Face recognition is a stark example of a technology that is being deployed faster than society and the law can adopt new norms and rules. It lets governments and private enterprise track citizens anywhere there is a camera, even if they're not carrying any devices. In general, people who are in public don't have any legal expectation of privacy and can be photographed or recorded. Because of this, the technology has the potential to be more intrusive than phone tracking, the legality of which the U.S. Supreme Court will soon decide. There are only two states, Texas and Illinois, that limit private companies' ability to track people via their faces.

Amazon staff have called on founder and chief executive Jeff Bezos to stop sales of AWS Rekognition facial recognition tech to U.S. law enforcement. Amazon employees have written a letter to CEO Jeff Bezos in which they ask the company to stop selling its facial recognition tool to American law enforcement. The tech giant's sales to U.S. cops was revealed by an American Civil Liberties Union (ACLU) investigation earlier this month, as it emerged Amazon Web Services' Rekognition tool was shipped to police in Florida and Oregon. The cost of the tool was also revealed to be remarkably low, as evidenced by a Forbes test of the product, in which a facial recognition project was set up for free across the publication's Jersey City and London offices. In a letter posted to an internal forum, first revealed by The Hill and published in full by Gizmodo, some employees expressed the same concerns as the ACLU about the power of Amazon's Rekognition being abused by American officers.

A group of Amazon employees has penned a letter to company chief Jeff Bezos, asking him to stop selling facial recognition to law enforcement. They said that "in the midst of historic militarization of police, renewed targeting of Black activists, and the growth of a federal deportation force currently engaged in human rights abuses," Amazon's facial recognition software will surely serve as a powerful surveillance tool for the government. They also pointed out that a tool like it will "ultimately serve to harm the most marginalized." The employees wrote the letter after an American Civil Liberties Union investigation revealed that the tech giant sells its Rekognition facial detection system to law enforcement customers. Orlando's police chief admitted that the city's cops are testing the software in their headquarters and in a few places downtown.

"Artificial intelligence, or AI, is rapidly transforming the world of medicine. AI computers are diagnosing medical conditions at a rate equal to or better than humans, all while developing their own code and algorithms to do so. With the rise of AI, there are new issues of patentability, inventorship, and ownership that must be addressed." "Recruiting and hiring is the most common use of advanced data analytics and artificial intelligence, adopted by 49 percent of survey respondents." Be developed for the common good.

This work proposes xGEMs: or manifold guided exemplars, a framework to understand black-box classifier behavior by exploring the landscape of the underlying data manifold as data points cross decision boundaries. To do so, we train an unsupervised implicit generative model - treated as a proxy to the data manifold. We summarize black-box model behavior quantitatively by perturbing data samples along the manifold. We demonstrate xGEMs' ability to detect and quantify bias in model learning and also for understanding the changes in model behavior as training progresses.

It's been nearly a decade since Recommind (now OpenText) first pioneered predictive coding for legal document review with OpenText Axcelerate . The advent of supervised machine learning revolutionized eDiscovery with the simplest of principles: if those documents are of interest to you, these probably will be also. Now, all users searching for content across enterprises can benefit from this same principle -- and the same proprietary artificial intelligence technology -- with Predictive Research in OpenText Decisiv 8.2, released in advance of OpenText Enterprise World 2018. Decisiv's unsupervised machine learning provides sophisticated, conceptual analysis of unstructured content to help users find what they're looking for, faster. Decisiv helps legal teams, government workers and business professionals identify useful content, and people with specific expertise, by instantly searching across a wide range of enterprise sources, even when those searching are not sure what terms are likely to yield the best results.

Smart technologies are maturing and set to disrupt the traditional conservative legal market. Banks in particular can leverage these to dramatically reduce their costs and boost efficiency, according to a new report. Technology is expected to fundamentally change the legal industry, a space that is still attached to manual and paper-based processes. According to McKinsey, 22% of a lawyer's job and 35% of a law clerk's job can be automated. "If I was the parent of a law student, I would be concerned a bit," Todd Solomon, a partner at the law firm McDermott Will & Emery, based in Chicago, told the MIT Technology Review.

On Friday, June 22nd, IPI together with United Nations University – Centre for Policy Research are cohosting an all-day policy seminar on "Governing Artificial Intelligence." This event aims to foster an informed discussion on the global public policy implications of AI. What opportunities and challenges does AI hold for humanity? What public policy puzzles emerge from the development and deployment of AI globally and in different political, economic, and social contexts? What role, if any, does the United Nations have to play in helping governments, industry, and civil society worldwide solve these policy puzzles?

Future Tense is a partnership of Slate, New America, and Arizona State University that examines emerging technologies, public policy, and society. "If you look up the word stupid in the dictionary, there's a picture of you," went the sickest burn on the elementary school playground, back before the dictionary was dishing out sick burns of its own. Now Google basically is the dictionary, and real people's pictures come up when you perform a Google Image search for stupid. My recent results included a man with a condom over his head, a teenage boy in a hospital after attempting to complete the Duct Tape Challenge, and--I'm pleased to report--many pictures of Trump. It's a well-acknowledged problem that Google's algorithm determines what images are associated with your name--it's decided, for example, that a still of Rachel Withers, Commuter looking distraught the morning after Election Day 2016 is the second-most important image of me to share (though this is my own fault, for attaching it to an article about being distraught).

Did you hear the one about the affordable yet efficient human lawyer and its robot counterpart? One is complete myth and will never happen while the other might be just around the corner thanks to artificial intelligence (AI). Everybody loves a silly lawyer joke but the joke may be on us because the lawyer or barrister is one of the professions least likely to be replaced by automation and it may also be one that will benefit most from AI and machine learning. There is an interesting website called willrobotstakemyjob.com where you can enter various jobs and see the probability that automation will, at some point in the future, render certain professions obsolete or not. This is calculated using a methodology developed by Oxford University researchers looking at the future of employment.