Tag: my words

I’m Not Afraid of AI Overlords— I’m Afraid of Whoever’s Training Them To Think That Way

Posted by Damien P. Williams on October 8, 2021

Posted in: Uncategorized. Tagged: ai, algorithmic bias, algorithmic intelligence, algorithmic justice, algorithmic systems, algorithms, alondra nelson, alvaro bedoya, anna lauren hoffman, artificial intelligence, ashley shew, bias, cambridge analytica, clare garvie, disability, disability studies, epistemology, ethics washing, facebook, facial recognition, frances haugen, google, humanities, Invisible Architecture of Bias, Invisible Architectures of Bias, joy buolamwini, justice, kim crayton, machine learning, my words, my work, my writing, oversight board, philosophy, philosophy of technology, politics, public policy, ruha benjamin, safiya noble, science and technology studies, science technology and society, social construction of technology, social dynamics, social sciences, sociology, sts, technological ethics, timnit gebru, twitter, u.s. politics, values, virginia eubanks, white house office of science and technology policy, youtube. 3 comments

I’m Not Afraid of AI Overlords— I’m Afraid of Whoever’s Training Them To Think That Way

by Damien P. Williams

I want to let you in on a secret: According to Silicon Valley’s AI’s, I’m not human.

Well, maybe they think I’m human, but they don’t think I’m me. Or, if they think I’m me and that I’m human, they think I don’t deserve expensive medical care. Or that I pose a higher risk of criminal recidivism. Or that my fidgeting behaviours or culturally-perpetuated shame about my living situation or my race mean I’m more likely to be cheating on a test. Or that I want to see morally repugnant posts that my friends have commented on to call morally repugnant. Or that I shouldn’t be given a home loan or a job interview or the benefits I need to stay alive.

Now, to be clear, “AI” is a misnomer, for several reasons, but we don’t have time, here, to really dig into all the thorny discussion of values and beliefs about what it means to think, or to be a pow3rmind— especially because we need to take our time talking about why values and beliefs matter to conversations about “AI,” at all. So instead of “AI,” let’s talk specifically about algorithms, and machine learning.

Machine Learning (ML) is the name for a set of techniques for systematically reinforcing patterns, expectations, and desired outcomes in various computer systems. These techniques allow those systems to make sought after predictions based on the datasets they’re trained on. ML systems learn the patterns in these datasets and then extrapolate them to model a range of statistical likelihoods of future outcomes.

Algorithms are sets of instructions which, when run, perform functions such as searching, matching, sorting, and feeding the outputs of any of those processes back in on themselves, so that a system can learn from and refine itself. This feedback loop is what allows algorithmic machine learning systems to provide carefully curated search responses or newsfeed arrangements or facial recognition results to consumers like me and you and your friends and family and the police and the military. And while there are many different types of algorithms which can be used for the above purposes, they all remain sets of encoded instructions to perform a function.

And so, in these systems’ defense, it’s no surprise that they think the way they do: That’s exactly how we’ve told them to think.

[Image of Michael Emerson as Harold Finch, in season 2, episode 1 of the show Person of Interest, “The Contingency.” His face is framed by a box of dashed yellow lines, the words “Admin” to the top right, and “Day 1” in the lower right corner.]

Hello Everyone.

Here is my prerecorded talk for the NC State R.L. Rabb Symposium on Embedding AI in Society.

There are captions in the video already, but I’ve also gone ahead and C/P’d the SRT text here, as well.

There were also two things I meant to mention, but failed to in the video:

1) The history of facial recognition and carceral surveillance being used against Black and Brown communities ties into work from Lundy Braun, Melissa N Stein, Seiberth et al., and myself on the medicalization and datafication of Black bodies without their consent, down through history. (Cf. Me, here: Fitting the description: historical and sociotechnical elements of facial recognition and anti-black surveillance”.)

2) Not only does GPT-3 fail to write about humanities-oriented topics with respect, it still can’t write about ISLAM AT ALL without writing in connotations of violence and hatred.

Also I somehow forgot to describe the slide with my email address and this website? What the hell Damien.

Anyway.

I’ve embedded the content of the resource slides in the transcript, but those are by no means all of the resources on this, just the most pertinent.

All of that begins below the cut.

Black man with a mohawk and glasses, wearing a black button up shirt, a red paisley tie, a light grey check suit jacket, and black jeans, stands in front of two tall bookshelves full of books, one thin & red, one of wide untreated pine, and a large monitor with a printer and papers on the stand beneath it.

[First conference of the year; figured i might as well get gussied up.]

Master and Servant: Disciplinarity and the Implications of AI and Cyborg Identity

Posted by Damien P. Williams on May 4, 2020

Posted in: Uncategorized. Tagged: algorithmic bias, algorithmic systems, anti-capitalism, artificial intelligence, assistive technology, autonomous created intelligence, autonomous generated intelligence, bias, biotechnology, bodyminds, capitalism, cyborg, cyborg anthropology, cyborgs, decolonial studies, decolonization, disability, disability studies, disciplinarity, discipline and punish, facial recognition, foucault, gender, gender studies, harriet washington, Invisible Architecture of Bias, Invisible Architectures of Bias, jan golinski, lgbtqia+, machine consciousness, medical apartheid, misogyny, more work for mother, my words, my work, phenomenology, race, racism, resist, ruth schwartz cowan, science technology and society, semper eam posse utrumque, sexuality, situated knowledge, sts, surveillance culture, systemic disparity, systems of control, technological ethics, technology, transphobia. Leave a Comment

Much of my research deals with the ways in which bodies are disciplined and how they go about resisting that discipline. In this piece, adapted from one of the answers to my PhD preliminary exams written and defended two months ago, I “name the disciplinary strategies that are used to control bodies and discuss the ways that bodies resist those strategies.” Additionally, I address how strategies of embodied control and resistance have changed over time, and how identifying and existing as a cyborg and/or an artificial intelligence can be understood as a strategy of control, resistance, or both.

In Jan Golinski’s Making Natural Knowledge, he spends some time discussing the different understandings of the word “discipline” and the role their transformations have played in the definition and transmission of knowledge as both artifacts and culture. In particular, he uses the space in section three of chapter two to discuss the role Foucault has played in historical understandings of knowledge, categorization, and disciplinarity. Using Foucault’s work in Discipline and Punish, we can draw an explicit connection between the various meanings “discipline” and ways that bodies are individually, culturally, and socially conditioned to fit particular modes of behavior, and the specific ways marginalized peoples are disciplined, relating to their various embodiments.

This will demonstrate how modes of observation and surveillance lead to certain types of embodiments being deemed “illegal” or otherwise unacceptable and thus further believed to be in need of methodologies of entrainment, correction, or reform in the form of psychological and physical torture, carceral punishment, and other means of institutionalization.

Locust, “Master and Servant (Depeche Mode Cover)”

Audio, Transcript, and Slides from “SFF and STS: Teaching Science, Technology, and Society via Pop Culture”

Posted by Damien P. Williams on September 22, 2019

Posted in: Uncategorized. Tagged: A Future Worth Thinking About, ableism, Actor-network theory, african diaspora, africanfuturism, afrofuturism, akira, algorithmic systems, amazon, animal ethics, Anne Leckie, anthropology, audio, bias, bitch planet, black panther, compassion, consciousness, damien patrick williams, decolonial studies, decolonization, disability, disability studies, Dune, ethics, ethnography, farscape, feminist ethics, frank herbert, frankenstein, gender, ghost in the shell, implicit bias, indigenous knowledge, Invisible Architecture of Bias, Invisible Architectures of Bias, iron man, Janelle Monáe, kelly sue deconnick, Lizzo, mary shelley, Missy Elliott, my voice, my words, my work, my writing, N.K. Jemisin, neurodiversity, Nnedi Okorafor, Octavia Butler, person of interest, philosophy of technology, pop culture, post-colonial studies, primer, race, racism, Samuel Delaney, science and technology studies, science fiction, science fiction and fantasy, science technology and society, sexism, sff, social dynamics, Society for the Social Studies of Science, sociology, sts, surveillance culture, systemic disparity, technology, the animatrix, The Broken Earth, transcripts, upstream color, Urula K Le Guin, Who Fears Death, Xenogenesis. Leave a Comment

Below are the slides, audio, and transcripts for my talk “SFF and STS: Teaching Science, Technology, and Society via Pop Culture” given at the 2019 Conference for the Society for the Social Studies of Science, in early September.

(Cite as: Williams, Damien P. “SFF and STS: Teaching Science, Technology, and Society via Pop Culture,” talk given at the 2019 Conference for the Society for the Social Studies of Science, September 2019)

[Direct Link to the Mp3]

[Damien Patrick Williams]

Thank you, everybody, for being here. I’m going to stand a bit far back from this mic and project, I’m also probably going to pace a little bit. So if you can’t hear me, just let me know. This mic has ridiculously good pickup, so I don’t think that’ll be a problem.

So the conversation that we’re going to be having today is titled as “SFF and STS: Teaching Science, Technology, and Society via Pop Culture.”

I’m using the term “SFF” to stand for “science fiction and fantasy,” but we’re going to be looking at pop culture more broadly, because ultimately, though science fiction and fantasy have some of the most obvious entrees into discussions of STS and how making doing culture, society can influence technology and the history of fictional worlds can help students understand the worlds that they’re currently living in, pop Culture more generally, is going to tie into the things that students are going to care about in a way that I think is going to be kind of pertinent to what we’re going to be talking about today.

So why we are doing this:

Why are we teaching it with science fiction and fantasy? Why does this matter? I’ve been teaching off and on for 13 years, I’ve been teaching philosophy, I’ve been teaching religious studies, I’ve been teaching Science, Technology and Society. And I’ve been coming to understand as I’ve gone through my teaching process that not only do I like pop culture, my students do? Because they’re people and they’re embedded in culture. So that’s kind of shocking, I guess.

But what I’ve found is that one of the things that makes students care the absolute most about the things that you’re teaching them, especially when something can be as dry as logic, or can be as perhaps nebulous or unclear at first, I say engineering cultures, is that if you give them something to latch on to something that they are already from with, they will be more interested in it. If you can show to them at the outset, “hey, you’ve already been doing this, you’ve already been thinking about this, you’ve already encountered this, they will feel less reticent to engage with it.”

Audio, Transcripts, and Slides from “Any Sufficiently Advanced Neglect is Indistinguishable from Malice”

Posted by Damien P. Williams on August 20, 2019

Posted in: Uncategorized. Tagged: A Future Worth Thinking About, ableism, algorithmic bias, algorithmic justice, algorithmic systems, amazon, animal ethics, audio, bias, biomedical ethics, biotech ethics, compassion, consciousness, damien patrick williams, debbie chachra, disability, disability studies, embodied cognition, ethics, facebook, facial recognition, feminist ethics, Gayatri Spivak, gender, google, homophobia, implicit bias, intersubjectivity, Invisible Architecture of Bias, Invisible Architectures of Bias, joy buolamwini, kimberlé williams crenshaw, Machine ethics, machine intelligence, misogyny, my voice, my words, my work, my writing, neurodiversity, neuroethics, personhood rights, phenomenology, philosophy of mind, philosophy of technology, race, racism, ruha benjamin, science and technology studies, science technology and society, sexism, social cognition, social dynamics, Society for Philosophy and Technology, surveillance culture, systemic disparity, technological ethics, technology, transcripts, transphobia. 2 comments

Below are the slides, audio, and transcripts for my talk ‘”Any Sufficiently Advanced Neglect is Indistinguishable from Malice”: Assumptions and Bias in Algorithmic Systems,’ given at the 21st Conference of the Society for Philosophy and Technology, back in May 2019.

(Cite as: Williams, Damien P. ‘”Any Sufficiently Advanced Neglect is Indistinguishable from Malice”: Assumptions and Bias in Algorithmic Systems;’ talk given at the 21st Conference of the Society for Philosophy and Technology; May 2019)

Now, I’ve got a chapter coming out about this, soon, which I can provide as a preprint draft if you ask, and can be cited as “Constructing Situated and Social Knowledge: Ethical, Sociological, and Phenomenological Factors in Technological Design,” appearing in Philosophy And Engineering: Reimagining Technology And Social Progress. Guru Madhavan, Zachary Pirtle, and David Tomblin, eds. Forthcoming from Springer, 2019. But I wanted to get the words I said in this talk up onto some platforms where people can read them, as soon as possible, for a couple of reasons.

First, the Current Occupants of the Oval Office have very recently taken the policy position that algorithms can’t be racist, something which they’ve done in direct response to things like Google’s Hate Speech-Detecting AI being biased against black people, and Amazon claiming that its facial recognition can identify fear, without ever accounting for, i dunno, cultural and individual differences in fear expression?

[Free vector image of a white, female-presenting person, from head to torso, with biometric facial recognition patterns on her face; incidentally, go try finding images—even illustrations—of a non-white person in a facial recognition context.]

All these things taken together are what made me finally go ahead and get the transcript of that talk done, and posted, because these are events and policy decisions about which I a) have been speaking and writing for years, and b) have specific inputs and recommendations about, and which are, c) frankly wrongheaded, and outright hateful.

And I want to spend time on it because I think what doesn’t get through in many of our discussions is that it’s not just about how Artificial Intelligence, Machine Learning, or Algorithmic instances get trained, but the processes for how and the cultural environments in which HUMANS are increasingly taught/shown/environmentally encouraged/socialized to think is the “right way” to build and train said systems.

That includes classes and instruction, it includes the institutional culture of the companies, it includes the policy landscape in which decisions about funding and get made, because that drives how people have to talk and write and think about the work they’re doing, and that constrains what they will even attempt to do or even understand.

All of this is cumulative, accreting into institutional epistemologies of algorithm creation. It is a structural and institutional problem.

So here are the Slides:

The Audio:

[Direct Link to Mp3]

And the Transcript is here below the cut:

2017 SRI Technology and Consciousness Workshop Series Final Report

Posted by Damien P. Williams on March 8, 2019

Posted in: Uncategorized. Tagged: A Future Worth Thinking About, ableism, Adrian Willoughby, advaita vedanta, algorithmic bias, Alva Noe, animal ethics, Antonio Chella, bias, Bill Rowe, biomedical ethics, biotech ethics, buddhism, Christof Koch, compassion, consciousness, damien patrick williams, Daniel Sanchez, daoism, David Chalmers, David Gamez, David Presti, David Sahner, disability, disability studies, Earth Erowid, eastern philosophy, embodied cognition, ethics, extended mind hypothesis, feminist ethics, Fire Erowid, Gary Small, gender, Giulio Tononi, Henk Barendregt, homophobia, Ian Horswill, implicit bias, intersubjectivity, Invisible Architecture of Bias, Invisible Architectures of Bias, Joanna Bryson, John Murray, John Rushby, John Sullins III, Jonathan Moreno, Julia Mossbridge, machine consciousness, Machine ethics, machine intelligence, machine minds, Marcia Grabowecky, Mark Bickhard, my words, my work, my writing, Naveen Sundar Govindarajulu, neurodiversity, neuroethics, nonhuman animals, nonhuman personhood, nonwestern philosophy, Owen Holland, Patrick Lincoln, Paul Syverson, personhood rights, phenomenology, philosophy of mind, philosophy of technology, race, racism, Robin Zebrowski, Ron Rensink, Selmer Bringsjord, sexism, shannon vallor, social cognition, social dynamics, sri international, Subash Kak, Susan Blackmore, Susan Kaiser-Greenland, Susan Schneider, taoism, technological ethics, technology, technology and consciousness workshop series, transphobia. 4 comments

So, as you know, back in the summer of 2017 I participated in SRI International’s Technology and Consciousness Workshop Series. This series was an eight week program of workshops the current state of the field around, the potential future paths toward, and the moral and social implications of the notion of conscious machines. To do this, we brought together a rotating cast of dozens of researchers in AI, machine learning, psychedelics research, ethics, epistemology, philosophy of mind, cognitive computing, neuroscience, comparative religious studies, robotics, psychology, and much more.

[Image of my name card from the Technology & Consciousness workshop series.]

We traveled from Arlington, VA, to Menlo Park, CA, to Cambridge, UK, and back, and while my primary role was that of conference co-ordinator and note-taker (that place in the intro where it says I “maintained scrupulous notes?” Think 405 pages/160,656 words of notes, taken over eight 5-day weeks of meetings), I also had three separate opportunities to present: Once on interdisciplinary perspectives on minds and mindedness; then on Daoism and Machine Consciousness; and finally on a unifying view of my thoughts across all of the sessions. In relation to this report, I would draw your attention to the following passage:

An objection to this privileging of sentience is that it is anthropomorphic “meat chauvinism”: we are projecting considerations onto technology that derive from our biology. Perhaps conscious technology could have morally salient aspects distinct from sentience: the basic elements of its consciousness could be different than ours.

All of these meetings were held under the auspices of the Chatham House Rule, which meant that there were many things I couldn’t tell you about them, such as the names of the other attendees, or what exactly they said in the context of the meetings. What I was able tell you, however, was what I talked about, and I did, several times. But as of this week, I can give you even more than that.

This past Thursday, SRI released an official public report on all of the proceedings and findings from the 2017 SRI Technology and Consciousness Workshop Series, and they have told all of the participants that they can share said report as widely as they wish. Crucially, that means that I can share it with you. You can either click this link, here, or read it directly, after the cut.

“Consciousness and Conscious Machines: What’s At Stake?”

Posted by Damien P. Williams on January 16, 2019

Posted in: Uncategorized. Tagged: A Future Worth Thinking About, ableism, advaita vedanta, algorithmic bias, animal ethics, autonomous created intelligence, autonomous creative intelligence, autonomous generated intelligence, autonomously creative intelligence, bias, biomedical ethics, biotech ethics, buddhism, compassion, consciousness, daoism, disability, disability studies, distributed machine consciousness, eastern philosophy, embodied cognition, embodied machine consciousness, ethics, extended mind hypothesis, feminist ethics, gender, homophobia, implicit bias, intersubjectivity, Invisible Architecture of Bias, Invisible Architectures of Bias, machine consciousness, Machine ethics, machine intelligence, machine minds, my words, my work, my writing, neurodiversity, neuroethics, nonhuman animals, nonhuman personhood, nonwestern philosophy, personhood rights, phenomenology, philosophy of mind, philosophy of technology, race, racism, sexism, social cognition, social dynamics, taoism, technological ethics, technology, technology and consciousness workshop series, transphobia. 1 comment

[This paper was prepared for the 2019 Towards Conscious AI Systems Symposium co-located with the Association for the Advancement of Artificial Intelligence 2019 Spring Symposium Series.

Much of this work derived from my final presentation at the 2017 SRI Technology and Consciousness Workshop Series: “Science, Ethics, Epistemology, and Society: Gains for All via New Kinds of Minds”.]

Abstract. This paper explores the moral, epistemological, and legal implications of multiple different definitions and formulations of human and nonhuman consciousness. Drawing upon research from race, gender, and disability studies, including the phenomenological basis for knowledge and claims to consciousness, I discuss the history of the struggles for personhood among different groups of humans, as well as nonhuman animals, and systems. In exploring the history of personhood struggles, we have a precedent for how engagements and recognition of conscious machines are likely to progress, and, more importantly, a roadmap of pitfalls to avoid. When dealing with questions of consciousness and personhood, we are ultimately dealing with questions of power and oppression as well as knowledge and ontological status—questions which require a situated and relational understanding of the stakeholders involved. To that end, I conclude with a call and outline for how to place nuance, relationality, and contextualization before and above the systematization of rules or tests, in determining or applying labels of consciousness.

Keywords: Consciousness, Machine Consciousness, Philosophy of Mind, Phenomenology, Bodyminds

[Overlapping images of an Octopus carrying a shell, a Mantis Shrimp on the sea floor, and a Pepper Robot]

My Appearance on The Machine Ethics Podcast’s A.I. Retreat Episode

Posted by Damien P. Williams on October 23, 2018

Posted in: Uncategorized. Tagged: algorithmic bias, algorithmic intelligence, algorithmic justice, algorithmic systems, andy budd, artificial intelligence, artificial superintelligence, audio, autonomous created intelligence, autonomous creative intelligence, autonomous generated intelligence, autonomously creative intelligence, ben byford, ben sauer, consciousness, Dan Saffer, design, disability studies, distributed machine consciousness, distributed networked intelligence, embodied machine consciousness, ethics, gender, gender studies, Hollie Lubbock, intelligence, juvet, machine consciousness, Machine ethics, machine intelligence, machine learning, machine minds, magic, magick, meta-ethics, moral agency, moral patiency, my voice, my words, neurodiversity, neuroethics, norway, phenomenology, philosophy of mind, philosophy of technology, podcasts, race, science and technology studies, science technology and society, Syd Lawrence, the machine ethics podcast, The Second Future of A.I. Retreat. Leave a Comment

As you already know, we went to the second Juvet A.I. Retreat, back in September. If you want to hear several of us talk about what we got up to at the then you’re in luck because here are several conversations conducted by Ben Byford of the Machine Ethics Podcast.

I am deeply grateful to Ben Byford for asking me to sit down and talk about this with him. I talk a great deal, and am surprisingly able to (cogently?) get on almost all of my bullshit—technology and magic and the occult, nonhuman personhood, the sham of gender and race and other social constructions of expected lived categories, the invisible architecture of bias, neurodiversity, and philosophy of mind—in a rather short window of time.

So that’s definitely something…

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.

Last week, I talked to The Atlantic’s Ed Yong about new research in crowd sentiment tipping points, how it could give hope and dread for those working for social change, and how it might be used by bad actors to create/enhance already-extant sentiment-manipulation factories.

From the article:

…“You see this clump of failures below 25 percent and this clump of successes above 25 percent,” Centola says. “Mathematically, we predicted that, but seeing it in a real population was phenomenal.”

“What I think is happening at the threshold is that there’s a pretty high probability that a noncommitted actor”—a person who can be swayed in any direction—“will encounter a majority of committed minority actors, and flip to join them,” says Pamela Oliver, a sociologist at the University of Wisconsin at Madison. “There is therefore a good probability that enough non-committed actors will all flip at the same time that the whole system will flip.”

We talked about a lot, and much of it didn’t make it into the article, but one of the things that matters most about all of this is that we’re going to have to be increasingly mindful and intentional about the information we take in. We now know that we have the ability to move the needle of conversation, with not too much effort, and with this knowledge we can make progressive social change. We can use this to fight against the despair that can so easily creep into this work of spreading compassion and trying to create a world where we can all flourish.

[Argentina’s Mt Tronador Casaño Overa glacier, by McKay Savage]

But we have to know that there will also be those who see this as a target number to hit so that they might better disrupt and destabilize groups and beliefs. We already know that many such people are hard at work, trying to sow doubt and mistrust. We already have evidence that these actors will make other people’s lives unpleasant for the sake of it. With this new research, they’ll be encouraged, as well. As I said to Ed Yong:

“There are already a number of people out there who are gaming group dynamics in careful ways… If they know what target numbers they have to hit, it’s easy to see how they could take this information and create [or increase the output of the existing] sentiment-manipulation factory.”

The infiltration of progressive groups to move them toward chaos and internal strife is not news, just like the infiltration (and origin) of police and military groups by white supremacists is not news.

And so, while I don’t want to add to a world in which people feel like they have to continually mistrust each other, we do have to be intentional about the work we do, and how we do it, and we have to be mindful of who is trying to get us to believe what, and why they want us to believe it. Especially if we want to get others to believe and value as we do.

This research gives us a useful set of tools and a good to place to start.

Until Next Time.

A Future Worth Thinking About

Thinking about magic, cyborgs, robots, and artificial intelligence--and why some of those words could use changing--since 1982.

my words

All posts tagged my words

Video and Transcript: “Why AI Research Needs Disabled and Marginalized Perspectives”

Master and Servant: Disciplinarity and the Implications of AI and Cyborg Identity

My Appearance on The Machine Ethics Podcast’s A.I. Retreat Episode

At HPE: “4 obstacles to ethical AI (and how to address them)”

On Social Tipping Points

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