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<blockquote style="position: relative; padding-left: 55px;"><section><a href="https://mas.to/users/beatnikprof/statuses/111161930194594738">Tony Pennino (beatnikprof@mas.to)'s status on Monday, 02-Oct-2023 23:41:45 JST</a><a href="https://mas.to/@beatnikprof" title="beatnikprof@mas.to"><img src="https://gnusocial.jp/avatar/111843-48-20230409185838.webp" width="48" height="48" alt="Tony Pennino" style="position: absolute; left: 0; top: 0;">Tony Pennino</a></section><article><p>Is it possible to be surprised and not surprised at the same time?</p></article><footer><a rel="bookmark" href="https://gnusocial.jp/conversation/2129578#notice-4180035">In conversation</a><time datetime="2023-10-02T23:41:45+09:00" title="Monday, 02-Oct-2023 23:41:45 JST">Monday, 02-Oct-2023 23:41:45 JST</time> <span>from <span><a href="https://mas.to/@beatnikprof/111161930194594738" rel="external" title="Sent from mas.to via ActivityPub">mas.to</a></span></span><a href="https://mas.to/@beatnikprof/111161930194594738">permalink</a><h4>Attachments</h4><ol><li><label><a rel="external" href="https://gnusocial.jp/attachment/1594999">A new study finds a potential risk with self- driving cars: failure to detect dark-skinned pedestrians The findings speak to a bigger problem in the development of automated systems: algorithmic bias. By Sigal Samuel</a></label><br><a href="https://media.mas.to/masto-public/media_attachments/files/111/161/923/014/880/057/original/0c65911ed19d5e85.png" rel="external">https://media.mas.to/masto-public/media_attachments/files/111/161/923/014/880/057/original/0c65911ed19d5e85.png</a></li></ol></footer></blockquote>

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Tony Pennino (beatnikprof@mas.to)'s status on Monday, 02-Oct-2023 23:41:45 JST Tony Pennino
Is it possible to be surprised and not surprised at the same time?
In conversationMonday, 02-Oct-2023 23:41:45 JST from mas.topermalink
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1. A new study finds a potential risk with self- driving cars: failure to detect dark-skinned pedestrians The findings speak to a bigger problem in the development of automated systems: algorithmic bias. By Sigal Samuel
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