In October, Amazon had to discontinue an artificial intelligence–powered recruiting tool after it discovered the system was biased against female applicants. In 2016, a ProPublica investigation revealed a recidivism assessment tool that used machine learning was biased against black defendants. More recently, the US Department of Housing and Urban Development sued Facebook because its ad-serving algorithms enabled advertisers to discriminate based on characteristics like gender and race. And Google refrained from renewing its AI contract with the Department of Defense after employees raised ethical concerns. Those are just a few of the many ethical controversies surrounding artificial intelligence algorithms in the past few years.

Stanford's Machine Learning course taught by Andrew Ng was released in 2011. This has become a staple course of Coursera and, to be honest, in machine learning. As of this article, it has had 2,632,122 users enroll in the course. That is just enrolled in, but unknown if they have finished. It is estimated that 1% – 15% of users who start complete the course.

When the Defense Department launched Project Maven, an effort to remake American military technology through artificial intelligence, it leaned on a team of about a dozen engineers working at Google. Many of them, according to two people familiar with the arrangement, were Chinese citizens. The Pentagon was fine with that, they said, even amid rising tensions between Washington and Beijing. Classified data was not involved, the Pentagon reasoned, and the American military needed the most qualified minds for the job. The Trump administration is now moving to limit Chinese access to advanced American research, as relations between the United States and China reach their worst point in decades.

Researchers have developed new software that can be integrated with existing hardware to enable people using robotic prosthetics or exoskeletons to walk in a safer, more natural manner on different types of terrain. The new framework incorporates computer vision into prosthetic leg control, and includes robust artificial intelligence (AI) algorithms that allow the software to better account for uncertainty. "Lower-limb robotic prosthetics need to execute different behaviors based on the terrain users are walking on," says Edgar Lobaton, co-author of a paper on the work and an associate professor of electrical and computer engineering at North Carolina State University. "The framework we've created allows the AI in robotic prostheses to predict the type of terrain users will be stepping on, quantify the uncertainties associated with that prediction, and then incorporate that uncertainty into its decision-making." The researchers focused on distinguishing between six different terrains that require adjustments in a robotic prosthetic's behavior: tile, brick, concrete, grass, "upstairs" and "downstairs."

In this episode of the McKinsey on AI podcast miniseries, McKinsey's David DeLallo and Jeni Tennison, CEO of the Open Data Institute (ODI), discuss the promise and pitfalls of open data. They explore ways that applications of open data can benefit society and consider efforts to preserve data security and privacy, promote data discovery, and ensure the quality of open data. David DeLallo: Data--it's the lifeblood of the AI techniques used most often today. Most organizations have plenty of data within their veritable walls to fuel AI applications that improve areas from operations to product offerings. But it's the sharing of data across organizations that could unlock huge benefits for society.

Medical images reconstructed using artificial intelligence (AI) techniques are unreliable, according to recent research by an international team of mathematicians. The team found that deep learning tools that create high-quality images from short scan times produce multiple alterations and artefacts in the data that could affect diagnosis. These issues were found in multiple systems, suggesting the phenomenon will not be easy to fix. Cutting medical scan time could reduce costs and allow more scans to be performed. To enable this, some researchers have developed AI systems that construct high-quality images from low-resolution scans.

Over the last 10 years, Israel has positioned itself as one of the leading ecosystems for Artificial Intelligence startups. The number of newly founded Israeli startups that employ Artificial Intelligence has raised over the years and so has the capital they have raised. Our analysis shows 1,042 active AI companies in Israel as of June 2020. In 2019, over 150 AI companies were established in Israel representing between 15–25% of all startups founded in 2019. Israel is a global reference in computer vision and mobility related startups.

A Polish website called PimEyes uses facial recognition to search the internet for pictures of a person based on a single image. That photo can be taken from a news site, social media, or an uploaded selfie, and the computer algorithm then shows matches on the web. The free part of service shows photos it believes to be the same person, and rates the'match' out of five stars. It provides a generic name of the site where the picture is found (i.e. For that added insight, it offers a premium service for £9.79 a day where customers can see exactly where the photo comes from.

Thermal-imaging cameras and swab tests for coronavirus are not "clinically valuable" in airports, according to a panel of aviation health experts. About one in every three infectious people would be missed, they say. Air systems and low humidity on planes already reduces virus spread through the cabin. But passengers should wear face coverings at all times, board and disembark one row at a time and be seated apart from others if possible. And those seated at the back should be the first on and last off.

To some in the tech industry, facial recognition increasingly looks like toxic technology. IBM is the latest company to declare facial recognition too troubling. CEO Arvind Krishna told members of Congress Monday that IBM would no longer offer the technology, citing the potential for racial profiling and human rights abuse. In a letter, Krishna also called for police reforms aimed at increasing scrutiny and accountability for misconduct. "We believe now is the time to begin a national dialogue on whether and how facial recognition technology should be employed by domestic law enforcement agencies," wrote Krishna, the first non-white CEO in the company's 109-year history.