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It's time we listened to the plight of Thai dissidents abroad

Al Jazeera

About a month ago, two bodies surfaced on the Thai bank of the Mekong River, in the province of Nakhon Phanom. The bodies were handcuffed, disembowelled and stuffed with cement to weigh them down. Rumours started spreading immediately that they may belong to two of the three Thai activists who disappeared from Vientiane, the capital of Laos, on December 12, 2018. Last week the bodies were confirmed to belong to Chatchan "Phoo Chana" Boonphawal, 56, and Kraidet "Kasalong" Luelert, 47, close aides to more widely known republican activist Surachai Danwattananusorn, 76, who disappeared along with them and is still missing. Whoever killed the activists was hoping that the cement in their stomachs would do its work and sink the bodies, and the memory of them, to the bottom of the river.


Morning roundup of Artificial Intelligence news for November 23, 2016

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Werner Vogels, CTO of Amazon, announced yesterday that the MXNet deep learning framework would become "[Amazon's] deep learning framework of choice." Amazon Web Services is expected to announce a new version of its PostgreSQL database for its cloud customers during its AWS re:Invent conference next week, according to a Fortune report. Democratizing Machine Learning has always been BigML's founding mission, so we are continually searching for new opportunities. As such, when a company is interested in our technology and is willing to help us further our cause of "Machine Learning for everyone", we feel the urge to collaborate. This is exactly what happened with our new education partner.


SCL: SCL Irish Group event: "Exploring Bias in AI" (Breakfast meeting) - Thursday 28 November 2019, Dublin

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This event will be highly interactive. Dr Suzanne Little will give a short talk followed by group break-out sessions to discuss the topic in more depth. About the speaker: Dr Suzanne Little is Associate Professor and Senior Lecturer at the School of Computing, Dublin City University and SFI Principal Investigator, Insight Centre for Data Analytics. Before moving to the School of Computing at DCU in 2015, Suzanne was previously a Senior Research Fellow at the Insight Centre for Data Analytics at DCU. Suzanne originally joined the CLARITY research centre at Dublin City University in February 2012 and was principally responsible for the SAVASA project (Standards based Approach to Video Archive Search and Analysis). In 2013, CLARITY evolved to become Insight where Suzanne worked on and managed a number of projects in video analytics, motion analysis and data collection.


Abolish the #TechToPrisonPipeline

#artificialintelligence

The authors of the Harrisburg University study make explicit their desire to provide "a significant advantage for law enforcement agencies and other intelligence agencies to prevent crime" as a co-author and former NYPD police officer outlined in the original press release.[38] At a time when the legitimacy of the carceral state, and policing in particular, is being challenged on fundamental grounds in the United States, there is high demand in law enforcement for research of this nature, research which erases historical violence and manufactures fear through the so-called prediction of criminality. Publishers and funding agencies serve a crucial role in feeding this ravenous maw by providing platforms and incentives for such research. The circulation of this work by a major publisher like Springer would represent a significant step towards the legitimation and application of repeatedly debunked, socially harmful research in the real world. To reiterate our demands, the review committee must publicly rescind the offer for publication of this specific study, along with an explanation of the criteria used to evaluate it. Springer must issue a statement condemning the use of criminal justice statistics to predict criminality and acknowledging their role in incentivizing such harmful scholarship in the past. Finally, all publishers must refrain from publishing similar studies in the future.


Researchers will shine light into the black box of artificial intelligence in medicine

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BROOKLYN, New York, Tuesday, September 3, 2019 - As artificial intelligence and data science enable computer tools to make predictions previously made by skilled humans, a different knowledge gap looms: These black-box tools often offer highly trained medical personnel little understanding of their inner workings. Equally little understood: how deploying these tools affects experts' work practices, perceptions of the value of work, and the expert-patient relationship. Researchers from New York University and Georgia Tech are conducting foundational research to understand and improve expert work in an age of data-intensive enhanced cognition, especially in healthcare, where new technologies are rapidly being deployed. The National Science Foundation recently awarded the team $2 million for the four-year project, which is expected to transform the future of expert work through a combined redesign of technology, workflow, and interactions. "Better understanding of how new technologies impact healthcare expert work will lead to more effective use of healthcare technologies, a healthier and better-informed population, and the more efficient use of human capabilities in restructured healthcare occupations," said NYU Tandon School of Engineering Professor of Technology Management and Innovation Oded Nov, the principal investigator.