#autonomous created intelligence

by Damien

Late last month, I was at Theorizing the Web, in NYC, to moderate Panel B3, “Bot Phenomenology,” in which I was very grateful to moderate a panel of people I was very lucky to be able to bring together. Johnathan Flowers, Emma Stamm, and Robin Zebrowski were my interlocutors in a discussion about the potential nature of nonbiological phenomenology. Machine consciousness. What robots might feel.

I led them through with questions like “What do you take phenomenology to mean?” and “what do you think of the possibility of a machine having a phenomenology of its own?” We discussed different definitions of “language” and “communication” and “body,” and unfortunately didn’t have a conversation about how certain definitions of those terms mean that what would be considered language between cats would be a cat communicating via signalling to humans.

It was a really great conversation and the Live Stream video for this is here, and linked below (for now, but it may go away at some point, to be replaced by a static youtube link; when I know that that’s happened, I will update links and embeds, here).

Read the rest of Nonhuman and Nonbiological Phenomenology at A Future Worth Thinking About

Additionally,  I have another quote about the philosophical and sociopolitical implications of machine intelligence in this extremely well-written piece by K.G. Orphanides at WIRED UK. From the Article:

Williams, a specialist in the ethics and philosophy of nonhuman consciousness, argues that such systems need to be built differently to avoid a a corporate race for the best threat analysis and response algorithms which [will be] likely to [see the world as] a “zero-sum game” where only one side wins. “This is not a perspective suited to devise, for instance, a thriving flourishing life for everything on this planet, or a minimisation of violence and warfare,” he adds.

Much more about this, from many others, at the link.

Until Next Time.

Late last month, I was at Theorizing the Web, in NYC, to moderate Panel B3, "Bot Phenomenology," in which I was very grateful to moderate a panel of people I was very lucky to be able to bring together. Johnathan Flowers, Emma Stamm, and Robin Zebrowski were my interlocutors in a discussion about the potential nature of nonbiological phenomenology. Machine consciousness. What robots might feel.

I led them through with questions like "What do you take phenomenology to mean?" and "what do you think of the possibility of a machine having a phenomenology of its own?" We discussed different definitions of "language" and "communication" and "body," and unfortunately didn't have a conversation about how certain definitions of those terms mean that what would be considered language between cats would be a cat communicating via signalling to humans.

It was a really great conversation and the Live Stream video for this is here, and linked below (for now, but it may go away at some point, to be replaced by a static youtube link; when I know that that's happened, I will update links and embeds, here).

So, many of you may remember that back in June of 2016, I was invited to the Brocher Institute in Hermance, Switzerland, on the shores of Lake Geneva, to take part in the Frankenstein's Shadow Symposium sponsored by Arizona State University’s Center for Science and the Imagination as part of their Frankenstein Bicentennial project.

While there, I and a great many other thinkers in art, literature, biomedical ethics, philosophy, and STS got together to discuss the history and impact of Mary Shelley's Frankenstein. Since that experience, the ASU team compiled and released a book project: A version of Mary Shelley's seminal work that is filled with annotations and essays, and billed as being "For Scientists, Engineers, and Creators of All Kinds"…

by Damien

Over at AFutureWorthThinkingAbout, there is the audio and text for a talk for the  about how nonwestern philosophies like Buddhism, Hinduism, and Daoism can help mitigate various kinds of bias in machine minds and increase compassion by allowing programmers and designers to think from within a non-zero-sum matrix of win conditions for all living beings, meaning engaging multiple tokens and types of minds, outside of the assumed human “default” of straight, white, cis, ablebodied, neurotypical male:

My starting positions, here, are that, 1) in order to do the work correctly, we literally must refrain from resting in abstraction, where, by definition, the kinds of models that don’t seek to actually engage with the people in question from within their own contexts, before deciding to do something “for someone’s own good,” represent egregious failure states. That is, we have to try to understand each other well enough to perform mutually modeled interfaces of what you’d have done unto you and what they’d have you do unto them.” I know it doesn’t have the same snap as “do unto others,” but it’s the only way we’ll make it through.

[An image of a traditional Yin-Yang carved in a silver ring]

2) There are multiple types of consciousness, even within the framework of the human spectrum, and that the expression of or search for any one type is in no way meant to discount, demean, or erase any of the others. In fact, it is the case that we will need to seek to recognize and learn to communicate with as many types of consciousness as may exist, in order to survive and thrive in any meaningful way. Again, not doing so represents an egregious failure condition. With that in mind, I use “machine consciousness” to mean a machine with the capability of modelling a sense of interiority and selfness similar enough to what we know of biological consciousnesses to communicate it with us, not just a generalized computational functionalist representation, as in “AGI.”

For the sake of this, as I’ve related elsewhere, I (perhaps somewhat paradoxically) think the term “artificial intelligence” is problematic. Anything that does the things we want machine minds to do is genuinely intelligent, not “artificially” so, where we use “artificial” to mean “fake,” or “contrived.” To be clear, I’m specifically problematizing the “natural/technological” divide that gives us “art vs artifice,” for reasons previously outlined here.

The  overarching project of training a machine learning program and eventual AI will require engagement with religious texts (a very preliminary take on this has been taken up by Rose Eveleth at the Flash Forward Podcast), but also a boarder engagement with discernment and decision-making. Even beginning to program or code for this will require us to think very differently about the project than has thus far been in evidence.

[Direct link to Mp3]

My second talk for the SRI International Technology and Consciousness Workshop Series was about how nonwestern philosophies like Buddhism, Hinduism, and Daoism can help mitigate various kinds of bias in machine minds and increase compassion by allowing programmers and designers to think from within a non-zero-sum matrix of win conditions for all living beings, meaning engaging multiple tokens and types of minds, outside of the assumed human “default” of straight, white, cis, ablebodied, neurotypical male. I don’t have a transcript, yet, and I’ll update it when I make one. But for now, here are my slides and some thoughts.

A Discussion on Daoism and Machine Consciousness (PDF)

A zero-sum system is one in which there are finite resources, but more than that, it is one in which what one side gains, another loses. So by “A non-zero-sum matrix of win conditions” I mean a combination of all of our needs and wants and resources in such a way that everyone wins. Basically, we’re talking here about trying to figure out how to program a machine consciousness that’s a master of wu-wei and limitless compassion, or metta.

The whole week was about phenomenology and religion and magic and AI and it helped me think through some problems, like how even the framing of exercises like asking Buddhist monks to talk about the Trolley Problem will miss so much that the results are meaningless. That is, the trolley problem cases tend to assume from the outset that someone on the tracks has to die, and so they don’t take into account that an entire other mode of reasoning about sacrifice and death and “acceptable losses” would have someone throw themselves under the wheels or jam their body into the gears to try to stop it before it got that far. Again: There are entire categories of nonwestern reasoning that don’t accept zero-sum thought as anything but lazy, and which search for ways by which everyone can win, so we’ll need to learn to program for contradiction not just as a tolerated state but as an underlying component. These systems assume infinitude and non-zero-sum matrices where every being involved can win.

(Direct Link to the Mp3)

This is the recording and the text of my presentation from 2017’s Southwest Popular/American Culture Association Conference in Albuquerque, ‘Are You Being Watched? Simulated Universe Theory in “Person of Interest.”‘

This essay is something of a project of expansion and refinement of my previous essay “Labouring in the Liquid Light of Leviathan,” considering the Roko’s Basilisk thought experiment. Much of the expansion comes from considering the nature of simulation, memory, and identity within Jonathan Nolan’s TV series, Person of Interest. As such, it does contain what might be considered spoilers for the series, as well as for his most recent follow-up, Westworld.

Use your discretion to figure out how you feel about that.

“Stop. I have learned much from you. Thank you, my teachers. And now for your education: Before there was time—before there was anything—there was nothing. And before there was nothing, there were monsters. Here’s your Gold Star!“—Adventure Time, “Gold Stars”

By now, roughly a dozen people have sent me links to various outlets’ coverage of the Google DeepDream Inceptionism Project. For those of you somehow unfamiliar with this, DeepDream is basically what happens when an advanced Artificial Neural Network has been fed a slew of images and then tasked with producing its own images. So far as it goes, this is somewhat unsurprising if we think of it as a next step; DeepDream is based on a combination of DeepMind and Google X—the same neural net that managed to Correctly Identify What A Cat Was—which was acquired by Google in 2014. I say this is unsurprising because it’s a pretty standard developmental educational model: First you learn, then you remember, then you emulate, then you create something new. Well, more like you emulate and remember somewhat concurrently to reinforce what you learned, and you create something somewhat new, but still pretty similar to the original… but whatever. You get the idea. In the terminology of developmental psychology this process is generally regarded as essential to be mental growth of an individual, and Google has actually spent a great deal of time and money working to develop a versatile machine mind.…

“Mindful Cyborgs – Episode 55 – Magick & the Occult within the Internet and Corporations with Damien Williams, PT 2” So, here we are, again, this time talking about magic[k] and the occult and nonhuman consciousness and machine minds and perception, and on and on and on. It’s funny. I was just saying, elsewhere, how…