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Dan Liebling

danyoel@hci.social

<p>Staff Engineer, Science AI @ Google. he/him <br /><a href="https://bsky.app/profile/liebling.org" target="_blank" rel="nofollow noopener" translate="no"><span class="invisible">https://</span><span class="">bsky.app/profile/liebling.org</span><span class="invisible"></span></a>
Caltech, University of Washington, Microsoft Research alum
Aspiring cello player 🎻 Learning as adult = less plasticity but more self-motivation and better chunking.</p>

Posts

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    @andresmh @drewww this falls under the category of “people who bought the software don’t actually use it.”

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    Good example of AI assistance in writing that retains the author&amp;#39;s agency: SciCapenter &amp;quot;generates a comprehensive checklist to assess caption quality across multiple critical aspects, such as helpfulness, OCR mention, key takeaways, and visual properties reference.&amp;quot; #chi2024 https://dl.acm.org/doi/10.1145/3613905.3650738

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    you can tell a paper summary is LLM-generated because it ends with superfluous junk like &amp;quot;[Result] is introduced, highlighting its promising potential for future research and the dataset&amp;#39;s impact on revolutionizing [field].&amp;quot; It&amp;#39;s surprisingly hard to get the model to curb its enthusiasm

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    &amp;quot;corporate wants you to find the difference between these two images&amp;quot; (left: getliner.com, right: perplexity.ai)

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    “CSCW is reorienting towards AI” overheard at work. True?

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    @BenjaminHan but it’s so good at those things

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    @BenjaminHan how did it go? At least a year ago, the watch app could get stuck “on” recording data and was nearly impossible to terminate.

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    @BenjaminHan that’s intense I use Zwift with Apple TV but it has a 2-device Bluetooth limit. So I have to choose between cadence sensor and HR sensor in addition to the controllable bike trainer.

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    @jbigham prepare to have your game changed https://news.delta.com/delta-soars-centennial-year-game-changing-innovations-ces-2025

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    One thing unique about this device is the screen. Our UXR showed that viewing the speech recognition output engendered trust in the translation. When it’s audio only, users watch the face of the other party to get hints about their understanding. They also listen to the output for words they know in the other language (eg airplane/l’avion.