Category 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).

Please use the tag and/or category ‘Rushkoff’ in your new posts. Use any other tags or categories you want. To access categories and tags while composing a post, click ‘Document’ at the top of the options area on the right side of the editing page.

How to add a category to a post in WordPress sites using the Gutenberg editor

Any comments you add to this post should inherit the post’s categories and tags. Add any additional ones as you like.

Last, this site includes a book reviews app for registered site members. To use it, log in and select Review under the New menu.

Starting a new book review

Evolutionary robots – Future of embodied AI?

Photo by Jeremy Avery on Unsplash

An article in Nature Machine Intelligence reports on R&D efforts employing evolutionary approaches to getting robots that are better adapted to their environments.

We propose ‘multi-level evolution’, a bottom-up automatic process that designs robots across multiple levels and niches them to tasks and environmental conditions. Multi-level evolution concurrently explores constituent molecular and material building blocks, as well as their possible assemblies into specialized morphological and sensorimotor configurations. Multi-level evolution provides a route to fully harness a recent explosion in available candidate materials and ongoing advances in rapid manufacturing processes.

ai will never conquer humanity

From this piece located at the publications page of the International Computer Science Institute.   “Mathematical models help describe reality, but only by ignoring its inherent integrity.” Computers work on binary logic and the world is full of  ‘noise.’ Hence computers, and mathematical models for that matter, can only approximate reality by eliminating that noise.

“Can a bunch of bits represent reality exactly, in a way that can be controlled and predicted indefinitely? The answer is no, because nature is inherently chaotic, while a bunch of bits representing a program can never be so, by definition.”

Which leads us to ask: “Are our mathematical models just a desperate, failed attempt to de-noise an otherwise very confusing, extremely blurred reality?”

So yes, math and computers are quite useful as long as we keep the above in mind instead of assuming they reveal reality as it is. And as long as we also search for that noisy humanity in the spaces between binary logic, which will never be revealed by math or computers alone.

Rushkoff: Team Human

Mark suggested this book as a future group reading and discussion and I agree. Rushkoff provides a very brief summary of his new book on the topic in the TED talk below. It starts with tech billionaires main concern being: Where do I build my bunker at the end of the world? So what happened to the idyllic utopias we thought tech was working toward, a collaborative commons of humanity? The tech boom became all about betting on stocks and getting as much money as possible for me, myself and I while repressing what makes us human. The motto became: “Human beings are the problem and technology is the solution.” Rushkoff is not very kind to the transhumanist notion of AI replacing humanity either, a consequence of that motto. He advises that we embed human values into the tech so that it serves us rather than the reverse.

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)

Ruskoff: The anti-human religion of Silicon Valley

Underlying our tech vision is a gnostic belief system of leaving the body behind, as it is an inferior biological system thwarting our evolution. Hence all the goals of downloading our supposed consciousness into a machine. It’s an anti-human and anti-environment religion that has no concern for either, imagining that tech is our ultimate savior.

And ironic enough, it’s a belief system that teamed up with the US human potential movement at Esalen. What started as an embodied based human potential program, with practices geared at integrating our minds with our bodies and the environment, got sidetracked by this glorious evolution beyond all that messy material and biological stuff.

And then there’s the devil’s bargain of this religion with our social media, like Facebook and Google, who use tech merely as a means of manipulating us for their own capitalistic purposes. Apparently it has been accepted that there is no alternative to capitalism, since the latter also assumes that humanity is strictly utilitarian and self-interested, the latter also being just mere algorithmic computations determined by an equally algorithmic ‘natural’ selection. Since tech can do all that better then what’s all the fuss?

Lent responds to Harari

Lent makes many of the points we had in our discussion of Harari’s book Homo Deus. Lent said:

“Apparently unwittingly, Harari himself perpetuates unacknowledged fictions that he relies on as foundations for his own version of reality. Given his enormous sway as a public intellectual, Harari risks causing considerable harm by perpetuating these fictions. Like the traditional religious dogmas that he mocks, his own implicit stories wield great influence over the global power elite as long as they remain unacknowledged. I invite Harari to examine them here. By recognizing them as the myths they actually are, he could potentially transform his own ability to help shape humanity’s future.”

I will only list the bullet point fictions below. See the link for the details:

1. Nature is a machine.
2. There is no alternative.
3. Life is meaningless so it’s best to do nothing.
4. Humanity’s future is a spectator sport.

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