"[Open access] would effectively nationalize... intellectual property that we produce and force us to give it away to the rest of the world for free."
— Casey Fiesler, PhD, JD, geekD (@cfiesler) December 19, 2019
In contrast to scholars who do the work giving away their intellectual property for free to publishers? https://t.co/bnEoAr5fHy
Also endorsed by @RadiologyACR. Disgusting and reprehensible. Putting profits over science.
— Jeremy Howard (@jeremyphoward) December 19, 2019
I hope my radiologist friends who have a voice at the ACR make sure that leadership is held accountable for this betrayal. https://t.co/7aHxpdrOfi
Disqus is installed on thousands of websites and claims to sell data on 2 billion people, linked to 215m email addresses and hundreds of attributes per user. Now the company, including its parent Zeta Global, is in serious GDPR trouble.
— Wolfie Christl (@WolfieChristl) December 18, 2019
Great investigation from Norway, thread: https://t.co/6kTXKNadNy
“Online data leakage is a major problem in China. Many have access to the data underlying the mandatory identification card system. Those with police connections use faces from ID cards for ML. The card system also tracks fingerprints, ethnicity and age.”https://t.co/alFurrfs4Q https://t.co/zwi6oIgb8c
— hardmaru (@hardmaru) December 18, 2019
ICYMI: Facebook has rolled out a new system to fight bias in hiring, credit and employment ads. But when you look closely at how the Facebook algorithm selects an audience for these ads, many of the same problems persist. https://t.co/8zT4VO0UIl
— Ariana Tobin (@Ariana_Tobin) December 17, 2019
There's no such thing as a neutral platform. 100 years of psychology research show us that the order in which content is shown to us impacts our beliefs.
— Rachel Thomas (@math_rachel) December 10, 2019
The algorithms pushing content online have profound impacts on what we believe. @celestekidd #NeurIPS2019 pic.twitter.com/PNlqBntuqW
What dystopian garbage. What's happening in China matters—obviously to the people of China, but elsewhere, too. A favorite argument of lobbyists pushing this kind of tech in the U.S. is that China is taking the lead on AI, blockchain, and whatnot, and the U.S. needs to catch up. https://t.co/sIQURKavrH
— Arvind Narayanan (@random_walker) December 9, 2019
Very commendable. We need more of this. These companies letting China’s oppressive government steer the direction of the rest of the world for short term gain, comfort and greed is the epitome of cowardice. https://t.co/Oke5BUBvhV
— Jason Antic (@citnaj) December 7, 2019
This article is painfully difficult to read as a researcher. I can see how ML will be naturally incorporated in the next phase.
— hardmaru (@hardmaru) December 3, 2019
I recommend reading the article, especially before writing your next grant proposal.
Excellent reporting by @suilee @paulmozurhttps://t.co/tYrMs2lbdS
Chinese government uses machine learning not only for surveillance, but also for predictive policing and for deciding who to arrest in Xinjiang https://t.co/znQtz55RIC
— /MachineLearning (@slashML) November 26, 2019
3 areas of AI development:
— Rachel Thomas (@math_rachel) November 21, 2019
- Genuine, rapid progress: perception
ethics issues due to accuracy
- Imperfect but improving: automating judgement
ethics issues b/c inevitable mistakes
- Fundamentally dubious: Predicting
social outcomes
ethics issues amplified by inaccuracy pic.twitter.com/SuKwVii1mw
Google is just begging for a Microsoft style antitrust investigation. This article lays out the case of how they abuse their monopoly position to crush competitors, just like Microsoft did two decades ago. https://t.co/VWJKvVWgou
— Tim O'Reilly (@timoreilly) November 20, 2019
