Category: Evolutionary

Sentience is Physical

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Sentience is all the rage these days. With large language models (LLMs) based on deep learning neural networks, question-answering behavior of these systems takes on curious approximations to talking with a smart person. Recently a member of Google’s AI team was fired after declaring one of their systems sentient. His offense? Violating public disclosure rules. I and many others who have a firm understanding of how these systems work—by predicting next words from previous productions crossed with the question token stream—are quick to dismiss the claims of sentience. But what does sentience really amount to and how can we determine if a machine becomes sentient?

Note that there are those who differentiate sentience (able to have feelings), from sapience (able to have thoughts), and consciousness (some private, subjective phenomenal sense of self). I am willing to blend them together a bit since the topic here isn’t narrowly trying to address the ethics of animal treatment, for example, where the distinction can be useful.

First we have the “imitation game” Turing test-style approach to the question of how we might ever determine if a machine becomes sentient. If a remote machine can fool a human into believing it is a person, it must be as intelligent as a person and therefore sentient like we presume of people. But this is a limited goal line. If the interaction is only over a limited domain like solving your cable internet installation problems, we don’t think of that as a sentient machine. Even against a larger domain of open-ended question and answering, if the human doesn’t hit upon a revealing kind of error that a machine might make that a human would not, we remain unconvinced that the target is sentient.… Read the rest

Type 2 Modular Cognitive Responsibility for a New Year

Mark Davis1 Comment

Brain on QI’m rebooting a startup that I had set aside a year ago. I’ve had some recent research and development advances that make it again seem worth pursuing. Specifically, the improved approach uses a deep learning decision-making filter of sorts to select among natural language generators based on characteristics of the interlocutor’s queries. The channeling to the best generator uses word and phrase cues, while the generators themselves are a novel deep learning framework that integrates ontologies about specific domain areas or motives of the chatbot. Some of the response systems involve more training than others. They are deeper and have subtle goals in responding to the query. Others are less nuanced and just engage in non-performative casual speech.

In social and cognitive psychology there is some recent research that bears a resemblance to this and also is related to contemporary politics and society. Well, cognitive modularity at the simplest is one area of similarity. But within the scope of that is the Type 1/Type 2 distinction, or “fast” versus “slow” thinking. In this “dual process” framework decision-making may be guided by intuitive Type 1 thinking that relates to more primitive, older evolutionary modules of the mind. Type 1 evolved to help solve survival dilemmas that require quick resolution. But inferential reasoning developed more slowly and apparently fairly late for us, with the impact of modern education strengthening the ability of these Type 2 decision processes to override the intuitive Type 1 decisions.

These insights have been applied in remarkably interesting ways in trying to understand political ideologies, moral choices, and even religious identity. For instance, there is some evidence that conservative political leanings correlates more with Type 1 processes.… Read the rest

One Shot, Few Shot, Radical Shot

Mark Davis1 Comment

Exunoplura is back up after a sad excursion through the challenges of hosting providers. To be blunt, they mostly suck. Between systems that just don’t work right (SSL certificate provisioning in this case) and bad to counterproductive support experiences, it’s enough to make one want to host it oneself. But hosting is mostly, as they say of war, long boring periods punctuated by moments of terror as things go frustratingly sideways. But we are back up again after two hosting provider side-trips!

Honestly, I’d like to see an AI agent effectively navigate through these technological challenges. Where even human performance is fleeting and imperfect, the notion that an AI could learn how to deal with the uncertain corners of the process strikes me as currently unthinkable. But there are some interesting recent developments worth noting and discussing in the journey towards what is named “general AI” or a framework that is as flexible as people can be, rather than narrowly tied to a specific task like visually inspecting welds or answering a few questions about weather, music, and so forth.

First, there is the work by the OpenAI folks on massive language models being tested against one-shot or few-shot learning problems. In each of these learning problems, the number of presentations of the training data cases is limited, rather than presenting huge numbers of exemplars and “fine tuning” the response of the model. What is a language model? Well, it varies across different approaches, but typically is a weighted context of words of varying length, with the weights reflecting the probabilities of those words in those contexts over a massive collection of text corpora. For the OpenAI model, GPT-3, the total number of parameters (words/contexts and their counts) is an astonishing 175 billion using 45 Tb of text to train the model.… Read the rest

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