@davpoole.bsky.social

AI Educator, researcher, author. Professor Emeritus in CS at University of British Columbia. One of the founders of Statistical Relational AI. https://www.cs.ubc.ca/~poole/

AI is like plastic — a lot of people hate it because it often comes across as fake and tacky, but it’s flexible and it’s cheap and there’s so many things that would be impossible or impractical without it. And yes, a lot of AI will be junk. Just like everything else. (cf Sturgeon’s Law.)

The "Real World" is unfair. It is biased. And when it comes to estimating treatment effects, the "Big Data" can't fix a bias that's baked into how the data are collected (I would say "design", but there is usually no design involved). So pardon me if I prefer boring old "Useful Evidence".

I’m sorry, this might be a great investigation, but “as it was never intended” is obscene. This is precisely how many people specifically and repeatedly told us — warned us — it would be used.

The Washington post
Breaking News
Post Exclusive
8 minutes ago
Police use facial recognition as it was never intended: As a shortcut to finding and arresting suspects without further evidence
Confident in unproven facial recognition technology, sometimes investigators skip steps, and at least eight Americans have been wrongfully arrested, a Washington Post investigation found.

I genuinely cannot believe Google is now showing Gemini-generated medical snippets including *drug summaries and medical advice* to treatserious health conditions. I checked. It does. With barely a tiny disclaimer about GenAI. How can a (formerly?) trusted company be so incredibly reckless?

Autonomous vehicles accelerate the trend begun by cars of isolating travellers from their neighbourhoods, reducing neighbors to mere obstacles our sensors try to avoid, and hence dissolving the social bonds that hold together communities

Google AI reporting “no drug interactions” for two drugs that definitely have drug interactions. When can we collectively decide the AI experiment is over?

Two things I learned from #neurips2024 1) transcriptions are still terrible. The simultaneous transcriptions of the talks didn't take into account the vocabulary of the papers being presented. It's probably the fault of one-size-fits-all language models. There were slides with the vocabulary... 2/

We are pleased to announce the latest version of AIPython.org: open-source, runnable pseudocode (in Python) for all your favorite AI algorithms, including search, CSPs, logic, planning, supervised machine learning, neural network, graphical models, unsupervised learning, causality, /2

AIPython

aipython.org

Human minds, intelligences and states of consciousness are beautifully diverse—I just don't buy that the right approach for AI is "all you need is more compute", pretending AI has an objective view from nowhere, and being owned by a small number of homogenously white-bread tech firms