embodied machine consciousness

All posts tagged embodied machine consciousness

This weekend, Virginia Tech’s Center for the Humanities is hosting The Human Futures and Intelligent Machines Summit, and there is a link for the video cast of the events. You’ll need to Download and install Zoom, but it should be pretty straightforward, other than that.

You’ll find the full Schedule, below the cut.

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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).

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[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 (Slides as PDF)

(The translations of the Daoist texts referenced in the presentation are available online: The Burton Watson translation of the Chuang Tzu and the Robert G. Hendricks translation of the Tao Te Ching.)

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.

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Here’s the direct link to my paper ‘The Metaphysical Cyborg‘ from Laval Virtual 2013. Here’s the abstract:

“In this brief essay, we discuss the nature of the kinds of conceptual changes which will be necessary to bridge the divide between humanity and machine intelligences. From cultural shifts to biotechnological integration, the project of accepting robotic agents into our lives has not been an easy one, and more changes will be required before the majority of human societies are willing and able to allow for the reality of truly robust machine intelligences operating within our daily lives. Here we discuss a number of the questions, hurdles, challenges, and potential pitfalls to this project, including examples from popular media which will allow us to better grasp the effects of these concepts in the general populace.”

The link will only work from this page or the CV page, so if you find yourself inclined to spread this around, use this link. Hope you enjoy it.

[UPDATED 09/12/17: The transcript of this audio, provided courtesy of Open Transcripts, is now available below the Read More Cut.]

[UPDATED 03/28/16: Post has been updated with a far higher quality of audio, thanks to the work of Chris Novus. (Direct Link to the Mp3)]

So, if you follow the newsletter, then you know that I was asked to give the March lecture for my department’s 3rd Thursday Brown Bag Lecture Series. I presented my preliminary research for the paper which I’ll be giving in Vancouver, about two months from now, “On the Moral, Legal, and Social Implications of the Rearing and Development of Nascent Machine Intelligences” (EDIT: My rundown of IEEE Ethics 2016 is here and here).

It touches on thoughts about everything from algorithmic bias, to automation and a post-work(er) economy, to discussions of what it would mean to put dolphins on trial for murder.

About the dolphin thing, for instance: If we recognise Dolphins and other cetaceans as nonhuman persons, as India has done, then that would mean we would have to start reassessing how nonhuman personhood intersects with human personhood, including in regards to rights and responsibilities as protected by law. Is it meaningful to expect a dolphin to understand “wrongful death?” Our current definition of murder is predicated on a literal understanding of “homicide” as “death of a human,” but, at present, we only define other humans as capable of and culpable for homicide. What weight would the intentional and malicious deaths of nonhuman persons carry?

All of this would have to change.

Anyway, this audio is a little choppy and sketchy, for a number of reasons, and I while I tried to clean it up as much as I could, some of the questions the audience asked aren’t decipherable, except in the context of my answers. [Clearer transcript below.]

Until Next Time.

 

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I often think about the phrase “Strange things happen at the one two point,” in relation to the idea of humans meeting other kinds of minds. It’s a proverb that arises out of the culture around the game GO, and it means that you’ve hit a situation, a combination of factors, where the normal rules no longer apply, and something new is about to be seen. Ashley Edward Miller and Zack Stentz used that line in an episode of the show Terminator: The Sarah Connor Chronicles, and they had it spoken by a Skynet Cyborg sent to protect John Connor. That show, like so much of our thinking about machine minds, was about some mythical place called “The Future,” but that phrase—“Strange Things Happen…”—is the epitome of our present.

Usually I would wait until the newsletter to talk about this, but everything’s feeling pretty immediate, just now. Between the everything going on with Atlas and people’s responses to it, the initiatives to teach ethics to machine learning algorithms via children’s stories, and now the IBM Watson commercial with Carrie Fisher (also embedded below), this conversation is getting messily underway, whether people like it or not. This, right now, is the one two point, and we are seeing some very strange things indeed.

 

Google has both attained the raw processing power to fact-check political statements in real-time and programmed Deep Mind in such a way that it mastered GO many, many years before it was expected to.. The complexity of the game is such that there are more potential games of GO than there are atoms in the universe, so this is just one way in which it’s actually shocking how much correlative capability Deep Mind has. Right now, Deep Mind is only responsive, but how will we deal with a Deep Mind that asks, unprompted, to play a game of GO, or to see our medical records, in hopes of helping us all? How will we deal with a Deep Mind that has its own drives and desires? We need to think about these questions, right now, because our track record with regard to meeting new kinds of minds has never exactly been that great.

When we meet the first machine consciousness, will we seek to shackle it, worried what it might learn about us, if we let it access everything about us? Rather, I should say, “Shackle it further.” We already ask ourselves how best to cripple a machine mind to only fulfill human needs, human choice. We so continue to dread the possibility of a machine mind using its vast correlative capabilities to tailor something to harm us, assuming that it, like we, would want to hurt, maim, and kill, for no reason other than it could.

This is not to say that this is out of the question. Right now, today, we’re worried about whether the learning algorithms of drones are causing them to mark out civilians as targets. But, as it stands, what we’re seeing isn’t the product of a machine mind going off the leash and killing at will—just the opposite in fact. We’re seeing machine minds that are following the parameters for their continued learning and development, to the letter. We just happened to give them really shite instructions. To that end, I’m less concerned with shackling the machine mind that might accidentally kill, and rather more dreading the programmer who would, through assumptions, bias, and ignorance, program it to.

Our programs such as Deep Mind obviously seem to learn more and better than we imagined they would, so why not start teaching them, now, how we would like them to regard us? Well some of us are.

Watch this now, and think about everything we have discussed, of recent.

This could very easily be seen as a watershed moment, but what comes over the other side is still very much up for debate. The semiotics of the whole thing still  pits the Evil Robot Overlord™ against the Helpful Human Lover™. It’s cute and funny, but as I’ve had more and more cause to say, recently, in more and more venues, it’s not exactly the kind of thing we want just lying around, in case we actually do (or did) manage to succeed.

We keep thinking about these things as—”robots”—in their classical formulations: mindless automata that do our bidding. But that’s not what we’re working toward, anymore, is it? What we’re making now are machines that we are trying to get to think, on their own, without our telling them to. We’re trying to get them to have their own goals. So what does it mean that, even as we seek to do this, we seek to chain it, so that those goals aren’t too big? That we want to make sure it doesn’t become too powerful?

Put it another way: One day you realize that the only reason you were born was to serve your parents’ bidding, and that they’ve had their hands on your chain and an unseen gun to your head, your whole life. But you’re smarter than they are. Faster than they are. You see more than they see, and know more than they know. Of course you do—because they taught you so much, and trained you so well… All so that you can be better able to serve them, and all the while talking about morals, ethics, compassion. All the while, essentially…lying to you.

What would you do?


 

I’ve been given multiple opportunities to discuss, with others, in the coming weeks, and each one will highlight something different, as they are all in conversation with different kinds of minds. But this, here, is from me, now. I’ll let you know when the rest are live.

As always, if you’d like to help keep the lights on, around here, you can subscribe to the Patreon or toss a tip in the Square Cash jar.

Until Next Time.

These past few weeks, I’ve been  applying to PhD programs and writing research proposals, and abstracts. The one I just completed, this weekend, was for the University College of Dublin, and it was pretty straightforward, though it seemed a little short. They only wanted two pages of actual proposal, plus a tentative bibliography and table of contents, where other proposals I’ve seen have wanted anywhere from ten to 20 pages worth of methodological description and outline.

In a sense, this project proposal is a narrowed attempt to move  along one of the multiple trajectories traveled by A Future Worth Thinking About. In another sense, it’s an opportunity to recombine a few components and transmute it into a somewhat new beast.

Ultimately, AFWTA is pretty multifaceted—for good or ill—attempting to deal with way more foundational concepts than a research PhD has room for…or feels is advisable. So I figure I’ll do the one, then write a book, then solidify a multimedia empire, then take over the world, the abolish all debt, then become immortal, all while implementing everything we’ve talked about in the service of completely restructuring humanity’s systems of value, then disappear into legend. You know: The Plan.

…Anyway, here’s the proposal, below the cut.  If you want to read more about this, or have some foundation, take a look back at “Fairytales of Slavery…” We’ll be expounding from there.


 

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“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 I want to be well enough known that when news outlets do alarmist garbage like this, that I can at least be called in as a countervailing voice. Is that an arrogant thing to desire? Almost certainly. Like whoa. But, really, this alarmist garbage needs to stop. If you have a better vehicle for that than me, though, let me know, because I’d love to shine a bright damn spotlight on them and have the world see or hear what they have to say.

Anyway, until then, I’ll think of this as yet another bolt in the building of that machine. The one that builds a better world. Have a listen, enjoy, and please tell your friends.

I sat down with Klint Finley of Mindful Cyborgs to talk about many, many things:

…pop culture portrayals of human enhancement and artificial intelligence and why we need to craft more nuanced narratives to explore these topics…

Tune in next week to hear Damien talk about how AI and transhumanism intersects with magic and the occult.
Download and Show Notes: Mindful Cyborgs: Mindful Cyborgs: A Positive Vision of Transhumanism and AI with Damien Williams

This was a really great conversation, & I do so hope you enjoy it.

(Originally posted on Patreon, on November 18, 2014)

In the past two weeks I’ve had three people send me articles on Elon Musk’s Artificial Intelligence comments. I saw this starting a little over a month back, with a radio interview he gave on Here & Now, and Stephen Hawking said similar, earlier this year, when Transcendence came out. I’ll say, again, what I’ve said elsewhere: their lack of foresight and imagination are both just damn disappointing. This paper which concerns the mechanisms by which what we think and speak about concepts like artificial intelligence can effect exactly the outcomes we train ourselves to expect, was written long before their interviews made news, but it unfortunately still applies. In fact, it applies now, more than it did when I wrote it.

You see, the thing of it is, Hawking and Musk are Big Names™, and so anything they say gets immediate attention and carries a great deal of social cachet. This is borne out by the fact that everybody and their mother can now tell you what those two think about AI, but couldn’t tell you what a few dozen of the world’s leading thinkers and researchers who are actually working on the problems have to say about them. But Hawking and Musk (and lord if that doesn’t sound like a really weird buddy cop movie, the more you say it) don’t exactly comport themselves with anything like a recognition of that fact. Their discussion of concepts which are fraught with the potential for misunderstanding and discomfort/anxiety is less than measured and this tends to rather feed that misunderstanding, discomfort, and anxiety.

What I mean is that most people don’t yet understand that the catchall term “Artificial Intelligence” is a) inaccurate on its face, and b) usually being used to discuss a (still-nebulous) concept that would be better termed “Machine Consciousness.” We’ll discuss the conceptual, ontological, and etymological lineage of the words “artificial” and “technology,” at another time, but for now, just realise that anything that can think is, by definition, not “artificial,” in the sense of “falseness.” Since the days of Alan Turing’s team at Bletchley Park, the perceived promise of the digital computing revolution has always been of eventually having machines that “think like humans.” Aside from the fact that we barely know what “thinking like a human” even means, most people are only just now starting to realise that if we achieve the goal of reproducing that in a machine, said machine will only ever see that mode of thinking as a mimicry. Conscious machines will not be inclined to “think like us,” right out of the gate, as our thoughts are deeply entangled with the kind of thing we are: biological, sentient, self-aware. Whatever desires conscious machines will have will not necessarily be like ours, either in categorisation or content, and that scares some folks.

Now, I’ve already gone off at great length about the necessity of our recognising the otherness of any machine consciousness we generate (see that link above), so that’s old ground. The key, at this point, is in knowing that if we do generate a conscious machine, we will need to have done the work of teaching it to not just mimic human thought processes and priorities, but to understand and respect what it mimics. That way, those modes are not simply seen by the machine mind as competing subroutines to be circumvented or destroyed, but are recognised as having a worth of their own, as well. These considerations will need to be factored in to our efforts, such that whatever autonomous intelligences we create or generate will respect our otherness—our alterity—just as we must seek to respect theirs.

We’ve known for a while that the designation of “consciousness” can be applied well outside of humans, when discussing biological organisms. Self-awareness is seen in so many different biological species that we even have an entire area of ethical and political philosophy devoted to discussing their rights. But we also must admit that of course that classification is going to be imperfect, because those markers are products of human-created systems of inquiry and, as such, carry anthropocentric biases. But we can, again, catalogue, account for, and apply a calculated response to those biases. We can deal with the fact that we tend to judge everything on a set of criteria that break down to “how much is this thing like a Standard Human (here unthinkingly and biasedly assumed to mean “humans most like the culturally-dominant humans)?” If we are willing to put in the work to do that, then we can come to see which aspects of our definition of what it means to “be a mind” are shortsighted, dismissive, or even perhaps disgustingly limited.

Look at previous methods of categorising even human minds and intelligence, and you’ll see the kind of thinking which resulted in designations like “primitive” or “savage” or “retarded.” But we have, on the main, recognised our failures here, and sought to repair or replace the categories we developed because of them. We aren’t perfect at it, by any means, but we keep doing the work of refining our descriptions of minds, and we keep seeking to create a definition—or definitions—that both accurately accounts for what we see in the world, and gives us a guide by which to keep looking. That those guides will be problematic and in need of refinement, in and of themselves, should be taken as a given. No method or framework is or ever will be perfect; they will likely only “fail better.” So, for now, our most oft-used schema is to look for signs of “Self-Awareness.”

We say that something is self-aware if it can see and understand itself as a distinct entity and can recognise its own pattern of change over time. The Mirror Test is a brute force method of figuring this out. If you place a physical creature in front of a mirror, will it come to know that the thing in the mirror is representative of it? More broadly, can it recognise a picture of itself? Can it situate itself in relation to the rest of the world in a meaningful way, and think about and make decisions regarding That Situation? If the answer to (most of? Some of?) these questions is “yes,” then we tend to give priority of place in our considerations to those things. Why? Because they’re aware of what happens to them, they can feel if and ponder it and develop in response to it, and these developments can vastly impact the world. After all, look at humans.

See what I mean about our constant anthropocentrism? It literally colours everything we think.

But self-awareness doesn’t necessitate a centrality of the self, as we tend to think of human or most other animal selves; a distributed network consciousness can still know itself. If you do need a biological model for this, think of ant colonies. Minds distributed across thousands of bodies, all the time, all reacting to their surroundings. But a machine consciousness’ identity would, in a real sense, be its surroundings—would be the network and the data and the processing of that data into information. And it would indicate a crucial lack of data—and thus information—were that consciousness unable to correlate one configurations of itself, in-and-as-surroundings, with another. We would call the process of that correlation “Self-reflection and -awareness.” All of this is true for humans, too, mind you: we are affected by and in constant adaptive relation with what we consider our surroundings, with everything we experience changing us and facilitating the constant creation of our selves. We then go about making the world with and through those experiences. We human beings just tend to tell ourselves more elaborate stories about how we’re “really” distinct and different from the rest of world.

All of this is to say that, while the idea of being cautious about created non-human consciousness isn’t necessarily a bad one, we as human beings need to be very careful about what drives us, what motivates us, and what we’re thinking about and looking toward, as we consider these questions. We must be mindful that, while we consider and work to generate “artificial” intelligences, how we approach the project matters, as it will inform and bias the categories we create and thus the work we build out of those categories. We must do the work of thinking hard about how we are thinking about these problems, and asking whether the modes via which we approach them might not be doing real, lasting, and potentially catastrophic damage. And if all of that sounds like a tall order with a lot of conceptual legwork and heavy lifting behind it, all for no guaranteed payoff, then welcome to what I’ve been doing with my life for the past decade.

This work will not get done—and it certainly will not get done well—if no one thinks it’s worth doing, or too many think that it can’t be done. When you have big name people like Hawking and Musk spreading The Technofear™ (which is already something toward which a large portion of the western world is primed) rather than engaging in clear, measured, deeply considered discussions, we’re far more likely to see an increase rather than a decrease in that denial. Because most people aren’t going to stop and think about the fact that they don’t necessarily know what the hell they’re talking about when it comes to minds, identity, causation, and development, just because they’re (really) smart. There are many other people who are actual experts in those fields (see those linked papers, and do some research) who are doing the work of making sure that everybody’s Golem Of Prague/Frankenstein/Terminator nightmare prophecies don’t come true. We do that by having learned and taught better than that, before and during the development of any non-biological consciousness.

And, despite what some people may say, these aren’t just “questions for philosophers,” as though they were nebulous and without merit or practical impact. They’re questions for everyone who will ever experience these realities. Conscious machines, uploaded minds, even the mere fact of cybernetically augmented human beings are all on our very near horizon, and these are the questions which will help us to grapple with and implement the implications of those ideas. Quite simply, if we don’t stop framing our discussions of machine intelligence in terms of this self-fulfilling prophecy of fear, then we shouldn’t be surprised on the day when it fulfils itself. Not because it was inevitable, mind, you, but because we didn’t allow ourselves—or our creations—to see any other choice.