ethics

Artificial intelligence, values, and alignment

I presented this paper in Bang Liu’s research group meeting in two installments on 2023-02-20 and 2023-02-27, and also in Irina Rish’s scaling and alignment course (IFT6760A) on 2023-03-07. You can view the slides I used here.The thumbnail for this post was generated with stable diffusion! See the alt text for details. Behind each vision for ethically-aligned AI sits a deeper question. How are we to decide which principles or objectives to encode in AI—and who has the right to make these decisions—given that we live in a pluralistic world that is full of competing conceptions of value?
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Unsolved problems in ML safety

This was a paper we presented about in Irina Rish’s neural scaling laws course (IFT6760A) in winter 2023. You can view the slides we used here, and the recording here (or my backup here).

ethics drift within bubbles

Here are some snippets from a Lex Fridman interview with John Abramson, outspoken critic of Big Pharma. Lex: Are people corrupt? Are people malevolent? Are people ignorant that work at the low level and at the high level, at Pfizer for example? How is this possible? I believe that most people are good, and I actually believe if you join Big Pharma your life trajectory often involves dreaming, wanting, and enjoying helping people.
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Tools and weapons: the promise and peril of the digital age

I started taking notes later in the book. There were lots of good insights in the first half. Sorry! broadband access permalink Getting the internet to rural communities is a big deal for the rural economy. Just like electricity, it’s something that needs government support because there isn’t the economic incentive for ISPs to reach some of these locations. ethical AI permalink The focus on AI now is not just a fad, but a convergence of several trends that have made AI the next logical step: the increased computational resources, flexible access to compute through the cloud, etc.
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Weapons of math destruction: how big data increases inequality and threatens democracy

In fact, I saw all kinds of parallels between finance and Big Data. Both industries gobble up the same pool of talent, much of it from elite universities like MIT, Princeton, or Stanford. These new hires are ravenous for success and have been focused on external metrics–like SAT scores and college admissions–their entire lives. Whether in finance or tech, the message they’ve received is that they will be rich, that they will run the world.
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