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Last Week in AI #61

Trustworthy AI developments, AI without supervision, and more!

Last Week in AI #61

Image credit: Todd St. John / The New York Times

Mini Briefs

Toward Trustworthy AI Development: Mechanisms for Supporting Verifiable Claims

For AI to be widely deployed in the real world it must “earn trust from [users], civil society, governments, and other stakeholders.” Instead of relying on abstract AI principles, which many countries and companies have published, stakeholders should focus on concrete ways that can verify responsible behavior. This both makes oversight more effective and protects users from “potentially ambiguous, misleading, or false claims.”

Some of the concrete measures the article suggests include third-party auditing, AI bias and safety bounties, and developing more privacy-preserving AI algorithms.

Implementation of such mechanisms can help make progress on the multifaceted problem of ensuring that AI development is conducted in a trustworthy fashion.

Computers Already Learn From Us. But Can They Teach Themselves?

This article interviews a few prominent AI and robotics experts about the emphasis on unsupervised and self-supervised learning, as opposed to supervised learning, for future AI research. Most recent breakthroughs in AI have been in supervised learning, which uses a database of “question-answer” pairs, often times tediously annotated by humans, to train a model to answer questions. Many experts in the field believe that other forms of learning that do not need labeled data may be more critical to AI development:

“My money is on self-supervised learning,” [Dr. Yann LeCun] said, referring to computer systems that ingest huge amounts of unlabeled data and make sense of it all without supervision or reward. He is working on models that learn by observation, accumulating enough background knowledge that some sort of common sense can emerge.

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News

Advances & Business

Concerns & Hype

  • Why you (probably) don’t need AI - 88% of brands are now using AI. And yet, 55% are disappointed with the results of their investment. As underwhelming as this satisfaction statistic may be, it doesn’t necessarily mean that AI technology itself is at fault. Rather, misguided adoption of AI is more likely to drive disappointment.

  • Security lapse exposed Clearview AI source code - Since it exploded onto the scene in January after a newspaper expose, Clearview AI quickly became one of the most elusive, secretive, and reviled companies in the tech startup scene.

  • Clearview AI Privacy Request Forms - This page contains links to automated forms from Clearview AI to obtain and remove personal data company collects.

Analysis & Policy

Expert Opinions & Discussion within the field

  • AI v Covid-19 - The coronavirus crisis has brought an unprecedented level of worldwide scientific collaboration. Artificial Intelligence based on Neural Networks and Deep Learning can help to fight Covid-19 in many ways.

That’s all for this week! If you are not subscribed and liked this, feel free to subscribe below!

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