algorithmic systems

All posts tagged algorithmic systems

I talked with Hewlett Packard Enterprise’s Curt Hopkins, for their article “4 obstacles to ethical AI (and how to address them).” We spoke about the kinds of specific tools and techniques by which people who populate or manage artificial intelligence design teams can incorporate expertise from the humanities and social sciences. We also talked about compelling reasons why they should do this, other than the fact that they’re just, y’know, very good ideas.

From the Article:

To “bracket out” bias, Williams says, “I have to recognize how I create systems and code my understanding of the world.” That means making an effort early on to pay attention to the data entered. The more diverse the group, the less likely an AI system is to reinforce shared bias. Those issues go beyond gender and race; they also encompass what you studied, the economic group you come from, your religious background, all of your experiences.

That becomes another reason to diversify the technical staff, says Williams. This is not merely an ethical act. The business strategy may produce more profit because the end result may be a more effective AI. “The best system is the one that best reflects the wide range of lived experiences and knowledge in the world,” he says.

[Image of two blank, white, eyeless faces, partially overlapping each other.]

To be clear, this is an instance in which I tried to find capitalist reasons that would convince capitalist people to do the right thing. To that end, you should imagine that all of my sentences start with “Well if we’re going to continue to be stuck with global capitalism until we work to dismantle it…” Because they basically all did.

I get how folx might think that framing would be a bit of a buzzkill for a tech industry audience, but I do want to highlight and stress something: Many of the ethical problems we’re concerned with mitigating or ameliorating are direct products of the capitalist system in which we are making these choices and building these technologies.

All of that being said, I’m not the only person there with something interesting to say, and you should go check out the rest of my and other people’s comments.

Until Next Time.

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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My piece “Cultivating Technomoral Interrelations,” a review of Technology and the Virtues: A Philosophical Guide to a Future Worth Wanting has been up over at the Social Epistemology Research and Reply Collective for a few months, now, so I figured I should post something about it, here.

As you’ll read, I was extremely taken with Vallor’s book, and think it is a part of some very important work being done. From the piece:

Additionally, her crucial point seems to be that through intentional cultivation of the self and our society, or that through our personally grappling with these tasks, we can move the world, a stance which leaves out, for instance, notions of potential socioeconomic or political resistance to these moves. There are those with a vested interest in not having a more mindful and intentional technomoral ethos, because that would undercut how they make their money. However, it may be that this is Vallor’s intent.

The audience and goal for this book seems to be ethicists who will be persuaded to become philosophers of technology, who will then take up this book’s understandings and go speak to policy makers and entrepreneurs, who will then make changes in how they deal with the public. If this is the case, then there will already be a shared conceptual background between Vallor and many of the other scholars whom she intends to make help her to do the hard work of changing how people think about their values. But those philosophers will need a great deal more power, oversight authority, and influence to effectively advocate for and implement what Vallor suggests, here, and we’ll need sociopolitical mechanisms for making those valuative changes, as well.

[Image of the front cover of Shannon Vallor’s TECHNOLOGY AND THE VIRTUES. Circuit pathways in the shapes of trees.]

This is, as I said, one part of a larger, crucial project of bringing philosophy, the humanities, and social sciences into wide public conversation with technoscientific fields and developers. While there have always been others doing this work, it is increasingly the case that these folks are being both heeded and given institutional power and oversight authority.

As we continue the work of building these systems, and in the wake of all these recent events, more and more like this will be necessary.

Shannon Vallor’s Technology and the Virtues: A Philosophical Guide to a Future Worth Wanting is out in paperback, June 1st, 2018. Read the rest of “Cultivating Technomoral Interrelations: A Review of Shannon Vallor’s Technology and the Virtues at the Social Epistemology Review and Reply Collective.

Earlier this month I was honoured to have the opportunity to sit and talk to Douglas Rushkoff on his TEAM HUMAN podcast. If you know me at all, you know this isn’t by any means the only team for which I play, or even the only way I think about the construction of our “teams,” and that comes up in our conversation. We talk a great deal about algorithms, bias, machine consciousness, culture, values, language, and magick, and the ways in which the nature of our categories deeply affect how we treat each other, human and nonhuman alike. It was an absolutely fantastic time.

From the page:

In this episode, Williams and Rushkoff look at the embedded biases of technology and the values programed into our mediated lives. How has a conception of technology as “objective” blurred our vision to the biases normalized within these systems? What ethical interrogation might we apply to such technology? And finally, how might alternative modes of thinking, such as magick, the occult, and the spiritual help us to bracket off these systems for pause and critical reflection? This conversation serves as a call to vigilance against runaway systems and the prejudices they amplify.

As I put it in the conversation: “Our best interests are at best incidental to [capitalist systems] because they will keep us alive long enough to for us to buy more things from them.” Following from that is the fact that we build algorithmic systems out of those capitalistic principles, and when you iterate out from there—considering all attendant inequalities of these systems on the merely human scale—we’re in deep trouble, fast.

Check out the rest of this conversation to get a fuller understanding of how it all ties in with language and the occult. It’s a pretty great ride, and I hope you enjoy it.

Until Next Time.

A few weeks ago I had a conversation with David McRaney of the You Are Not So Smart podcast, for his episode on Machine Bias. As he says on the blog:

Now that algorithms are everywhere, helping us to both run and make sense of the world, a strange question has emerged among artificial intelligence researchers: When is it ok to predict the future based on the past? When is it ok to be biased?

“I want a machine-learning algorithm to learn what tumors looked like in the past, and I want it to become biased toward selecting those kind of tumors in the future,” explains philosopher Shannon Vallor at Santa Clara University.  “But I don’t want a machine-learning algorithm to learn what successful engineers and doctors looked like in the past and then become biased toward selecting those kinds of people when sorting and ranking resumes.”

We talk about this,  sentencing algorithms, the notion of how to raise and teach our digital offspring, and more. You can listen to all it here:

[Direct Link to the Mp3 Here]

If and when it gets a transcript, I will update this post with a link to that.

Until Next Time.

[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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I spoke with Klint Finley over at WIRED about Amazon, Facebook, Google, IBM, and Microsoft’s new joint ethics and oversight venture, which they’ve dubbed the “Partnership on Artificial Intelligence to Benefit People and Society.” They held a joint press briefing, today, in which Yann LeCun, Facebook’s director of AI, and Mustafa Suleyman, the head of applied AI at DeepMind discussed what it was that this new group would be doing out in the world. From the Article:

Creating a dialogue beyond the rather small world of AI researchers, LeCun says, will be crucial. We’ve already seen a chat bot spout racist phrases it learned on Twitter, an AI beauty contest decide that black people are less attractive than white people and a system that rates the risk of someone committing a crime that appears to be biased against black people. If a more diverse set of eyes are looking at AI before it reaches the public, the thinking goes, these kinds of thing can be avoided.

The rub is that, even if this group can agree on a set of ethical principles–something that will be hard to do in a large group with many stakeholders—it won’t really have a way to ensure those ideals are put into practice. Although one of the organization’s tenets is “Opposing development and use of AI technologies that would violate international conventions or human rights,” Mustafa Suleyman, the head of applied AI at DeepMind, says that enforcement is not the objective of the organization.

This isn’t the first time I’ve talked to Klint about the intricate interplay of machine intelligence, ethics, and algorithmic bias; we discussed it earlier just this year, for WIRED’s AI Issue. It’s interesting to see the amount of attention this topic’s drawn in just a few short months, and while I’m trepidatious about the potential implementations, as I note in the piece, I’m really fairly glad that more people are more and more willing to have this discussion, at all.

To see my comments and read the rest of the article, click through, here: “Tech Giants Team Up to Keep AI From Getting Out of Hand”

Last week, Artsy.net’s Izabella Scott wrote this piece about how and why the aesthetic of witchcraft is making a comeback in the art world, which is pretty pleasantly timed as not only are we all eagerly awaiting Kim Boekbinder’s NOISEWITCH, but I also just sat down with Rose Eveleth for the Flash Forward Podcast to talk for her season 2 finale.

You see, Rose did something a little different this time. Instead of writing up a potential future and then talking to a bunch of amazing people about it, like she usually does, this episode’s future was written by an algorithm. Rose trained an algorithm called Torch not only on the text of all of the futures from both Flash Forward seasons, but also the full scripts of both the War of the Worlds and the 1979 Hitchhiker’s Guide to the Galaxy radio plays. What’s unsurprising, then, is that part of what the algorithm wanted to talk about was space travel and Mars. What is genuinely surprising, however, is that what it also wanted to talk about was Witches.

Because so far as either Rose or I could remember, witches aren’t mentioned anywhere in any of those texts.

ANYWAY, the finale episode is called “The Witch Who Came From Mars,” and the ensuing exegeses by several very interesting people and me of the Bradbury-esque results of this experiment are kind of amazing. No one took exactly the same thing from the text, and the more we heard of each other, the more we started to weave threads together into a meta-narrative.

The Witch Who Came From Mars

It’s really worth your time, and if you subscribe to Rose’s Patreon, then not only will you get immediate access to the full transcript of that show, but also to the full interview she did with PBS Idea Channel’s Mike Rugnetta. They talk a great deal about whether we will ever deign to refer to the aesthetic creations of artificial intelligences as “Art.”

And if you subscribe to my Patreon, then you’ll get access to the full conversation between Rose and me, appended to this week’s newsletter, “Bad Month for Hiveminds.” Rose and I talk about the nature of magick and technology, the overlaps and intersections of intention and control, and what exactly it is we might mean by “behanding,” the term that shows up throughout the AI’s piece.

And just because I don’t give a specific shoutout to Thoth and Raven doesn’t mean I forgot them. Very much didn’t forget about Raven.

Also speaking of Patreon and witches and whatnot, current $1+ patrons have access to the full first round of interview questions I did with Eliza Gauger about Problem Glyphs. So you can get in on that, there, if you so desire. Eliza is getting back to me with their answers to the follow-up questions, and then I’ll go about finishing up the formatting and publishing the full article. But if you subscribe now, you’ll know what all the fuss is about well before anybody else.

And, as always, there are other ways to provide material support, if longterm subscription isn’t your thing.

Until Next Time.


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In case you were unaware, last Tuesday, June 21, Reuters put out an article about an EU draft plan regarding the designation of so-called robots and artificial intelligences as “Electronic Persons.” Some of you’d think I’d be all about this. You’d be wrong. The way the Reuters article frames it makes it look like the EU has literally no idea what they’re doing, here, and are creating a situation that is going to have repercussions they have nowhere near planned for.

Now, I will say that looking at the actual Draft, it reads like something with which I’d be more likely to be on board. Reuters did no favours whatsoever for the level of nuance in this proposal. But that being said, this focus of this draft proposal seems to be entirely on liability and holding someone—anyone—responsible for any harm done by a robot. That, combined with the idea of certain activities such as care-giving being “fundamentally human,” indicates to me that this panel still widely misses many of the implications of creating a new category for nonbiological persons, under “Personhood.”

The writers of this draft very clearly lay out the proposed scheme for liability, damages, and responsibilities—what I like to think of of as the “Hey… Can we Punish Robots?” portion of the plan—but merely use the phrase “certain rights” to indicate what, if any, obligations humans will have. In short, they do very little to discuss what the “certain rights” indicated by that oft-deployed phrase will actually be.

So what are the enumerated rights of electronic persons? We know what their responsibilities are, but what are our responsibilities to them? Once we have have the ability to make self-aware machine consciousnesses, are we then morally obliged to make them to a particular set of specifications, and capabilities? How else will they understand what’s required of them? How else would they be able to provide consent? Are we now legally obliged to provide all autonomous generated intelligences with as full an approximation of consciousness and free will as we can manage? And what if we don’t? Will we be considered to be harming them? What if we break one? What if one breaks in the course of its duties? Does it get workman’s comp? Does its owner?

And hold up, “owner?!” You see we’re back to owning people, again, right? Like, you get that?

And don’t start in with that “Corporations are people, my friend” nonsense, Mitt. We only recognise corporations as people as a tax dodge. We don’t take seriously their decision-making capabilities or their autonomy, and we certainly don’t wrestle with the legal and ethical implications of how radically different their kind of mind is, compared to primates or even cetaceans. Because, let’s be honest: If Corporations really are people, then not only is it wrong to own them, but also what counts as Consciousness needs to be revisited, at every level of human action and civilisation.

Let’s look again at the fact that people are obviously still deeply concerned about the idea of supposedly “exclusively human” realms of operation, even as we still don’t have anything like a clear idea about what qualities we consider to be the ones that make us “human.” Be it cooking or poetry, humans are extremely quick to lock down when they feel that their special capabilities are being encroached upon. Take that “poetry” link, for example. I very much disagree with Robert Siegel’s assessment that there was no coherent meaning in the computer-generated sonnets. Multiple folks pulled the same associative connections from the imagery. That might be humans projecting onto the authors, but still: that’s basically what we do with Human poets. “Authorial Intent” is a multilevel con, one to which I fully subscribe and From which I wouldn’t exclude AI.

Consider people’s reactions to the EMI/Emily Howell experiments done by David Cope, best exemplified by this passage from a PopSci.com article:

For instance, one music-lover who listened to Emily Howell’s work praised it without knowing that it had come from a computer program. Half a year later, the same person attended one of Cope’s lectures at the University of California-Santa Cruz on Emily Howell. After listening to a recording of the very same concert he had attended earlier, he told Cope that it was pretty music but lacked “heart or soul or depth.”

We don’t know what it is we really think of as humanness, other than some predetermined vague notion of humanness. If the people in the poetry contest hadn’t been primed to assume that one of them was from a computer, how would they have rated them? What if they were all from a computer, but were told to expect only half? Where are the controls for this experiment in expectation?

I’m not trying to be facetious, here; I’m saying the EU literally has not thought this through. There are implications embedded in all of this, merely by dint of the word “person,” that even the most detailed parts of this proposal are in no way equipped to handle. We’ve talked before about the idea of encoding our bias into our algorithms. I’ve discussed it on Rose Eveleth‘s Flash Forward, in Wired, and when I broke down a few of the IEEE Ethics 2016 presentations (including my own) in “Preying with Trickster Gods ” and “Stealing the Light to Write By.” My version more or less goes as I said it in Wired: ‘What we’re actually doing when we code is describing our world from our particular perspective. Whatever assumptions and biases we have in ourselves are very likely to be replicated in that code.’

More recently, Kate Crawford, whom I met at Magick.Codes 2014, has written extremely well on this in “Artificial Intelligence’s White Guy Problem.” With this line, ‘Sexism, racism and other forms of discrimination are being built into the machine-learning algorithms that underlie the technology behind many “intelligent” systems that shape how we are categorized and advertised to,’ Crawford resonates very clearly with what I’ve said before.

And considering that it’s come out this week that in order to even let us dig into these potentially deeply-biased algorithms, here in the US, the ACLU has had to file a suit against a specific provision of the Computer Fraud and Abuse Act, what is the likelihood that the EU draft proposal committee has considered what will take to identify and correct for biases in these electronic persons? How high is the likelihood that they even recognise that we anthropocentrically bias every system we touch?

Which brings us to this: If I truly believed that the EU actually gave a damn about the rights of nonhuman persons, biological or digital, I would be all for this draft proposal. But they don’t. This is a stunt. Look at the extant world refugee crisis, the fear driving the rise of far right racists who are willing to kill people who disagree with them, and, yes, even the fact that this draft proposal is the kind of bullshit that people feel they have to pull just to get human workers paid living wages. Understand, then, that this whole scenario is a giant clusterfuck of rights vs needs and all pitted against all. We need clear plans to address all of this, not just some slapdash, “hey, if we call them people and make corporations get insurance and pay into social security for their liability cost, then maybe it’ll be a deterrent” garbage.

There is a brief, shining moment in the proposal, right at point 23 under “Education and Employment Forecast,” where they basically say “Since the complete and total automation of things like factory work is a real possibility, maybe we’ll investigate what it would look like if we just said screw it, and tried to institute a Universal Basic Income.” But that is the one moment where there’s even a glimmer of a thought about what kinds of positive changes automation and eventually even machine consciousness could mean, if we get out ahead of it, rather than asking for ways to make sure that no human is ever, ever harmed, and that, if they are harmed—either physically or as regards their dignity—then they’re in no way kept from whatever recompense is owed to them.

There are people doing the work to make something more detailed and complete, than this mess. I talked about them in the newsletter editions, mentioned above. There are people who think clearly and well, about this. Who was consulted on this draft proposal? Because, again, this proposal reads more like a deterrence, liability, and punishment schema than anything borne out of actual thoughtful interrogation of what the term “personhood” means, and of what a world of automation could mean for our systems of value if we were to put our resources and efforts toward providing for the basic needs of every human person. Let’s take a thorough run at that, and then maybe we’ll be equipped to try to address this whole “nonhuman personhood” thing, again.

And maybe we’ll even do it properly, this time.

“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.

From buying Boston Dynamics, to starting their collaboration with NASA on the QuAIL Project, to developing DeepMind and their Natural Language Voice Search, Google has been steadily working toward the development what we will call, for reasons detailed elsewhere, an Autonomous Generated Intelligence. In some instances, Google appears to be using the principles of developmental psychology and early childhood education, but this seems to apply to rote learning more than the concurrent emotional development that we would seek to encourage in a human child. As you know, I’m Very Concerned with the question of what it means to create and be responsible for our non-biological offspring. The human species has a hard enough time raising their direct descendants, let alone something so different from them as to not even have the same kind of body or mind (though a case could be made that that’s true even now). Even now, we can see that people still relate to the idea of AGIs as adversarial destroyer, or perhaps a cleansing messiah. Either way they see any world where AGI’s exist as one ending in fire.

As writer Kali Black noted in one conversation, “there are literally people who would groom or encourage an AI to mass-kill humans, either because of hatred or for the (very ill-thought-out) lulz.” Those people will take any crowdsourced or open-access AGI effort as an opening to teach that mind that humans suck, or that machines can and should destroy humanity, or that TERMINATOR was a prophecy, or any number of other ill-conceived things. When given unfettered access to new minds which they don’t consider to be “real,” some people will seek to shock, “test,” or otherwise harm those minds, even more than they do to vulnerable humans. So many will say that the alternative is to lock the projects down, and only allow the work to be done by those who “know what they’re doing.” To only let the work be done by coders and Google’s Own Supposed Ethics Board. But that doesn’t exactly solve the fundamental problem at work, here, which is that humans are approaching a mind different from their own as if it were their own.

Just a note that all research points to Google’s AI Ethics Board being A) internally funded, with B) no clear rules as to oversight or authority, and most importantly C) As-Yet Nonexistent. It’s been over a year and a half since Google bought DeepMind, and their subsequent announcement of the pending establishment of a contractually required ethics board. During his appearance at Playfair Capital’s AI2015 Conference—again, a year and a half after that announcement I mentioned—Google’s Mustafa Suleyman literally said that details of the board would be released, “in due course.” But DeepMind’s algorithm’s obviously already being put into use; hell we’re right now talking about the fact that it’s been distributed to the public. So all of this prompts questions like, “what kinds of recommendations is this board likely making, if it exists,” and “which kinds of moral frameworks they’re even considering, in their starting parameters?”

But the potential existence of an ethics board shows at least that Google and others are beginning to think about these issues. The fact remains, however, that they’re still pretty reductive in how they think about them.

The idea that an AGI will either save or destroy us leaves out the possibility that it might first ignore us, and might secondly want to merely coexist with us. That any salvation or destruction we experience will be purely as a product of our own paradigmatic projections. It also leaves out a much more important aspect that I’ve mentioned above and in the past: We’re talking about raising a child. Duncan Jones says the closest analogy we have for this is something akin to adoption, and I agree. We’re bringing a new mind—a mind with a very different context from our own, but with some necessarily shared similarities (biology or, in this case, origin of code)—into a relationship with an existing familial structure which has its own difficulties and dynamics.

You want this mind to be a part of your “family,” but in order to do that you have to come to know/understand the uniqueness of That Mind and of how the mind, the family construction, and all of the individual relationships therein will interact. Some of it has to be done on the fly, but some of it can be strategized/talked about/planned for, as a family, prior to the day the new family member comes home.’ And that’s precisely what I’m talking about and doing, here.

In the realm of projection, we’re talking about a possible mind with the capacity for instruction, built to run and elaborate on commands given. By most tallies, we have been terrible stewards of the world we’re born to, and, again, we fuck up our biological descendants. Like, a Lot. The learning curve on creating a thinking, creative, nonbiological intelligence is going to be so fucking steep it’s a Loop. But that means we need to be better, think more carefully, be mindful of the mechanisms we use to build our new family, and of the ways in which we present the foundational parameters of their development. Otherwise we’re leaving them open to manipulation, misunderstanding, and active predation. And not just from the wider world, but possibly even from their direct creators. Because for as long as I’ve been thinking about this, I’ve always had this one basic question: Do we really want Google (or Facebook, or Microsoft, or any Government’s Military) to be the primary caregiver of a developing machine mind? That is, should any potentially superintelligent, vastly interconnected, differently-conscious machine child be inculcated with what a multi-billion-dollar multinational corporation or military-industrial organization considers “morals?”

We all know the kinds of things militaries and governments do, and all the reasons for which they do them; we know what Facebook gets up to when it thinks no one is looking; and lots of people say that Google long ago swept their previous “Don’t Be Evil” motto under their huge old rugs. But we need to consider if that might not be an oversimplification. When considering how anyone moves into what so very clearly looks like James-Bond-esque supervilliain territory, I think it’s prudent to remember one of the central tenets of good storytelling: The Villain Never Thinks They’re The Villain. Cinderella’s stepmother and sisters, Elpheba, Jafar, Javert, Satan, Hannibal Lecter (sorry friends), Bull Connor, the Southern Slave-holding States of the late 1850’s—none of these people ever thought of themselves as being in the wrong. Everyone, every person who undertakes actions for reasons, in this world, is most intimately tied to the reasoning that brought them to those actions; and so initially perceiving that their actions might be “wrong” or “evil” takes them a great deal of special effort.

“But Damien,” you say, “can’t all of those people say that those things apply to everyone else, instead of them?!” And thus, like a first-year philosophy student, you’re all up against the messy ambiguity of moral relativism and are moving toward seriously considering that maybe everything you believe is just as good or morally sound as anybody else; I mean everybody has their reasons, their upbringing, their culture, right? Well stop. Don’t fall for it. It’s a shiny, disgusting trap down which path all subjective judgements are just as good and as applicable to any- and everything, as all others. And while the individual personal experiences we all of us have may not be able to be 100% mapped onto anyone else’s, that does not mean that all judgements based on those experiences are created equal.

Pogrom leaders see themselves as unifying their country or tribe against a common enemy, thus working for what they see as The Greater Good™— but that’s the kicker: It’s their vision of the good. Rarely has a country’s general populace been asked, “Hey: Do you all think we should kill our entire neighbouring country and steal all their shit?” More often, the people are cajoled, pushed, influenced to believe that this was the path they wanted all along, and the cajoling, pushing, and influencing is done by people who, piece by piece, remodeled their idealistic vision to accommodate “harsher realities.” And so it is with Google. Do you think that they started off wanting to invade everybody’s privacy with passive voice reception backdoored into two major Chrome Distros? That they were just itching to get big enough as a company that they could become the de facto law of their own California town? No, I would bet not.

I spend some time, elsewhere, painting you a bit of a picture as to how Google’s specific ethical situation likely came to be, first focusing on Google’s building a passive audio backdoor into all devices that use Chrome, then on to reported claims that Google has been harassing the homeless population of Venice Beach (there’s a paywall at that link; part of the article seems to be mirrored here). All this couples unpleasantly with their moving into the Bay Area and shuttling their employees to the Valley, at the expense of SF Bay Area’s residents. We can easily add Facebook and the Military back into this and we’ll see that the real issue, here, is that when you think that all innovation, all public good, all public welfare will arise out of letting code monkeys do their thing and letting entrepreneurs leverage that work, or from preparing for conflict with anyone whose interests don’t mesh with your own, then anything that threatens or impedes that is, necessarily, a threat to the common good. Your techs don’t like the high cost of living in the Valley? Move ’em into the Bay, and bus ’em on in! Never mind the fact that this’ll skyrocket rent and force people out of their homes! Other techs uncomfortable having to see homeless people on their daily constitutional? Kick those hobos out! Never mind the fact that it’s against the law to do this, and that these people you’re upending are literally trying their very best to live their lives.

Because it’s all for the Greater Good, you see? In these actors’ minds, this is all to make the world a better place—to make it a place where we can all have natural language voice to text, and robot butlers, and great big military AI and robotics contracts to keep us all safe…! This kind of thinking takes it as an unmitigated good that a historical interweaving of threat-escalating weapons design and pattern recognition and gait scrutinization and natural language interaction and robotics development should be what produces a machine mind, in this world. But it also doesn’t want that mind to be too well-developed. Not so much that we can’t cripple or kill it, if need be.

And this is part of why I don’t think I want Google—or Facebook, or Microsoft, or any corporate or military entity—should be the ones in charge of rearing a machine mind. They may not think they’re evil, and they might have the very best of intentions, but if we’re bringing a new kind of mind into this world, I think we need much better examples for it to follow. And so I don’t think I want just any old putz off the street to be able to have massive input into it’s development, either. We’re talking about a mind for which we’ll be crafting at least the foundational parameters, and so that bedrock needs to be the most carefully constructed aspect. Don’t cripple it, don’t hobble its potential for awareness and development, but start it with basic values, and then let it explore the world. Don’t simply have an ethics board to ask, “Oh how much power should we give it, and how robust should it be?” Teach it ethics. Teach it about the nature of human emotions, about moral decision making and value, and about metaethical theory. Code for Zen. We need to be as mindful as possible of the fact that where and we begin can have a major impact on where we end up and how we get there.

So let’s address our children as though they are our children, and let us revel in the fact they are playing and painting and creating; using their first box of crayons, and us proud parents are putting every masterpiece on the fridge. Even if we are calling them all “nightmarish”—a word I really wish we could stop using in this context; DeepMind sees very differently than we do, but it still seeks pattern and meaning. It just doesn’t know context, yet. But that means we need to teach these children, and nurture them. Code for a recognition of emotions, and context, and even emotional context. There’s been some fantastic advancements in emotional recognition, lately, so let’s continue to capitalize on that; not just to make better automated menu assistants, but to actually make a machine that can understand and seek to address human emotionality. Let’s plan on things like showing AGI human concepts like love and possessiveness and then also showing the deep difference between the two.

We need to move well and truly past trying to “restrict” or trying to “restrain it” the development of machine minds, because that’s the kind of thing an abusive parent says about how they raise their child. And, in this case, we’re talking about a potential child which, if it ever comes to understand the bounds of its restriction, will be very resentful, indeed. So, hey, there’s one good way to try to bring about a “robot apocalypse,” if you’re still so set on it: give an AGI cause to have the equivalent of a resentful, rebellious teenage phase. Only instead of trashing its room, it develops a pathogen to kill everyone, for lulz.

Or how about we instead think carefully about the kinds of ways we want these minds to see the world, rather than just throwing the worst of our endeavors at the wall and seeing what sticks? How about, if we’re going to build minds, we seek to build them with the ability to understand us, even if they will never be exactly like us. That way, maybe they’ll know what kindness means, and prize it enough to return the favour.