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    Researchers Launch AI Observatory Tracking Real Usage

    Public platform draws from consented conversations to measure actual AI assistant use.

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    22 Sources, 43d ago, first seen 43d ago

    TLDR

    Academics from MIT, Stanford and other institutions announced the launch of the AI Observatory. The platform aggregates consented conversations to create an independent public measure of how people interact with AI assistants. Posts from project leads including Shayne Longpre and Anka Reuel highlight its 145-feature taxonomy and note coverage on the front page of the Washington Post along with a long piece in MIT Technology Review. Multiple researchers described the effort as filling gaps left by coarse proprietary reports from frontier labs.

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    22 Sources, first seen 43d ago

    Combined views

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    22 Sources, first seen 43d ago

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    22 Sources

    @sanmikoyejohttps://ai-observatory.org is live! An independent, public measure of how people actually use AI, built from 24,521 consented conversations across 52 models. Led by @anka_reuel and @ShayneRedford, with a great team. Front page of WaPo and a long piece in MIT Tech Review today.
    @ShayneRedford7/ Huge thanks to my co-leads @AnkaReuel + @zoeykii and our incredible collaborators @thecatfangs @megan_richards_ @zhipinghci @chuanyang_jin Jenn Mickel, Cedric Whitney, @ahmetustun89 @niloofar_mire @OjewaleV @ArielNLee @alex_pentland @tianshi_li @yuntiandeng Mykel Kochenderfer @sarahookr and @sanmikoyejo. And thank you to @nitashatiku @washingtonpost and @eileenguo @techreview for covering the work. Their pieces are well worth reading. https://www.washingtonpost.com/business/2026/08/18/ai-observatory-tries-reveal-how-people-really-use-technology/ https://www.technologyreview.com/2026/08/18/1142226/how-people-use-ai/
    @thecatfangsDo some AI models refuse more user requests than others? Are people using AI to generate illicit content more or less over time? And which models do people go to for coding vs role-play? Unfortunately, existing reports of AI use from frontier labs are coarse and proprietary that do not help us understand the impacts and natural uses of AI. This prompted us to create a public AI observatory https://www.ai-observatory.org/
    @zoeykiiWe tried to audit how people are actually using AI assistants beyond what company reports show. Check it out here! 📍https://www.ai-observatory.org
    @yuntiandengRT @thecatfangs: Do some AI models refuse more user requests than others? Are people using AI to generate illicit content more or less over…
    @sebgehrReally nice initiative and interesting findings. Probably one of the highest impact research problems people interested in economics of AI and policy can work one.
    @tianshi_liGlad this is finally out! Understanding how people actually use AI is such a challenging yet important problem and it takes efforts to craft the work to achieve scale, rigor, and care to detail at the same time. Check out more 👇
    @niloofar_mireRT @tianshi_li: Glad this is finally out! Understanding how people actually use AI is such a challenging yet important problem and it takes…
    @megan_richards_AI is everywhere, but the data we have on how people are using it remains extremely limited. After nearly 2 years of work, we're excited to release the AI Observatory, a public platform for measuring how people are using AI assistants. We label nearly ~100K conversational turns with 145 detailed features, analyzing conversations with over 50 different model versions that occurred between 2023 and 2026. We learned a ton in the process, and are trying to make our learnings as accessible and usable as possible. We're especially grateful for coverage in @washingtonpost and @techreview this week (article links below).
    @Dr_AtoosaThis is an awesome effort ❣️

    22 Sources

    @sanmikoyejohttps://ai-observatory.org is live! An independent, public measure of how people actually use AI, built from 24,521 consented conversations across 52 models. Led by @anka_reuel and @ShayneRedford, with a great team. Front page of WaPo and a long piece in MIT Tech Review today.
    @ShayneRedford7/ Huge thanks to my co-leads @AnkaReuel + @zoeykii and our incredible collaborators @thecatfangs @megan_richards_ @zhipinghci @chuanyang_jin Jenn Mickel, Cedric Whitney, @ahmetustun89 @niloofar_mire @OjewaleV @ArielNLee @alex_pentland @tianshi_li @yuntiandeng Mykel Kochenderfer @sarahookr and @sanmikoyejo. And thank you to @nitashatiku @washingtonpost and @eileenguo @techreview for covering the work. Their pieces are well worth reading. https://www.washingtonpost.com/business/2026/08/18/ai-observatory-tries-reveal-how-people-really-use-technology/ https://www.technologyreview.com/2026/08/18/1142226/how-people-use-ai/
    @thecatfangsDo some AI models refuse more user requests than others? Are people using AI to generate illicit content more or less over time? And which models do people go to for coding vs role-play? Unfortunately, existing reports of AI use from frontier labs are coarse and proprietary that do not help us understand the impacts and natural uses of AI. This prompted us to create a public AI observatory https://www.ai-observatory.org/
    @zoeykiiWe tried to audit how people are actually using AI assistants beyond what company reports show. Check it out here! 📍https://www.ai-observatory.org
    @yuntiandengRT @thecatfangs: Do some AI models refuse more user requests than others? Are people using AI to generate illicit content more or less over…
    @sebgehrReally nice initiative and interesting findings. Probably one of the highest impact research problems people interested in economics of AI and policy can work one.
    @tianshi_liGlad this is finally out! Understanding how people actually use AI is such a challenging yet important problem and it takes efforts to craft the work to achieve scale, rigor, and care to detail at the same time. Check out more 👇
    @niloofar_mireRT @tianshi_li: Glad this is finally out! Understanding how people actually use AI is such a challenging yet important problem and it takes…
    @megan_richards_AI is everywhere, but the data we have on how people are using it remains extremely limited. After nearly 2 years of work, we're excited to release the AI Observatory, a public platform for measuring how people are using AI assistants. We label nearly ~100K conversational turns with 145 detailed features, analyzing conversations with over 50 different model versions that occurred between 2023 and 2026. We learned a ton in the process, and are trying to make our learnings as accessible and usable as possible. We're especially grateful for coverage in @washingtonpost and @techreview this week (article links below).
    @Dr_AtoosaThis is an awesome effort ❣️