My second talk for the SRI International Technology and Consciousness Workshop Series was 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. I don’t have a transcript, yet, and I’ll update it when I make one. But for now, here are my slides and some thoughts.
(The translations of the Daoist texts referenced in the presentation are available online: The Burton Watson translation of the Chuang Tzu and the Robert G. Hendricks translation of the Tao Te Ching.)
A zero-sum system is one in which there are finite resources, but more than that, it is one in which what one side gains, another loses. So by “A non-zero-sum matrix of win conditions” I mean a combination of all of our needs and wants and resources in such a way that everyone wins. Basically, we’re talking here about trying to figure out how to program a machine consciousness that’s a master of wu-wei and limitless compassion, or metta.
The whole week was about phenomenology and religion and magic and AI and it helped me think through some problems, like how even the framing of exercises like asking Buddhist monks to talk about the Trolley Problem will miss so much that the results are meaningless. That is, the trolley problem cases tend to assume from the outset that someone on the tracks has to die, and so they don’t take into account that an entire other mode of reasoning about sacrifice and death and “acceptable losses” would have someone throw themselves under the wheels or jam their body into the gears to try to stop it before it got that far. Again: There are entire categories of nonwestern reasoning that don’t accept zero-sum thought as anything but lazy, and which search for ways by which everyone can win, so we’ll need to learn to program for contradiction not just as a tolerated state but as an underlying component. These systems assume infinitude and non-zero-sum matrices where every being involved can win.