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Appendix A: An Imagined and Incomplete Conversation about “Consciousness” and “AI,” Across Time

Every so often, I think about the fact of one of the best things my advisor and committee members let me write and include in my actual doctoral dissertation, and I smile a bit, and since I keep wanting to share it out into the world, I figured I should put it somewhere more accessible.

So with all of that said, we now rejoin An Imagined and Incomplete Conversation about “Consciousness” and “AI,” Across Time, already (still, seemingly unendingly) in progress:

René Descartes (1637):
The physical and the mental have nothing to do with each other. Mind/soul is the only real part of a person.

Norbert Wiener (1948):
I don’t know about that “only real part” business, but the mind is absolutely the seat of the command and control architecture of information and the ability to reflexively reverse entropy based on context, and input/output feedback loops.

Alan Turing (1952):
Huh. I wonder if what computing machines do can reasonably be considered thinking?

Wiener:
I dunno about “thinking,” but if you mean “pockets of decreasing entropy in a framework in which the larger mass of entropy tends to increase,” then oh for sure, dude.

John Von Neumann (1958):
Wow things sure are changing fast in science and technology; we should maybe slow down and think about this before that change hits a point beyond our ability to meaningfully direct and shape it— a singularity, if you will.

Clynes & Klines (1960):
You know, it’s funny you should mention how fast things are changing because one day we’re gonna be able to have automatic tech in our bodies that lets us pump ourselves full of chemicals to deal with the rigors of space; btw, have we told you about this new thing we’re working on called “antidepressants?”

Gordon Moore (1965):
Right now an integrated circuit has 64 transistors, and they keep getting smaller, so if things keep going the way they’re going, in ten years they’ll have 65 THOUSAND. :-O

Donna Haraway (1991):
We’re all already cyborgs bound up in assemblages of the social, biological, and techonological, in relational reinforcing systems with each other. Also do you like dogs?

Ray Kurzweil (1999):
Holy Shit, did you hear that?! Because of the pace of technological change, we’re going to have a singularity where digital electronics will be indistinguishable from the very fabric of reality! They’ll be part of our bodies! Our minds will be digitally uploaded immortal cyborg AI Gods!

Tech Bros:
Wow, so true, dude; that makes a lot of sense when you think about it; I mean maybe not “Gods” so much as “artificial super intelligences,” but yeah.

90’s TechnoPagans:
I mean… Yeah? It’s all just a recapitulation of The Art in multiple technoscientific forms across time. I mean (*takes another hit of salvia*) if you think about the timeless nature of multidimensional spiritual architectures, we’re already—

DARPA:
Wait, did that guy just say something about “Uploading” and “Cyborg/AI Gods?” We got anybody working on that?? Well GET TO IT!

Disabled People, Trans Folx, BIPOC Populations, Women:
Wait, so our prosthetics, medications, and relational reciprocal entanglements with technosocial systems of this world in order to survive makes us cyborgs?! :-O

[Simultaneously:]

Kurzweil/90’s TechnoPagans/Tech Bros/DARPA:
Not like that.
Wiener/Clynes & Kline:
Yes, exactly.

Haraway:
I mean it’s really interesting to consider, right?

Tech Bros:
Actually, if you think about the bidirectional nature of time, and the likelihood of simulationism, it’s almost certain that there’s already an Artificial Super Intelligence, and it HATES YOU; you should probably try to build it/never think about it, just in case.

90’s TechnoPagans:
…That’s what we JUST SAID.

Philosophers of Religion (To Each Other):
…Did they just Pascal’s Wager Anselm’s Ontological Argument, but computers?

Timnit Gebru and other “AI” Ethicists:
Hey, y’all? There’s a LOT of really messed up stuff in these models you started building.

Disabled People, Trans Folx, BIPOC Populations, Women:
Right?

Anthony Levandowski:
I’m gonna make an AI god right now! And a CHURCH!

The General Public:
Wait, do you people actually believe this?

Microsoft/Google/IBM/Facebook:
…Which answer will make you give us more money?

Timnit Gebru and other “AI” Ethicists:
…We’re pretty sure there might be some problems with the design architectures, too…

Some STS Theorists:
Honestly this is all a little eugenics-y— like, both the technoscientific and the religious bits; have you all sought out any marginalized people who work on any of this stuff? Like, at all??

Disabled People, Trans Folx, BIPOC Populations, Women:
Hahahahah! …Oh you’re serious?

Anthony Levandowski:
Wait, no, nevermind about the church.

Some “AI” Engineers:
I think the things we’re working on might be conscious, or even have souls.

“AI” Ethicists/Some STS Theorists:
Anybody? These prejudices???

Wiener/Tech Bros/DARPA/Microsoft/Google/IBM/Facebook:
“Souls?” Pfffft. Look at these whackjobs, over here. “Souls.” We’re talking about the technological singularity, mind uploading into an eternal digital universal superstructure, and the inevitability of timeless artificial super intelligences; who said anything about “Souls?”

René Descartes/90’s TechnoPagans/Philosophers of Religion/Some STS Theorists/Some “AI” Engineers:

[Scene]


Read more of this kind of thing at:
Williams, Damien Patrick. Belief, Values, Bias, and Agency: Development of and Entanglement with “Artificial Intelligence.” PhD diss., Virginia Tech, 2022. https://vtechworks.lib.vt.edu/handle/10919/111528.

So with the job of White House Office of Science and Technology Policy director having gone to Dr. Arati Prabhakar back in October, rather than Dr. Alondra Nelson, and the release of the “Blueprint for an AI Bill of Rights” (henceforth “BfaAIBoR” or “blueprint”) a few weeks after that, I am both very interested also pretty worried to see what direction research into “artificial intelligence” is actually going to take from here.

To be clear, my fundamental problem with the “Blueprint for an AI bill of rights” is that while it pays pretty fine lip-service to the ideas of  community-led oversight, transparency, and abolition of and abstaining from developing certain tools, it begins with, and repeats throughout, the idea that sometimes law enforcement, the military, and the intelligence community might need to just… ignore these principles. Additionally, Dr. Prabhakar was director of DARPA for roughly five years, between 2012 and 2015, and considering what I know for a fact got funded within that window? Yeah.

To put a finer point on it, 14 out of 16 uses of the phrase “law enforcement” and 10 out of 11 uses of “national security” in this blueprint are in direct reference to why those entities’ or concept structures’ needs might have to supersede the recommendations of the BfaAIBoR itself. The blueprint also doesn’t mention the depredations of extant military “AI” at all. Instead, it points to the idea that the Department Of Defense (DoD) “has adopted [AI] Ethical Principles, and tenets for Responsible Artificial Intelligence specifically tailored to its [national security and defense] activities.” And so with all of that being the case, there are several current “AI” projects in the pipe which a blueprint like this wouldn’t cover, even if it ever became policy, and frankly that just fundamentally undercuts Much of the real good a project like this could do.

For instance, at present, the DoD’s ethical frames are entirely about transparency, explainability, and some lipservice around equitability and “deliberate steps to minimize unintended bias in Al …” To understand a bit more of what I mean by this, here’s the DoD’s “Responsible Artificial Intelligence Strategy…” pdf (which is not natively searchable and I had to OCR myself, so heads-up); and here’s the Office of National Intelligence’s “ethical principles” for building AI. Note that not once do they consider the moral status of the biases and values they have intentionally baked into their systems.

An "Explainable AI" diagram from DARPA, showing two flowcharts, one on top of the other. The top one is labeled "today" and has the top level condition "task" branching to both a confused looking human user and state called "learned function" which is determined by a previous state labeled "machine learning process" which is determined by a state labeled "training data." "Learned Function" feeds "Decision or Recommendation" to the human user, who has several questions about the model's beaviour, such as "why did you do that?" and "when can i trust you?" The bottom one is labeled "XAI" and has the top level condition "task" branching to both a happy and confident looking human user and state called "explainable model/explanation interface" which is determined by a previous state labeled "new machine learning process" which is determined by a state labeled "training data." "explainable model/explanation interface" feeds choices to the human user, who can feed responses BACK to the system, and who has several confident statements about the model's beaviour, such as "I understand why" and "I know when to trust you."

An “Explainable AI” diagram from DARPA

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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.]

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