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    Michael Bernstein Calls AI Simulation What-If Machine

    Stanford HCI professor frames behavioral simulation as what-if machine in post.

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    6 Sources, 28d ago, first seen 28d ago

    TLDR

    Michael Bernstein, a Stanford professor of computer science focused on HCI, social computing, and human-centered AI, stated that he describes AI behavioral simulation as a what-if machine. He added that he wrote about the concept and how the What-If Machine works on the @simile_ai account. The statement appears in a public post quoting his description of the approach to generative simulation.

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    33.5K

    6 Sources, first seen 28d ago

    Combined views

    33.5K

    6 Sources, first seen 28d ago

    241 likes
    241 likes
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    9 comments
    80 saves
    20 reposts

    Sentiment

    Positive——Negative

    Summary

    Not enough discussion yet.

    No sentiment analysis available yet.

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    6 Sources

    @msbernstI describe AI behavioral simulation as a “what-if” machine. I wrote about what a What-If Machine is, and how it works, at @simile_ai:
    @percyliangThe "What-If Machine" is a vivid articulation of what Simile is building. It's not just about forecasting the future passively. It's about understanding how active interventions on the world change its course. It's the classic difference between causation and correlation.
    @wsisaacVery excited to read this!
    @joon_s_pkWhat we’ve learned is that we’re rarely interested in predicting the future for its own sake. We’re interested in counterfactuals, the “what-ifs”that teach us how we might shape it. A thoughtful summary from @msbernst of how we think about this problem at @simile_ai.

    6 Sources

    @msbernstI describe AI behavioral simulation as a “what-if” machine. I wrote about what a What-If Machine is, and how it works, at @simile_ai:
    @percyliangThe "What-If Machine" is a vivid articulation of what Simile is building. It's not just about forecasting the future passively. It's about understanding how active interventions on the world change its course. It's the classic difference between causation and correlation.
    @wsisaacVery excited to read this!
    @joon_s_pkWhat we’ve learned is that we’re rarely interested in predicting the future for its own sake. We’re interested in counterfactuals, the “what-ifs”that teach us how we might shape it. A thoughtful summary from @msbernst of how we think about this problem at @simile_ai.