my work

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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.”

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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:

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2017 SRI Technology and Consciousness Workshop Series Final Report

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 a rectangular name card with a stylized "Technology & Consciousness" logo, at the top, the name Damien Williams in bold in the middle, and SRI International italicized at the bottom; to the right a blurry wavy image of what appears to be a tree with a person standing next to it and another tree in the background to the left., all partially mirrored in a surface at the bottom of the image.

[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.

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[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]

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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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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.

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

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

[Image of the cover of the 2017 edited, annotated edition of Mary Shelley’s Frankenstein, “Annotated for Scientists, Engineers, and Creators of All Kinds.”]

Well, a few months ago, I was approached by the organizers and asked to contribute to a larger online interactive version of the book—to provide an annotation on some aspect of the book I deemed crucial and important to understand. As of now, there is a full functional live beta version of the website, and you can see my contribution and the contributions of many others, there.

From the About Page:

Frankenbook is a collective reading and collaborative annotation experience of the original 1818 text of Frankenstein; or, The Modern Prometheus, by Mary Wollstonecraft Shelley. The project launched in January 2018, as part of Arizona State University’s celebration of the novel’s 200th anniversary. Even two centuries later, Shelley’s modern myth continues to shape the way people imagine science, technology, and their moral consequences. Frankenbook gives readers the opportunity to trace the scientific, technological, political, and ethical dimensions of the novel, and to learn more about its historical context and enduring legacy.

To learn more about Arizona State University’s celebration of Frankenstein’s bicentennial, visit frankenstein.asu.edu.

You’ll need to have JavaScript enabled and ad-blocks disabled to see the annotations, but it works quite well. Moving forward, there will be even more features added, including a series of videos. Frankenbook.org will be the place to watch for all updates and changes.

I am deeply honoured to have been asked to be a part of this amazing project, over the past two years, and I am so very happy that I get to share it with all of you, now. I really hope you enjoy it.

Until Next Time.

So by now you’re likely to have encountered something about the NYT Op-Ed Piece calling for a field of study that focuses on the impact of AI and algorithmic systems, a stance that elides the existence of not only communications and media studies people who focus on this work, but the whole entire disciplines of Philosophy of Technology and STS (rendered variously as “Science and Technology Studies” or “Science Technology and Society,” depending on a number of factors, but if you talk about STS, you’ll get responses from all of the above, about the same topics). While Dr. O’Neil has since tried to reframe this editorial as a call for businesses, governments, and the public to pay more attention to those people and groups, many have observed that such an argument exists nowhere in the article itself. Instead what we have is lines like academics (seemingly especially those in the humanities) are “asleep at the wheel.”

Instead of “asleep at the wheel” try “painfully awake on the side of the road at 5am in a part of town lyft and uber won’t come to, trying to flag down a taxi driver or hitchhike or any damn thing just please let me make this meeting so they can understand some part of what needs to be done.”* The former ultimately frames the humanities’ and liberal arts’ lack of currency and access as “well why aren’t you all speaking up more.” The latter gets more to the heart of “I’m sorry we don’t fund your departments or engage with your research or damn near ever heed your recommendations that must be so annoying for you oh my gosh.”

But Dr O’Neil is not the only one to write or say something along these lines—that there is somehow no one, or should be someone out here doing the work of investigating algorithmic bias, or infrastructure/engineering ethics, or any number of other things that people in philosophy of technology and STS are definitely already out here talking about. So I figured this would be, at the least, a good opportunity to share with you something discussing the relationship between science and technology, STS practitioners’ engagement with the public, and the public’s engagement of technoscience. Part 1 of who knows how many.

[Cover of the journal Techné: Research in Philosophy and Technology]

The relationship between technology and science is one in which each intersects with, flows into, shapes, and affects the other. Not only this, but both science and technology shape and are shaped by the culture in which they arise and take part. Viewed through the lens of the readings we’ll discuss it becomes clear that many scientists and investigators at one time desired a clear-cut relationship between science and technology in which one flows from the other, with the properties of the subcategory being fully determined by those of the framing category, and sociocultural concerns play no part.

Many investigators still want this clarity and certainty, but in the time since sociologists, philosophers, historians, and other investigators from the humanities and so called soft sciences began looking at the history and contexts of the methods of science and technology, it has become clear that these latter activities do not work in an even and easily rendered way. When we look at the work of Sergio Sismondo, Trevor J. Pinch and Wiebe E. Bijker, Madeline Akrich, and Langdon Winner, we can see that the social dimensions and intersections of science, culture, technology, and politics are and always have been crucially entwined.

In Winner’s seminal “Do Artifacts Have Politics?”(1980), we can see what counts as a major step forward along the path toward a model which takes seriously the social construction of science and technology, and the way in which we go about embedding our values, beliefs, and politics into the systems we make. On page 127, Winner states,

The things we call “technologies” are ways of building order in our world… Consciously or not, deliberately or inadvertently, societies choose structures for technologies that influence how people are going to work, communicate, travel, consume, [etc.]… In the processes by which structuring decisions are made, different people … possess unequal degrees of power [and] levels of awareness.

By this, Winner means to say that everything we do in the construction of the culture of scientific discovery and technological development is modulated by the sociocultural considerations that get built into them, and those constructed things go on to influence the nature of society, in turn. As a corollary to this, we can see a frame in which the elements within the frame—including science and technology—will influence and modulate each other, in the process of generating and being generated by the sociopolitical frame. Science will be affected by the tools it uses to make its discoveries, and the tools we use will be modulated and refined as our understandings change.

Pinch and Bijker write very clearly about the multidirectional interactions of science, technology, and society in their 1987 piece, [The Social Construction of Technological Systems,] using the history of the bicycle as their object of study. Through their investigation of the messy history of bicycles, “safety bicycles,” inflated rubber tires, bicycle racing, and PR ad copy, Pinch and Bijker show that science and technology aren’t clearly distinguished anymore, if they ever were. They show how scientific studies of safety were less influential on bicycle construction and adoption than the social perception [of] the devices, meaning that politics and public perception play a larger role in what gets studied, created, and adopted than we used to admit.

They go on to highlight a kind of multidirectionality and interpretive flexibility, which they say we achieve by looking at the different social groups that intersect with the technology, and the ways in which they do so (pg. 34). When we do this, we will see that each component group is concerned with different problems and solutions, and that each innovation made to address these concerns alters the landscape of the problem space. How we define the problem dictates the methods we will use and the technology that we create to seek a solution to it.

[Black and white figures comparing the frames of a Whippet Spring Frame bicycle (left) and a Singer Xtraordinary bicycle (right), from “The Social Construction of Facts and Artifacts: Or How the Sociology of Science and the Sociology of Technology Might Benefit Each Other” by Trevor J. Binch and Wiebe E. Bijker, 1987]


Akrich’s 1997 “The De-Scription of Technical Objects” (published, perhaps unsurprisingly, in a volume coedited by Bijker), engages the moral valences of technological intervention, and the distance between intent in design and “on the ground” usage. In her investigation of how people in Burkina Faso, French Polynesia, and elsewhere make use of technology such as generators and light boxes, we again see a complex interplay between the development of a scientific or technological process and the public adoption of it. On page 221 Akrich notes, “…the conversion of sociotechnical facts into facts pure and simple depends on the ability to turn technical objects into black boxes. In other words, as they become indispensable, objects also have to efface themselves.” That is, in order for the public to accept the scientific or technological interventions, those interventions had to become an invisible part of the framework of the public’s lives. Only when the public no longer had to think about these interventions did they become paradoxically “seen,” understood, as “good” science and technology.

In Sismondo’s “Science and Technology Studies and an Engaged Program” (2008) he spends some time discussing the social constructivist position that we’ve begun laying out, above—the perspective that everything we do and all the results we obtain from the modality of “the sciences” are constructed in part by that mode. Again, this would mean that “constructed” would describe both the data we organize out of what we observe, and what we initially observe at all. From page 15, “Not only data but phenomena themselves are constructed in laboratories—laboratories are places of work, and what is found in them is not nature but rather the product of much human effort.”

But Sismondo also says that this is only one half of the picture, then going on to discuss the ways in which funding models, public participation, and regulatory concerns can and do alter the development and deployment of science and technology. On page 19 he discusses a model developed in Denmark in the 1980’s:

Experts and stakeholders have opportunities to present information to the panel, but the lay group has full control over its report. The consensus conference process has been deemed a success for its ability to democratize technical decision-making without obviously sacrificing clarity and rationality, and it has been extended to other parts of Europe, Japan, and the United States…

This all merely highlights the fact that, if the public is going to be engaged, then the public ought to be as clear and critical as possible in its understanding of the exchanges that give rise to the science and technology on which they are asked to comment.

The non-scientific general public’s understanding of the relationship between science and technology is often characterized much as I described at the beginning of this essay. That is, it is often said that the public sees the relationship as a clear and clean move from scientific discoveries or breakthroughs to a device or other application of those principles. However, this casting does not take into account the variety of things that the public will often call technology, such as the Internet, mobile phone applications, autonomous cars, and more.

While there are scientific principles at play within each of those technologies, it still seems a bit bizarre to cast them merely as “applied science.” They are not all devices or other single physical instantiations of that application, and even those that are singular are the applications of multiple sciences, and also concrete expressions of social functions. Those concretions have particular psychological impacts, and philosophical implications, which need to be understood by both their users and their designers. Every part affects every other part, and each of those parts is necessarily filtered through human perspectives.

The general public needs to understand that every technology humans create will necessarily carry within it the hallmarks of human bias. Regardless of whether there is an objective reality at which science points, the sociocultural and sociopolitical frameworks in which science gets done will influence what gets investigated. Those same sociocultural and sociopolitical frameworks will shape the tools and instruments and systems—the technology—used to do that science. What gets done will then become a part of the scientific and technological landscape to which society and politics will then have to react. In order for the public to understand this, we have to educate about the history of science, the nature of social scientific methods, and the impact of implicit bias.

My own understanding of the relationship between science and technology is as I have outlined: A messy, tangled, multivalent interaction in which each component influences and is influenced by every other component, in near simultaneity. This framework requires a willingness to engage multiple perspectives and disciplines, and to perhaps reframe the normative project of science and technology to one that appreciates and encourages a multiplicity of perspectives, and no single direction of influence between science, technology and society. Once people understand this—that science and technology generate each other while influencing and being influenced by society—we do the work of engaging them in a nuanced and mindful way, working together to prevent the most egregious depredations of technoscientific development, or at least to agilely respond to them, as they arise.

But to do this, researchers in the humanities need to be heeded. In order to be heeded, people need to know that we exist, and that we have been doing this work for a very, very long time. The named field of Philosophy of Technology has been around for 70 years, and it in large parta foregrounded the concerns taken up and explored by STS. Here are just a few names of people to look at in this extensive history: Martin Heidegger, Bruno Latour, Don Ihde, Ian Hacking, Joe Pitt, and more recently, Ashley Shew, Shannon Vallor, Robin Zebrowski, John P. Sullins, John Flowers, Matt Brown, Shannon Conley, Lee Vinsel, Jacques Ellul, Andrew Feenberg, Batya Friedman, Geoffrey C. Bowker and Susan Leigh Star, Rob Kling, Phil Agre, Lucy Suchman, Joanna Bryson, David Gunkel, so many others. Langdon Winner published “Do Artifacts Have Politics” 37 years ago. This episode of the You Are Not So Smart podcast, along with Shannon Vallor and Alistair Croll, has all of us talking about the public impact of the aforementioned.

What I’m saying is that many of us are trying to do the work, out here. Instead of pretending we don’t exist, try using large platforms (Like the NYT opinion page, and well read blogs) to highlight the very real work being attempted. I know for a fact the NYT has received submission articles about philosophy of tech and STS. Engage them. Discuss these topics in public, and know that there are many voices trying to grapple with and understand this world, and we have been, for a really damn long time.

So you see that we are still talking about learning and thinking in public. About how we go about getting people interested and engaged in the work of the technology that affects their lives. But there is a lot at the base of all this about what people think of as “science” or “expertise” and where they think that comes from, and what they think of those who engage in or have it. If we’re going to do this work, we have to be able to have conversations with people who not only don’t value what we do, but who think what we value is wrongheaded, or even evil. There is a lot going on in the world, right now, in regards to science and knowability. For instance, late last year there was a revelation about the widespread use of Dowsing by UK water firms (though if you ask anybody in the US, you’ll find it’s still in use, here, too).

And then this guy was trying to use systems of fluid dynamics and aeronautics to launch himself in a rocket to prove that the earth is flat and that science isn’t real. Yeah. And while there’s a much deeper conversation to be had here about whether the social construction of the category of “science” can be understood as distinct from a set of methodologies and formulae, but i really don’t think this guy is talking about having that conversation.

So let’s also think about the nature of how laboratory science is constructed, and what it can do for us.

In his 1983 “Give Me a Laboratory and I Will Move The World,” Bruno Latour makes the claim that labs have their own agency. What Latour is asserting, here, is that the forces which coalesce within the framework of a lab become active agents in their own right. They are not merely subject to the social and political forces that go into their creation, but they are now active participants in the framing and reframing of those forces. He believes that the nature of inscription—the combined processes of condensing, translating, and transmitting methods, findings, and pieces of various knowledges—is a large part of what gives the laboratory this power, and he highlights this when he says:

The strength gained in the laboratory is not mysterious. A few people much weaker than epidemics can become stronger if they change the scale of the two actors—making the microbes big, and the epizootic small—and others dominate the events through the inscription devices that make each of the steps readable. The change of scale entails an acceleration in the number of inscriptions you can get. …[In] a year Pasteur could multiply anthrax outbreaks. No wonder that he became stronger than veterinarians. For every statistic they had, he could mobilize ten of them. (pg. 163—164)

This process of inscription is crucial for Latour; not just for the sake of what the laboratory can do of its own volition, but also because it is the mechanism by which scientists may come to understand and translate the values and concerns of another, which is, for him, the utmost value of science. In rendering the smallest things such as microbes and diseases legible on a large scale, and making largescale patterns individually understandable and reproducible, the presupposed distinctions of “macro” and “micro” are shown to be illusory. Latour believes that it is only through laboratory engagement that we can come to fully understand the complexities of these relationships (pg. 149).

When Latour begins laying out his project, he says sociological methods can offer science the tools to more clearly translate human concerns into a format with which science can grapple. “He who is able to translate others’ interests into his own language carries the day.” (pg. 144). However, in the process of detailing what it is that Pasteurian laboratory scientists do in engaging the various stakeholders in farms, agriculture, and veterinary medicine, it seems that he is has only described half of the project. Rather than merely translating the interests of others into our own language, evidence suggests that we must also translate our interests back into the language of our interlocutor.

So perhaps we can recast Latour’s statement as, “whomsoever is able to translate others’ interests into their own language and is equally able to translate their own interests into the language of another, carries the day.” Thus we see that the work done in the lab should allow scientists and technicians to increase the public’s understanding both of what it is that technoscience actually does and why it does it, by presenting material that can speak to many sets of values.

Karin Knorr-Cetina’s assertion in her 1995 article “Laboratory Studies: The Cultural Approach to the Study of Science” is that laboratory is an “enhanced” environment. In many ways this follows directly from Latour’s conceptualization of labs. Knorr-Cetina says that the constructed nature of the lab ‘“improves upon” the natural order,’ because said natural order is, in itself, malleable, and capable of being understood and rendered in a multiplicity of ways (pg. 9). If laboratories are never engaging the objects they study “as they occur in nature,” this means that labs are always in the process of shaping what they study, in order to better study it (ibid). This framing of the engagement of laboratory science is clarified when she says:

Detailed description [such as that done in laboratories] deconstructs—not out of an interest in critique but because it cannot but observe the intricate labor that goes into the creation of a solid entity, the countless nonsolid ingredients from which it derives, the confusion and negotiation that often lie at its origin, and the continued necessity of stabilizing and congealing. Constructionist studies have revealed the ordinary working of things that are black-boxed as “objective” facts and “given” entities, and they have uncovered the mundane processes behind systems that appear monolithic, awe inspiring, inevitable. (pg. 12)

Thus, the laboratory is one place in which the irregularities and messiness of the “natural world” are ordered in such a ways as to be able to be studied at all. However, Knorr-Cetina clarifies that “nothing epistemically special” is happening, in a lab (pg. 16). That is, while a laboratory helps us to better recognize nonhuman agents (“actants”) and forces at play in the creation of science, this is merely a fact of construction; everything that a scientist does in a lab is open to scrutiny and capable of being understood. If this is the case, then the “enhancement” gained via the conditions of the laboratory environment is merely a change in degree, rather than a difference in kind, as Latour seems to assert.

[Stock photo image of hundreds of scallops and two scallop fishers on the deck of a boat in the St Brieuc Bay.]

[Stock photo image of hundreds of scallops and two scallop fishers on the deck of a boat in the St Brieuc Bay.]


In addition to the above explorations of what the field of laboratory studies has to offer, we can also look at the works of Michel Callon and Sharon Traweek. Though primarily concerned with describing the network of actors and their concerns in St Brieuc Bay scallop-fishing and -farming industries, Callon’s investigation can be seen as example of Latour’s principle of bringing the laboratory out in the world, both in terms of the subjects of Callon’s investigation and the methods of those subjects. While Callon himself might disagree with this characterization, we can trace the process of selection and enframing of subjects and the investigation of their translation procedures, which we can see on page 20, when he says,

We know that the ingredients of controversies are a mixture of considerations concerning both Society and Nature. For this reason we require the observer to use a single repertoire when they are described. The vocabulary chosen for these descriptions and explanations can be left to the discretion of the observer. He cannot simply repeat the analysis suggested by the actors he is studying. (Callon, 1984)

In this way, we can better understand how laboratory techniques have become a component even of the study and description of laboratories.

When we look at a work like Sharon Traweek’s Beamtimes and Lifetimes, we can see that she finds value in bringing ethnographic methodologies into laboratory studies, and perhaps even laboratory settings. She discusses the history of the laboratory’s influence, arcing back to WWI and WWII, where scientists were tasked with coming up with more and better weapons, with their successes being used to push an ever-escalating arms race. As this process continued, the characteristics of what made a “good lab scientist” were defined and then continually reinforced, as being “someone who did science like those people over there.” In the building of the laboratory community, certain traits and behaviours become seen as ideal, those who do not match those traits and expectations are regarded as necessarily doing inferior work. She says,

The field worker’s goal, then, is to find out what the community takes to be knowledge, sensible action, and morality, as well as how its members account for unpredictable information, disturbing actions, and troubling motives. In my fieldwork I wanted to discover the physicists’ “common sense” world view, what everyone in the community knows, and what every newcomer needs to learn in order to act in a sensible way, in order to be taken seriously. (pg. 8)

And this is also the danger of focusing too closely on the laboratory: the potential for myopia, for thinking that the best or perhaps even only way to study the work of scientists is to render that work through the lens of the lab.

While the lab is a fantastic tool and studies of it provide great insight, we must remember that we can learn a great deal about science and technology via contexts other than that of the lab. While Latour argues that laboratory science actually destabilizes the inside-the-lab/outside-the-lab distinction by showing that the tools and methods of the lab can be brought anywhere out into the world, it can be said that the distinction is reinstantiated by our focusing on laboratories as the sole path to understand scientists. Much the same can be said for the insistence that systems engineers are the sole best examples of how to engage technological development. Thinking that labs are the only resource we have means that we will miss the behavior of researchers at conferences, retreats, in journal articles, and other places where the norms of the scientific community are inscribed and reinforced. It might not be the case that scientists understand themselves as creating community rules, in these fora, but this does not necessarily mean that they are not doing so.

The kinds of understandings a group has about themselves will not always align with what observations and descriptions might be gleaned from another’s investigation of that group, but this doesn’t mean that one of those has to be “right” or “true” while the other is “wrong” and “false.” The interest in studying a discipline should come not from that group’s “power” to “correctly” describe the world, but from understanding more about what it is about whatever group is under investigation that makes it itself. Rather than seeking a single correct perspective, we should instead embrace the idea that a multiplicity of perspectives might all be useful and beneficial, and then ask “To What End?”

We’re talking about Values, here. We’re talking about the question of why whatever it is that matters to you, matters to you. And how you can understand that other people have different values from each other, and we can all learn to talk about what we care about in a way that helps us understand each other. That’s not neutral, though. Even that can be turned against us, when it’s done in bad faith. And we have to understand why someone would want to do that, too.

[Direct Link to Mp3]

Above is the (heavily edited) audio of my final talk for the SRI Technology and Consciousness Workshop Series. The names and voices of other participants have been removed in accordance with the Chatham House Rule.

Below you’ll find the slide deck for my presentation, and below the cut you’ll find the Outline and my notes. For now, this will have to stand in for a transcript, but if you’ve been following the Technoccult Newsletter or the Patreon, then some of this will be strikingly familiar.

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This summer I participated in SRI International’s Technology and Consciousness Workshop Series. The meetings were held under the auspices of the Chatham House Rule, which means that there are many things I can’t tell you about them, such as who else was there, or what they said in the context of the meetings; however I can tell you what I talked about. In light of this recent piece in The Boston Globe and the ongoing developments in the David Slater/PETA/Naruto case, I figured that now was a good time to do so.

I presented three times—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. This is my outline and notes for the first of those talks.

I. Overview
In a 2013 aeon Article Michael Hanlon said he didn’t think we’d ever solve “The Hard Problem,” and there’s been some skepticism about it, elsewhere. I’ll just say that said question seems to completely miss a possibly central point. Something like consciousness is, and what it is is different for each thing that displays anything like what we think it might be. If we manage to generate at least one mind that is similar enough to what humans experience as “conscious” that we may communicate with it, what will we owe it and what would it be able to ask from us? How might our interactions be affected by the fact that its mind (or their minds) will be radically different from ours? What will it be able to know that we cannot, and what will we have to learn from it?

So I’m going to be talking today about intersectionality, embodiment, extended minds, epistemic valuation, phenomenological experience, and how all of these things come together to form the bases for our moral behavior and social interactions. To do that, I’m first going to need ask you some questions:

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