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--></style><title>Re: AI - "superhuman
capacities"?</title></head><body>
<div>/.../</div>
<div>the team trained a deep learning model to identify race as white,
Black, or Asian - even though the images themselves contained
no explicit mention of the patient's race. This is a feat even
the most seasoned physicians cannot do, and it's not clear how the
model was able to do this</div>
<div>/.../</div>
<div>Even when you filter medical images past where the images are
recognizable as medical images at all, deep models maintain a
very high performance. That is concerning because superhuman
capacities are generally much more difficult to control, regulate,
and prevent from harming people.</div>
<div>/.../</div>
<div>This paper should make us pause and truly reconsider whether we
are ready to bring AI to the bedside.</div>
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<div
>https://news.mit.edu/2022/artificial-intelligence-predicts-patients-<span
></span>race-from-medical-images-0520</div>
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<div>hasonlónak tünik, noha egészen más területröl:</div>
<div><br></div>
<div><a
href=
"https://phys.org/news/2022-05-ai-reveals-unsuspected-math-underlying.html"
>https://phys.org/news/2022-05-ai-reveals-unsuspected-math-underlying<span
></span>.html</a></div>
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<blockquote type="cite" cite>
<blockquote type="cite" cite><font size="-1">A mesterséges
intelligencia 90 százalékos pontossággal képes megmondani egy
röntgen- vagy CT-felvételr'l az adott személy
rasszát.</font></blockquote>
<blockquote type="cite" cite><a
href=
"https://hvg.hu/tudomany/20220518_mesterseges_intelligencia_rontgenkep_ct_felvetel_faji_hovatartozas"><span
></span
>https://hvg.hu/tudomany/20220518_mesterseges_intelligencia_rontgenke</a
><a
href=
"https://hvg.hu/tudomany/20220518_mesterseges_intelligencia_rontgenkep_ct_felvetel_faji_hovatartozas"><span
></span>p_ct_felvetel_faji_hovatartozas</a></blockquote>
</blockquote>
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