More and more privacy watchdogs around the world are standing up to Clearview AI, a U.S. company that has collected billions of photos from the internet without people's permission. The company, which uses those photos for its facial recognition software, was fined £7.5 million ($9.4 million) by a U.K. regulator on May 26. The U.K. Information Commissioner's Office (ICO) said the firm, Clearview AI, had broken data protection law. The company denies breaking the law. But the case reveals how nations have struggled to regulate artificial intelligence across borders. Facial recognition tools require huge quantities of data.

The ADA, which applies to employers with 15 or more employees, prohibits discrimination based on disability and requires reasonable accommodations to allow qualified individuals with disabilities to be evaluated for or perform a job. The EEOC's guidance on AI explains how, in the absence of safeguards, an employer's use of certain software tools to select new employees, monitor performance, determine pay or promotions, or administer or score tests may violate these ADA provisions. This Compliance Overview provides the EEOC's guidance for employers. Employers now have a wide variety of computer-based tools available to assist them in hiring workers, monitoring worker performance, determining pay or promotions, and establishing the terms and conditions of employment. Employers may utilize these tools to save time and effort, increase objectivity or decrease bias. When this occurs, employers may risk violating federal equal employment opportunity (EEO) laws that protect individuals with disabilities.

The sheer potential of facial recognition technology in various fields is almost unimaginable. However, certain errors that commonly creep into its functionality and a few ethical considerations need to be addressed before its most elaborate applications can be realized. An accurate facial recognition system uses biometrics to map facial features from a photograph or video. It compares the information with a database of known faces to find a match. Facial recognition can help verify a person's identity, but it also raises privacy issues. A few decades back, we could not have predicted that facial recognition would go on to become a near-indispensable part of our lives in the future.

Why you don't really know what you know October 2020 What does it really mean to know anything? How well can we understand the world when so much of our knowledge relies on evidence and argument provided by others? These questions matter not only to scientists. Many other fields are becoming more complex, and we have access to far more information and informed opinions than ever before. Yet at the same time, increasing political polarization and misinformation are making it hard to know whom or what to trust.

We are moving to a world where every application needs to be intelligent and adaptive to real-time model learning. As businesses build modern data capabilities, they must make decisions at the speed of human thought. Developers are challenged by this, given the huge silos that exist between databases and analytic products, and the complexity of a fragmented data estate can hamper the speed of agility and innovation. What is needed is a consistent data ecosystem. To help address the fragmentation that exists today between databases, analytics and governance, and enable organizations to unlock these new capabilities, we shared several exciting announcements today at Microsoft Build that demonstrate our continued innovation and investment in the data products our customers have come to know and trust, which will enable our customers to achieve the kind of sustained agility that allows them to pivot and adapt in real-time, add layers of intelligence to their applications, unlock fast and predictive insights, and govern their data--wherever it resides.

The European Union is also hammering out its own rules. The AI Act is the next major piece of tech legislation on the agenda in what has been a busy few years. In recent weeks, it closed negotiations on the Digital Markets Act and the Digital Services Act, two major regulations that will curtail Big Tech. The AI law now seeks to impose an all-encompassing framework based on the level of risk, which will have far-reaching effects on what products a company brings to market. It defines four categories of risk in AI: minimal, limited, high and unacceptable.

A former Marine from Orange County has been arrested and faces federal charges for allegedly creating hundreds of Twitter accounts used to stalk a professional video game player who lives in Calgary, Canada, authorities said. Evan Baltierra, 29, was arrested Monday by FBI agents at his home in Trabuco Canyon on suspicion of stalking, according to federal prosecutors. He admitted to investigators he harassed the woman who made her living as a professional online gamer on the popular "War of Warcraft," authorities said. The suspect "orchestrated a campaign of harassment targeting the victim, her boyfriend, her friends and her boyfriend's family," according to court records. Baltierra and his attorney could not be reached for comment.

Clearview AI, the surveillance firm notoriously known for harvesting some 20 billion face scans off of public social media searches, said it may bring its technology to schools and other private businesses. In an interview with Reuters on Tuesday, the company revealed it's working with a U.S. company selling visitor management systems to schools. That reveal came around the same time as a horrific shooting at Robb Elementary School in Uvalde, Texas that tragically left 19 children and two teachers dead. Though Clearview wouldn't provide more details about the education-linked companies to Gizmodo, other facial recognition competitors have spent years trying to bring the tech to schools with varying levels of success and pushback. New York state even moved to ban facial recognition in schools two years ago.

As robots are becoming increasingly intelligent and autonomous, from self-driving cars to assistive robots for vulnerable populations, important ethical questions inevitably emerge wherever and whenever such robots interact with humans and thereby impact human well-being. Questions that must be answered include whether such robots should be deployed in human societies in fairly unconstrained environments and what kinds of provisions are needed in robotic control systems to ensure that autonomous machines will not cause humans harms or at least minimize harm when it cannot be avoided. The goal of this specialty is to provide the first interdisciplinary forum for philosophers, psychologists, legal experts, AI researchers and roboticists to disseminate their work specifically targeting the ethical aspects of autonomous intelligent robots. Note that the conjunction of "AI and robotics" here indicates the journal's intended focus is on the ethics of intelligent autonomous robots, not the ethics of AI in general or the ethics of non-intelligent, non-autonomous machines. Examples of questions that we seek to address in this journal are: -- computational architectures for moral machines -- algorithms for moral reasoning, planning, and decision-making -- formal representations of moral principles in robots -- computational frameworks for robot ethics -- human perceptions and the social impact of moral machines -- legal aspects of developing and disseminating moral machines -- algorithms for learning and applying moral principles -- implications of robotic embodiment/physical presence in social space -- variance of ethical challenges across different contexts of human -robot interaction

Artificial Intelligence (AI) Patent Application filings continue their explosive growth trend at the U.S. Patent Office (USPTO). At the end of 2020, the USPTO published a report finding an exponential increase in the number of patent application filings from 2002 to 2018. In addition, current data shows that AI-related application filings pertaining to graphics and imaging are taking the lead over AI modeling and simulation applications. In the last quarter of 2020, the United States Patent and Trademark Office (USPTO) reported that patent filings for Artificial Intelligence (AI) related inventions more than doubled from 2002 to 2018. See Office of the Chief Economist, Inventing AI: Tracking The Diffusion Of Artificial Intelligence With Patents, IP DATA HIGHLIGHTS No. 5 (Oct.