Tag Archives: artificial intelligence

Ideas of Stuart Kauffman

If you are familiar with complex systems theorist Dr. Stuart Kauffman’s ideas you know he covers a broad range of disciplines and concepts, many in considerable depth, and with a keen eye for isomorphic and integrative principles. If you peruse some of his writings and other communications, please share with us how you see Kauffman’s ideas informing our focal interests: brain, mind, intelligence (organic and inorganic), and self-aware consciousness.

Do you find Kauffman’s ideas well supported by empirical research? Which are more scientific and which, if any, more philosophical? What intrigues, provokes, or inspires you? Do any of his perspectives or claims help you better orient or understand your own interests in our focal topics?

Following are a few reference links to get the conversation going. Please add your own in the comments to this post. If you are a member and have a lot to say on a related topic, please create a new post, tag it with ‘Stuart Kauffman,’ and create a link to your post in the comments to this post.

Book: Team Human by Douglas Rushkoff

Team Human by Douglas Rushkoff investigates the impacts of current and emerging technologies and digital culture on individuals and groups and seeks ways to evade or extract ourselves from their corrosive effects.

After you read the book, please post your thoughts as comments to this post or, if you prefer, as new posts. There are interviews and other resources about the book online. Feel free to recommend in the comments those you find meaningful. Also, the audiobook is available through the Albuquerque Public Library but may have a long wait queue (I’m aiming for a record number of ‘q’s in this sentence).

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The info processing (IP) metaphor of the brain is wrong

Psychologist Robert Epstein, the former editor of Psychology Today, challenges anyone to show the brain processing information or data. The IP metaphor, he says, is so deeply embedded in thinking about thinking it prevents us from learning how the brain really works. Epstein also takes on popular luminaries including Ray Kurzweil and Henry Markram, seeing both exemplifying the extremes of wrongness we get into with the IP metaphor and the notion mental experience could persist outside the organic body.

The Empty Brain (Aeon article with audio)

Applying artificial intelligence for social good

This McKinsey article is an excellent overview of this more extensive article (3 MB PDF) enumerating the ways in which varieties of deep learning can improve existence. Worth a look.

The articles cover the following:

  • Mapping AI use cases to domains of social good
  • AI capabilities that can be used for social good
  • Overcoming bottlenecks, especially around data and talent
  • Risks to be managed
  • Scaling up the use of AI for social good

Musk: merging of humans and technology essential to survival

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From Axios interview with Elon Musk:

Musk said his neuroscience company, Neuralink, has about 85 of “the highest per capita intelligence” group of engineers he has ever assembled — with the mission of building a hard drive for your brain.

  • “The long-term aspiration with Neuralink would be to achieve a symbiosis with artificial intelligence.”
  • Wait. What? “To achieve a sort of democratization of intelligence, such that it is not monopolistically held in a purely digital form by governments and large corporations.”

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Informative neuroscience presentations at NYU Center for Mind, Brain & Consciousness

The NYU Center for Mind, Brain & Consciousness hosts presentations, including topical debates among leading neuroscience researchers. Many of the sessions are recorded for later viewing. The upcoming debate among Joseph LeDoux (Center for Neural Science, NYU), Yaïr Pinto (Psychology, University of Amsterdam), and Elizabeth Schechter (Philosophy, Washington University in St. Louis), will tackle the question, “Do Split-brain patients have two minds?” Previous topics addressed animal consciousness, hierarchical predictive coding and perception, AI ‘machinery,’ AI ethics, unconscious perception, research replication issues, neuroscience and art, explanatory power of mirror neurons, child vs adult learning, and brain-mapping initiatives.

Can we understand other minds? Novels and stories say: no

by Kanta Dihal

This article was originally published at Aeon and has been republished under Creative Commons.

Cassandra woke up to the rays of the sun streaming through the slats on her blinds, cascading over her naked chest. She stretched, her breasts lifting with her arms as she greeted the sun. She rolled out of bed and put on a shirt, her nipples prominently showing through the thin fabric. She breasted boobily to the stairs, and titted downwards.

This particular hyperbolic gem has been doing the rounds on Tumblr for a while. It resurfaced in April 2018, in response to a viral Twitter challenge posed by the US podcaster Whitney Reynolds: women, describe yourself the way a male writer would.

The dare hit a sweet spot. Many could summon up passages from books containing terrible, sexualised descriptions of women. Some of us recalled Haruki Murakami, whose every novel can be summarised as: ‘Protagonist is an ordinary man, except lots of really beautiful women want to sleep with him.’ Others remembered J M Coetzee, and his variations on the plot: ‘Tenured male professor in English literature sleeps with beautiful female undergraduate.’ It was a way for us to joke about the fact that so much great literature was written by men who could express perfectly detailed visual descriptions of the female body, and yet possessed such an impoverished understanding of the female mind.

This is why the philosophical project of trying to map the contours of other minds needs a reality check. If other humans are beyond our comprehension, what hope is there for understanding the experience of animals, artificial intelligence or aliens?

I am a literature scholar. Over thousands of years of literary history, authors have tried and failed to convey an understanding of Others (with a capital ‘O’). Writing fiction is an exercise that stretches an author’s imagination to its limits. And fiction shows us, again and again, that our capacity to imagine other minds is extremely limited.

It took feminism and postcolonialism to point out that writers were systematically misrepresenting characters who weren’t like them. Male authors, it seems, still struggle to present convincing female characters a lot of the time. The same problem surfaces again when writers try to introduce a figure with a different ethnicity to their own, and fail spectacularly.

I mean, ‘coffee-coloured skin’? Do I really need to find out how much milk you take in the morning to know the ethnicity you have in mind? Writers who keep banging on with food metaphors to describe darker pigmentation show that they don’t appreciate what it’s like to inhabit such skin, nor to have such metaphors applied to it.

Conversely, we recently learnt that some publishers rejected the Korean-American author Leonard Chang’s novel The Lockpicker (2017) – for failing to cater to white readers’ lack of understanding of Korean-Americans. Chang gave ‘none of the details that separate Koreans and Korean-Americans from the rest of us’, one publisher’s letter said. ‘For example, in the scene when she looks into the mirror, you don’t show how she sees her slanted eyes …’ Any failure to understand a nonwhite character, it seems, was the fault of the nonwhite author.

Fiction shows us that nonhuman minds are equally beyond our grasp. Science fiction provides a massive range of the most fanciful depictions of interstellar space travel and communication – but anthropomorphism is rife. Extraterrestrial intelligent life is imagined as Little Green Men (or Little Yellow or Red Men when the author wants to make a particularly crude point about 20th-century geopolitics). Thus alien minds have been subject to the same projections and assumptions that authors have applied to human characters, when they fundamentally differ from the authors themselves.

For instance, let’s look at a meeting of human minds and alien minds. The Chinese science fiction author Liu Cixin is best known for his trilogy starting with The Three-Body Problem (2008). It appeared in English in 2014 and, in that edition, each book has footnotes – because there are some concepts that are simply not translatable from Chinese into English, and English readers need these footnotes to understand what motivates the characters. But there are also aliens in this trilogy. From a different solar system. Yet their motivations don’t need footnoting in translation.

Splendid as the trilogy is, I find that very curious. There is a linguistic-cultural barrier that prevents an understanding of the novel itself, on this planet. Imagine how many footnotes we’d need to really grapple with the motivations of extraterrestrial minds.

Our imaginings of artificial intelligence are similarly dominated by anthropomorphic fantasies. The most common depiction of AI conflates it with robots. AIs are metal men. And it doesn’t matter whether the press is reporting on swarm robots invented in Bristol or a report produced by the House of Lords: the press shall plaster their coverage with Terminator imagery. Unless the men imagining these intelligent robots want to have sex with them, in which case they’re metal women with boobily breasting metal cleavage – a trend spanning the filmic arts from Fritz Lang’s Metropolis (1927) to the contemporary TV series Westworld (2016-). The way that we imagine nonhumans in fiction reflects how little we, as humans, really get each other.

All this supports the idea that embodiment is central to the way we understand one another. The ridiculous situations in which authors miss the mark stem from the difference between the author’s own body and that of the character. It’s hard to imagine what it’s like to be someone else if we can’t feel it. So, much as I enjoyed seeing a woman in high heels outrun a T-Rex in Jurassic World (2015), I knew that the person who came up with that scene clearly has no conception of what it’s like to inhabit a female body, be it human or Tyrannosaurus.

Because stories can teach compassion and empathy, some people argue that we should let AIs read fiction in order to help them understand humans. But I disagree with the idea that compassion and empathy are based on a deep insight into other minds. Sure, some fiction attempts to get us to understand one another. But we don’t need any more than a glimpse of what it’s like to be someone else in order to empathise with them – and, hopefully, to not want to kill and destroy them.

As the US philosopher Thomas Nagel claimed in 1974, a human can’t know what it is like to be a bat, because they are fundamentally alien creatures: their sensory apparatus and their movements are utterly different from ours. But we can imagine ‘segments’, as Nagel wrote. This means that, despite our lack of understanding of bat minds, we can find ways to keep a bat from harm, or even nurse and raise an orphaned baby bat, as cute videos on the internet will show you.

The problem is that sometimes we don’t realise this segment of just a glimpse of something bigger. We don’t realise until a woman, a person of colour, or a dinosaur finds a way to point out the limits of our imagination, and the limits of our understanding. As long as other human minds are beyond our understanding, nonhuman ones certainly are, too.Aeon counter – do not remove

Kanta Dihal is a postdoctoral research assistant and the research project coordinator of the Leverhulme Centre for the Future of Intelligence at the University of Cambridge.

This article was originally published at Aeon and has been republished under Creative Commons.

The Singularity is Near: When Humans Transcend Biology

Kurzweil builds and supports a persuasive vision of the emergence of a human-level engineered intelligence in the early-to-mid twenty-first century. In his own words,

With the reverse engineering of the human brain we will be able to apply the parallel, self-organizing, chaotic algorithms of  human intelligence to enormously powerful computational substrates. This intelligence will then be in a position to improve its own design, both hardware and software,  in a rapidly accelerating iterative process.

In Kurzweil's view, we must and will ensure we evade obsolescence by integrating emerging metabolic and cognitive technologies into our bodies and brains. Through self-augmentation with neurotechnological prostheses, the locus of human cognition and identity will gradually (but faster than we'll expect, due to exponential technological advancements) shift from the evolved substrate (the organic body) to the engineered substrate, ultimately freeing the human mind to develop along technology's exponential curve rather than evolution's much flatter trajectory.

The book is extensively noted and indexed, making the deep-diving reader's work a bit easier.

If you have read it, feel free to post your observations in the comments below. (We've had a problem with the comments section not appearing. It may require more troubleshooting.)

Review and partial rebuttal of Bostrom’s ‘Superintelligence’

This article from the Bulletin of The Atomic Scientists site is an interesting overview of Nick Bostrom’s Superintelligence: Paths, Dangers, Strategies. The author rebuts Bostrom on several points, relying partly on the failure of AI research to date to produce any result approaching what most humans would regard as intelligence. The absence of recognizably intelligent artificial general intelligence is not, of course, a proof it can never exist. The author also takes issue with Bostrom’s (claimed) conflation of intelligence with inference abilities—an assumption the author says AI researchers found to be false.

70-year-old Hebbs synaptic learning theory wrong

Neural learning occurs at dendrite roots, not in synapses.

The newly suggested learning scenario indicates that learning occurs in a few dendrites that are in much closer proximity to the neuron, as opposed to the previous notion. …

The new learning scenario occurs in different sites of the brain and therefore calls for a reevaluation of current treatments for disordered brain functionality. … In addition, the learning mechanism is at the basis of recent advanced machine learning and deep learning achievements. The change in the learning paradigm opens new horizons for different types of deep learning algorithms and artificial intelligence based applications imitating our brain functions, but with advanced features and at a much faster speed.

Source: https://www.sciencedaily.com/releases/2018/03/180323084818.htm