Another day, another COVID-19 conspiracy theory making the rounds. First there was the Chinese bioweapons idea, then the 5G radiation theory that led to tower vandalism, and now the Plandemic video. Washington Post covers the latter while complaining that tech companies are incompetently ineffectual in stopping the spread of these mind viruses that accompany the biological ones. Meanwhile, a scientist who appears in the video is reviewed and debunked in AAAS Science based on materials she provided them. I’m still interested in these “sequences” in the Pacific Ocean. I’ve spent some time in there and may need to again.

The WaPo article ends with a suggestion that we all need to be more skeptical of dumb shit, though I’m guessing that that message will probably not reach the majority of believers or propagators of Plandemic-style conspiracy thinking. So it goes with all the other magical nonsense that percolates through our ordinary lives, confined as they are to only flights of fancy and hopeful aspirations for a better world.

Broadly, though, it does appear that susceptibility to conspiracy theories correlates with certain mental traits that linger at the edge of mental illnesses. Evita March and Jordan Springer got 230 mostly undergraduate students to answer online questionnaires that polled them on mental traits of schizotypy, Machiavellianism, trait narcissism, and trait psychopathy. They also evaluated their belief in odd/magical ideas. Their paper, Belief in conspiracy theories: The predictive role of schizotypy, Machiavellianism, and primary psychopathy, shows significant correlations with belief in conspiracies. Interestingly, they suggest that the urge to manipulate others in Machiavellianism and psychopathy may, in turn, lead to an innate fear of being manipulated oneself.

Mental illness and certain psychological traits have always been a bit of an evolutionary mystery.… Read the rest

Forever Uncanny

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Quanta has a fair round up of recent advances in deep learning. Most interesting is the recent performance on natural language understanding tests that are close to or exceed mean human performance. Inevitably, John Searle’s Chinese Room argument is brought up, though the author of the Quanta article suggests that inferring the Chinese translational rule book from the data itself is slightly different from the original thought experiment. In the Chinese Room there is a person who knows no Chinese but has a collection of translational reference books. She receives texts through a slot and dutifully looks up the translation of the text and passes out the result. “Is this intelligence?” is the question and it serves as a challenge to the Strong AI hypothesis. With statistical machine translation methods (and their alternative mechanistic implementation, deep learning), the rule books have been inferred by looking at translated texts (“parallel” texts as we say in the field). By looking at a large enough corpus of parallel texts, greater coverage of translated variants is achieved as well as some inference of pragmatic issues in translation and corner cases.

As a practical matter, it should be noted that modern, professional translators often use translation memory systems that contain idiomatic—or just challenging—phrases that they can reference when translating new texts. The understanding resides in the original translator’s head, we suppose, and in the correct application of the rule to the new text by checking for applicability according to, well, some other criteria that the translator brings to bear on the task.

In the General Language Understand Evaluation (GLUE) tests described in the Quanta article, the systems are inferring how to answer Wh-style queries (who, what, where, when, and how) as well as identify similar texts.… Read the rest

A Most Porous Barrier

Mark Davis2 Comments

Whenever there is a scientific—or even a quasi-scientific—theory invented, there are those who take an expansive view of the theory, broadly applying it to other areas of thought. This is perhaps inherent in the metaphorical nature of these kinds of thought patterns. Thus we see Darwinian theory influenced by Adam Smith’s “invisible hand” of economic optimization. Then we get Spencer’s Social Darwinism arising from Darwin. And E.O. Wilson’s sociobiology leads to evolutionary psychology, immediately following an activist’s  pitcher of ice water.

The is-ought barrier tends towards porousness, allowing the smuggling of insights and metaphors lifted from the natural world as explanatory footwork for our complex social and political interactions. After all, we are as natural as we are social. But at the same time, we know that science is best when it is tentative and subject to infernal levels of revision and reconsideration. Decisions about social policy derived from science, and especially those that have significant human impact, should be cushioned by a tentative level of trust as well.

E.O. Wilson’s most recent book, Genesis: The Deep Origin of Societies, is a continuation of his late conversion to what is now referred to as “multi-level selection,” where natural selection is believed to operate at multiple levels, from genes to whole societies. It remains a controversial theory that has been under development and under siege since Darwin’s time, when the mechanism of inheritance was not understood.

The book is brief and does not provide much, if any, new material since his Social Conquest of Earth, which was significantly denser and contained notes derived from his controversial 2010 Nature paper that called into question whether kin selection was overstated as a gene-level explanation of altruism and sacrifice within eusocial species.… Read the rest

Narcissism, Nonsense and Pseudo-Science

Mark Davis5 Comments

I recently began posting pictures of our home base in Sedona to Instagram (check it out in column to right). It’s been a strange trip. If you are not familiar with how Instagram works, it’s fairly simple: you post pictures and other Instagram members can “follow” you and you can follow them, meaning that you see their pictures and can tap a little heart icon to show you like their pictures. My goal, if I have one, is just that I like the Northern Arizona mountains and deserts and like thinking about the composition of photographs. I’m also interested in the gear and techniques involved in taking and processing pictures. I did, however, market my own books on the platform—briefly, and with apologies.

But Instagram, like Facebook, is a world unto itself.

Shortly after starting on the platform, I received follows from blond Russian beauties who appear to be marketing online sex services. I have received odd follows from variations on the same name who have no content on their pages and who disappear after a day or two if I don’t follow them back. Though I don’t have any definitive evidence, I suspect these might be bots. I have received follows from people who seemed to be marketing themselves as, well, people—including one who bait-and-switched with good landscape photography. They are typically attractive young people, often showing off their six-pack abs, and trying to build a following with the goal of making money off of Instagram. Maybe they plan to show off products or reference them, thus becoming “influencers” in the lingo of social media. Maybe they are trying to fund their travel experiences by reaping revenue from advertisers that co-exist with their popularity in their image feed.… Read the rest

Theoretical Reorganization

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Sean Carroll of Caltech takes on the philosophy of science in his paper, Beyond Falsifiability: Normal Science in a Multiverse, as part of a larger conversation on modern theoretical physics and experimental methods. Carroll breaks down the problems of Popper’s falsification criterion and arrives at a more pedestrian Bayesian formulation for how to view science. Theories arise, theories get their priors amplified or deflated, that prior support changes due to—often for Carroll—coherence reasons with other theories and considerations and, in the best case, the posterior support improves with better experimental data.

Continuing with the previous posts’ work on expanding Bayes via AIT considerations, the non-continuous changes to a group of scientific theories that arrive with new theories or data require some better model than just adjusting priors. How exactly does coherence play a part in theory formation? If we treat each theory as a binary string that encodes a Turing machine, then the best theory, inductively, is the shortest machine that accepts the data. But we know that there is no machine that can compute that shortest machine, so there needs to be an algorithm that searches through the state space to try to locate the minimal machine. Meanwhile, the data may be varying and the machine may need to incorporate other machines that help improve the coverage of the original machine or are driven by other factors, as Carroll points out:

We use our taste, lessons from experience, and what we know about the rest of physics to help guide us in hopefully productive directions.

The search algorithm is clearly not just brute force in examining every micro variation in the consequences of changing bits in the machine. Instead, large reusable blocks of subroutines get reparameterized or reused with variation.… Read the rest

Hypersensitive Conspiracy Disorder

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I was once cornered in a bar in Suva, Fiji by an Indian man who wanted to unburden himself and complain a bit. He was convinced that the United States had orchestrated the coups of 1987 in which the ethnically Fijian-dominated military took control of the country. The theory went like this: ethnic Indians had too much power for the Americans to bear as we were losing Subic Bay as a deep water naval base in the South Pacific. Suva was the best, nearest alternative but the Indians, with their cultural and political ties to New Delhi, were too socialist for the Americans. Hence the easy solution was to replace the elected government with a more pro-American authoritarian regime. Yet another Cold War dirty tricks effort, like Mossaddegh or Allende, far enough away that the American people just shrugged our collective shoulders. My drinking friend’s core evidence was an alleged sighting of Oliver North by someone, sometime, chatting with government officials. Ollie was the 4D chess grandmaster of the late 80s.

It didn’t work out that way, of course, and the coups continued into the 2000s. More amazing still was that the Berlin Wall came down within weeks of that bar meetup and the entire engagement model for world orders slid into a brief decade of deconstruction and confusion. Even the economic dominance of Japan ebbed and dissipated around the same time.

But our collective penchant for conspiracy theories never waned. And with the growth of the internet and then social media, the speed and ease of disseminating fringe and conspiratorial ideas has only increased. In the past week there were a number of news articles about the role of conspiracy theories, from a so-called “QAnon” advocate meeting with Trump to manipulation of the government by Israel’s Black Cube group.… Read the rest

Deep Simulation in the Southern Hemisphere

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I’m unusually behind in my postings due to travel. I’ve been prepping for and now deep inside a fresh pass through New Zealand after two years away. The complexity of the place seems to have a certain draw for me that has lured me back, yet again, to backcountry tramping amongst the volcanoes and glaciers, and to leasurely beachfront restaurants painted with eruptions of summer flowers fueled by the regular rains.

I recently wrote a technical proposal that rounded up a number of the most recent advances in deep learning neural networks. In each case, like with Google’s transformer architecture, there is a modest enhancement that is based on a realization of a deficit in the performance of one of two broad types of networks, recurrent and convolutional.

An old question is whether we learn anything about human cognition if we just simulate it using some kind of automatically learning mechanism. That is, if we use a model acquired through some kind of supervised or unsupervised learning, can we say we know anything about the original mind and its processes?

We can at least say that the learning methodology appears to be capable of achieving the technical result we were looking for. But it also might mean something a bit different: that there is not much more interesting going on in the original mind. In this radical corner sits the idea that cognitive processes in people are tactical responses left over from early human evolution. All you can learn from them is that they may be biased and tilted towards that early human condition, but beyond that things just are the way they turned out.

If we take this position, then, we might have to discard certain aspects of the social sciences.… Read the rest

The Obsessive Dreyfus-Hawking Conundrum

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I’ve been obsessed lately. I was up at 5 A.M. yesterday and drove to Ruidoso to do some hiking (trails T93 to T92, if interested). The San Augustin Pass was desolate as the sun began breaking over, so I inched up into triple digit speeds in the M6. Because that is what the machine is made for. Booming across White Sands Missile Range, I recalled watching base police work with National Park Rangers to chase oryx down the highway while early F117s practiced touch-and-gos at Holloman in the background, and then driving my carpool truck out to the high energy laser site or desert ship to deliver documents.

I settled into Starbucks an hour and a half later and started writing on ¡Reconquista!, cranking out thousands of words before trying to track down the trailhead and starting on my hike. (I would have run the thing but wanted to go to lunch later and didn’t have access to a shower. Neither restaurant nor diners deserve an après-run moi.) And then I was on the trail and I kept stopping and taking plot and dialogue notes, revisiting little vignettes and annotating enhancements that I would later salt in to the main text over lunch. And I kept rummaging through the development of characters, refining and sifting the facts of their lives through different sets of sieves until they took on both a greater valence within the story arc and, often, more comedic value.

I was obsessed and remain so. It is a joyous thing to be in this state, comparable only to working on large-scale software systems when the hours melt away and meals slip as one cranks through problem after problem, building and modulating the subsystems until the units begin to sing together like a chorus.… Read the rest

Evolving Visions of Chaotic Futures

Mark Davis1 Comment

FlutterbysMost artificial intelligence researchers think unlikely the notion that a robot apocalypse or some kind of technological singularity is coming anytime soon. I’ve said as much, too. Guessing about the likelihood of distant futures is fraught with uncertainty; current trends are almost impossible to extrapolate.

But if we must, what are the best ways for guessing about the future? In the late 1950s the Delphi method was developed. Get a group of experts on a given topic and have them answer questions anonymously. Then iteratively publish back the group results and ask for feedback and revisions. Similar methods have been developed for face-to-face group decision making, like Kevin O’Connor’s approach to generating ideas in The Map of Innovation: generate ideas and give participants votes equaling a third of the number of unique ideas. Keep iterating until there is a consensus. More broadly, such methods are called “nominal group techniques.”

Most recently, the notion of prediction markets has been applied to internal and external decision making. In prediction markets,  a similar voting strategy is used but based on either fake or real money, forcing participants towards a risk-averse allocation of assets.

Interestingly, we know that optimal inference based on past experience can be codified using algorithmic information theory, but the fundamental problem with any kind of probabilistic argument is that much change that we observe in society is non-linear with respect to its underlying drivers and that the signals needed are imperfect. As the mildly misanthropic Nassim Taleb pointed out in The Black Swan, the only place where prediction takes on smooth statistical regularity is in Las Vegas, which is why one shouldn’t bother to gamble.… Read the rest

On Woo-Woo and Schrödinger’s Cat

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schrodingers-cat-walks-into-a-bar-memeMichael Shermer and Sam Harris got together with an audience at Caltech to beat up on Deepak Chopra and a “storyteller” named Jean Houston in The Future of God debate hosted by ABC News. And Deepak got uncharacteristically angry back behind his crystal-embellished eyewear, especially at Shermer’s assertion that Deepak is just talking “woo-woo.”

But is there any basis for the woo-woo that Deepak is weaving? As it turns out, he is building on some fairly impressive work by Stuart Hameroff, MD, of University of Arizona and Sir Roger Penrose of Oxford University. Under development for more than 25 years, this work has most recently been summed up in their 2014 paper, “Consciousness in the universe: A review of the ‘Orch OR’ theory” available for free (but not the commentaries, alas). Deepak was even invited to comment on the paper in Physics of Life Reviews, though the content of his commentary was challenged as being somewhat orthogonal or contradictory to the main argument.

To start somewhere near the beginning, Penrose became obsessed with the limits of computation in the late 80s. The Halting Problem sums up his concerns about the idea that human minds can possibly be isomorphic with computational devices. There seems to be something that allows for breaking free of the limits of “mere” Turing Complete computation to Penrose. Whatever that something is, it should be physical and reside within the structure of the brain itself. Hameroff and Penrose would also like that something to explain consciousness and all of its confusing manifestations, for surely consciousness is part of that brain operation.

Now, to get at some necessary and sufficient sorts of explanations for this new model requires looking at Hameroff’s medical speciality: anesthesiology.… Read the rest