Tagalgorithmic systems

Cultivating Technomoral Interrelations: A Review of Shannon Vallor’s TECHNOLOGY AND THE VIRTUES

[“Cultivating Technomoral Interrelations: A Review of Shannon Vallor’s Technology and the Virtues” was originally published in Social Epistemology Review and Reply Collective 7, no. 2 (2018): 64-69.
The pdf of the article gives specific page references. Shortlink: https://wp.me/p1Bfg0-3US]

[Image of an eye in a light-skinned face; the iris and pupil have been replaced with a green neutral-faced emoji; by Stu Jones via CJ Sorg on Flickr / Creative Commons]

Shannon Vallor’s most recent book, Technology and the Virtues: A Philosophical Guide to a Future Worth Wanting takes a look at what she calls the “Acute Technosocial Opacity” of the 21st century, a state in which technological, societal, political, and human-definitional changes occur at such a rapid-yet-shallow pace that they block our ability to conceptualize and understand them.[1]

Vallor is one of the most publicly engaged technological ethicists of the past several years, and much of her work’s weight comes from its direct engagement with philosophy—both philosophy of technology and various virtue ethical traditions—and the community of technological development and innovation that is Silicon Valley. It’s from this immersive perspective that Vallor begins her work in Virtues.

Vallor contends that we need a new way of understanding the projects of human flourishing and seeking the good life, and understanding which can help us reexamine how we make and participate through and with the technoscientific innovations of our time. The project of this book, then, is to provide the tools to create this new understanding, tools which Vallor believes can be found in an examination and synthesis of the world’s three leading Virtue Ethical Traditions: Aristotelian ethics, Confucian Ethics, and Buddhism.

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A Discussion on Daoism and Machine Consciousness

Over at AFutureWorthThinkingAbout, there is the audio and text for a talk for the  about how nonwestern philosophies like Buddhism, Hinduism, and Daoism can help mitigate various kinds of bias in machine minds and increase compassion by allowing programmers and designers to think from within a non-zero-sum matrix of win conditions for all living beings, meaning engaging multiple tokens and types of minds, outside of the assumed human “default” of straight, white, cis, ablebodied, neurotypical male:

My starting positions, here, are that, 1) in order to do the work correctly, we literally must refrain from resting in abstraction, where, by definition, the kinds of models that don’t seek to actually engage with the people in question from within their own contexts, before deciding to do something “for someone’s own good,” represent egregious failure states. That is, we have to try to understand each other well enough to perform mutually modeled interfaces of what you’d have done unto you and what they’d have you do unto them.” I know it doesn’t have the same snap as “do unto others,” but it’s the only way we’ll make it through.

[An image of a traditional Yin-Yang carved in a silver ring]

2) There are multiple types of consciousness, even within the framework of the human spectrum, and that the expression of or search for any one type is in no way meant to discount, demean, or erase any of the others. In fact, it is the case that we will need to seek to recognize and learn to communicate with as many types of consciousness as may exist, in order to survive and thrive in any meaningful way. Again, not doing so represents an egregious failure condition. With that in mind, I use “machine consciousness” to mean a machine with the capability of modelling a sense of interiority and selfness similar enough to what we know of biological consciousnesses to communicate it with us, not just a generalized computational functionalist representation, as in “AGI.”

For the sake of this, as I’ve related elsewhere, I (perhaps somewhat paradoxically) think the term “artificial intelligence” is problematic. Anything that does the things we want machine minds to do is genuinely intelligent, not “artificially” so, where we use “artificial” to mean “fake,” or “contrived.” To be clear, I’m specifically problematizing the “natural/technological” divide that gives us “art vs artifice,” for reasons previously outlined here.

The  overarching project of training a machine learning program and eventual AI will require engagement with religious texts (a very preliminary take on this has been taken up by Rose Eveleth at the Flash Forward Podcast), but also a boarder engagement with discernment and decision-making. Even beginning to program or code for this will require us to think very differently about the project than has thus far been in evidence.

Read or listen to the rest of A Discussion on Daoism and Machine Consciousness at A Future Worth Thinking About

A Conversation With Klint Finley About AI and Ethics

I spoke with Klint Finley, known to this parish, 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, yesterday, 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.

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 increasingly willing to have this discussion, at all.

To see my comments and read the rest of the article, click through, above.

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