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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:

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”

A Future Worth Thinking About

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

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From WIRED: “Tech Giants Team Up to Keep AI From Getting Out of Hand”

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