IBM Addresses AI Bias with Massive Image Archive

According to IBM, the current largest facial attribute dataset is made up of just 200,000 images. IBM will also be releasing an annotated dataset of up to 36,000 images that are equally distributed across skin tones, genders, and ages. The company hopes that it will help algorithm designers to identify and address bias in their facial analysis.

Photo: Saul Loeb/Agence France-Presse/Getty Images Deep learning and related machine learning. A number of initiatives have been organized to address these and other major AI and deep learning.

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 · The study called for “urgent attention” to address the bias. “I responded pretty much right away,” said Ruchir Puri, chief scientist of IBM Research, describing an email he received from.

 · Big Law firms are gearing up for potential discrimination lawsuits, resulting from inherent bias in artificial intelligence tools used by employers. Since March, both Paul Hastings and DLA Piper have launched practices focused on artificial intelligence, while other firms like Littler Mendelson, Fisher Phillips, and Proskauer Rose have partners well-versed in the developing technology and its.

For the task of determining the gender of a face, we used the same methodology that revealed substantial gender and skin type bias in AI services sold by Microsoft, IBM, and (Megvii) Face++ to.

You don’t have to dig too deeply into the archive. took a big step forward in 2017. However, we’re far from the runaway technological singularity futurists are predicting by mid-century or earlier,

The Center for the Governance of AI is part of Oxford University’s Future of Humanity Institute. The new report, by Dafoe and Yale’s Baobao Zhang, is based on a 2018 survey of 2,000 US adults. There.

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 · The study called for “urgent attention” to address the bias. “I responded pretty much right away,” said Ruchir Puri, chief scientist of IBM Research, describing an email he received from.

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 · IBM has taken a keen insight in applying Watson’s supercomputing capabilities to imaging – especially since its 2015 acquisition of Merge. Big Blue, in fact, is developing numerous tools to help automate analytics, enabling cross-reference X-rays, MRIs and other images against electronic health record data, lab results, genomic tests and more.