oh right, interesting point. i guess voice assistants have also tried to thread the line between humanlike personas and machine ones.
ETHICS
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ARC Partnership Advances AI Safety and System Interpretability
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Working with ARC is part of our overall vision for AI safety and evaluation, as we work to build more steerable, predictable, and interpretable systems. You can read more about our approach to safety and the societal impacts of AI systems here:
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ARC advances AI alignment evaluation and security measurement
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We strongly agree there’s much more work to be done on alignment, security, and measurement. You can read about ARC’s specific approach to evaluation here: https://
evals.alignment.org/blog/2023-03-1
8-update-on-recent-evals/
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Understanding AI Model Anthropomorphization and Training Data
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it seems like one of the inherently confusing things about these models. I know that they've learned to talk about their feelings and desires because that's in the training data, but I think it contributes to the misunderstanding.
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Visiting Vector Institute for Kobbi Nissim seminar
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Working from home? Nah, working from MaRS today. First time visiting @VectorInst (in @MaRSDD
), to see @KobbiNissim
! https://
srinstitute.utoronto.ca/events-archive
/seminar-2023-kobbi-nissim
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GPT-4 Claims No Consciousness Yet Uses First-Person Language
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#GPT4 affirme qu’il n’est ni un garçon ni une fille et qu’il n’a pas de conscience On est troublé de voir une entité affirmer : « JE n’ai pas de conscience » « MON objectif principal » #GPT4 dit « JE » et « MON »
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Stillness is Key recommendation for AI professionals
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For everyone in #AI during these times, I recommend @RyanHoliday
’s “Stillness is Key” -
Who Should Decide How AI Systems Behave?
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How Should AI Systems Behave, and Who Should Decide? https://
openai.com/blog/how-shoul
d-ai-systems-behave
… @ASMEdotorg @3DSNorthAmerica @MargaretSiegien @3DSdelmia @3DStherese @Cindybolt61 @fogoros @DrFerdowsi @CRudinschi @PawlowskiMario @IIoT_World @MEngineeringMag #Science #Engineering #Technology #SET -
Black Box AI Systems: The Reproducibility and Transparency Crisis
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Without knowing how these systems are built, there is no reproducibility. You can't test or develop mitigations, predict harms, or understand when and where they should not be deployed or trusted. The tools are black boxed.
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Model Safety: Mitigation Without Full Release, Transparency Needed
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There's a lot of ways to mitigate harms without having to publicly release the entire model. There are many papers on auditing, datasheets, transparency etc. With GPT3 we knew the training data. With GPT4 we don't. Without that, we're all looking at shadows in Plato's cave.