মিডিয়া
- টুইট
- টুইট এবং উত্তর
- মিডিয়া, বর্তমান পৃষ্ঠা।
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I regularly talk to people who are miserable in their current jobs, have highly in-demand skills, and yet are convinced they couldn’t find another job and don’t even bother applying. https://code.likeagirl.io/toxic-jobs-low-self-esteem-interviewing-6c4650a3c28a …pic.twitter.com/Q66rEVUkwx
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Even experts often struggle with training new deep learning models. http://www.fast.ai/2018/07/12/auto-ml-1/ …pic.twitter.com/CSw4cVA3Nz
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husbands are ten times more likely to leave women with brain tumors than wives are to leave their husbands https://www.thecut.com/2018/03/doctors-dont-know-how-to-deal-with-womens-pain-books.html …pic.twitter.com/3Mma9fvupF
এই থ্রেডটি দেখান -
On medical bias against women: https://www.thecut.com/2018/03/doctors-dont-know-how-to-deal-with-womens-pain-books.html …pic.twitter.com/owg5YQNzm9
এই থ্রেডটি দেখান -
there is no need to wait and see if the police or government agencies will abuse facial recognition technology https://amp.theguardian.com/commentisfree/2018/jul/06/amazon-rekognition-facial-recognition-government …pic.twitter.com/ftdRFK3HK2
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Surveillance is Orwellian when accurate, Kafkaesque when inaccurate. -
@F_Kaltheuner https://thebaffler.com/salvos/big-brothers-blind-spot-mcneil …@jomcpic.twitter.com/38mU3FfAVp
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Another example of how informal social interactions can have a big impact on who succeeds is tech startups that lack onboarding https://medium.com/tech-diversity-files/donations-and-women-in-tech-panels-are-not-a-diversity-strategy-do-better-c3c51022a916 …pic.twitter.com/9CsLPYBsmC
এই থ্রেডটি দেখান -
Here are some tips from
@timnitGebru on how to counter clique culture:pic.twitter.com/2RzPURReGp
এই থ্রেডটি দেখান -
Important talk by
@timnitGebru at@CVPR on avoiding "clique culture": cliques push people out, harm diversity, & we all miss out on good ideashttps://www.youtube.com/watch?v=MKUCz_3Ee0A&feature=youtu.be&t=2515 …এই থ্রেডটি দেখান -
the problem with previous attempts at drag-and-drop machine learning interfaces is that they don't make the hard parts of ML easier. -
@jeremyphoward https://www.theverge.com/2018/6/12/17452742/deep-learning-ai-learn-lobe-made-easy-coding …@jjvincentpic.twitter.com/deYg4uLLar
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You Say This Can't Really Be America (2017) by
@PainterNell http://www.nellpainter.com/art.html pic.twitter.com/8ISF07bfit
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Questions to ask about software using machine learning https://www.infoq.com/presentations/unconscious-bias-machine-learning …pic.twitter.com/0lMbweWXLQ
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The idea of "structurelessness" does not prevent the formation of informal structures, only formal ones. Structurelessness becomes a way of masking power. https://www.jofreeman.com/joreen/tyranny.htm … (recent h/t
@random_walker, I first read it via@nrrrdcore@CodeNewbies)pic.twitter.com/92uoiJJ2rP
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medical data is often collected through systems designed by, and for, the needs of insurance providers first, and patients second. https://theoutline.com/post/4754/the-government-wants-your-medical-data?zd=1&zi=eiknb77o …pic.twitter.com/ip34wF0TUn
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"software is training most users to spend their days oscillating between being interrupted by notifications and being distracted by the compulsive tendency to stay on top of inboxes" https://medium.com/@searls/you-make-less-money-than-you-used-to-blame-your--61ae5831c93f …pic.twitter.com/hp4DrQZzS8
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"there are actual humans behind these algorithms, and humans can be responsibly regulated"
@joycex99@SphereStanford https://stanfordsphere.com/2018/05/21/silicon-valleys-libertarian-solution-is-regulation/ …pic.twitter.com/jjYLEhkp0L
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Numerous Facebook community "support" groups target addicts & their families. Many are run by marketers of for-profit rehab centers who often don't disclose their conflict of interest & hound members w/ predatory tactics https://www.theverge.com/2018/5/21/17370066/facebook-addiction-support-groups-rehab-patient-brokering …pic.twitter.com/OY1q2DF71L
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Lung cancer screening guidelines are based on a study in which only 4% of participants were African American. This impacts who qualifies for screening, cascading effect on future research.
@datasociety@KadijaFerryman report on bias in precision medicine https://datasociety.net/output/fairness-in-precision-medicine/ …pic.twitter.com/Z2WdvNnebV
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The FBI: - has access to 411 million facial images - if true candidate exists in database, will be listed by their system in top 50 choices just 85% of the time - claims they don't need to worry about false positives from
@EFF report https://www.eff.org/wp/law-enforcement-use-face-recognition …pic.twitter.com/wYti4tKfLv
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Machine Learning Arxiv papers are growing at a faster rate than Moore's Law. -- Zak Stone of TensorFlowpic.twitter.com/QtNGWwcvjv
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