Fox News Flash top headlines are here. Check out what's clicking on Foxnews.com. A Tennessee man was sentenced Tuesday to 45 months in prison for leaking classified information about the U.S. drone program in Afghanistan while he was working as an Air Force intelligence analyst. Daniel Hale, 33, pleaded guilty in March to violating the Espionage Act by leaking top-secret documents to a reporter. Hale, who was sentenced in U.S. District Court in Alexandria, said his guilt over participating in lethal drone strikes in Afghanistan led him to leak government secrets.

It is true that artificial intelligence (AI) will come to influence almost every aspect of our lives. In the scramble to realize the potential economic and societal benefits promised by AI, the ready availability of massive, complex, and assumed-to-be generalizable datasets with which to train and test new algorithms is vital. The interaction of governments with their citizens throughout their lives generates huge volumes of diverse information, and these continuously expanding repositories of data are now seen as a public good, providing the raw material for AI industries. In passing the National Artificial Intelligence Initiative Act of 2020 (NAIIA), the United States has adopted a path similar to that of the European Union, as defined within the European Commission's Coordinated Plan on Artificial Intelligence 2021 Review. Under the provisions of the NAIIA, the National Artificial Intelligence Research Resource Task Force (NAIRRTF) has been constituted to make recommendations to Congress on, among other things, the capabilities necessary to create shared computing infrastructure for use by AI researchers and potential solutions in respect to "barriers to the dissemination and use of high-quality government data sets."

A federal rule that requires health care providers to offer patients free, convenient and secure electronic access to their personal medical records went into effect earlier this year. However, providing patients with access to clinician notes, test results, progress documentation and other records doesn't automatically equip them to understand those records or make appropriate health decisions based on what they read. "Medicalese" can trip up even the most highly educated layperson, and studies have shown that low health literacy is associated with poor health outcomes. University of Notre Dame researcher John Lalor, an assistant professor of information technology, analytics and operations at the Mendoza College of Business, is part of a team working on a web-based natural language processing system that could increase the health literacy of patients who access their records through a patient portal. NoteAid, a project based at the University of Massachusetts Amherst, conveniently translates medical jargon for health care consumers.

Blizzard employees will halt work, citing the company's statements on the lawsuit and an internal email from Activision Blizzard Chief Compliance Officer Frances Townsend, which had called the lawsuit claims "a distorted and untrue picture of our company." While the workforce is mostly remote during the coronavirus pandemic, at least 50 employees plan to meet at the front of the Blizzard Campus, multiple current employees confirmed to The Washington Post. The walkout will start at 10 a.m. Pacific time, and is estimated to end at 2 p.m.

The company behind some of the biggest video games in the world is facing intense scrutiny after California regulators filed a lawsuit on July 20 alleging that it has fostered an intensely sexist workplace culture. The state's Department of Fair Employment and Housing is suing Activision Blizzard, the publisher of Call of Duty and Warcraft, following a two-year investigation in which it allegedly discovered evidence that women at the company perpetually face professional and personal discrimination. The disturbing examples span everything from pay imbalances and a glass ceiling to a drunken office culture wherein rape jokes and unwanted advances go unpunished. The company quickly denied the allegations in the lawsuit, but the scandal is snowballing. Both current and former executives have reacted with horror at the investigation, and a growing number of Activision Blizzard employees have shared their own troubling experiences working at the publisher--experiences that echo similar stories of discrimination at other major video game companies.

If efforts by states and cities to pass privacy regulations curbing the use of facial recognition are anything to go by, you might fear the worst for the companies building the technology. But a recent influx of investor cash suggests the facial recognition startup sector is thriving, not suffering. Facial recognition is one of the most controversial and complex policy areas in play. The technology can be used to track where you go and what you do. It's used by public authorities and in private businesses like stores.

The EU's forthcoming regulation on Artificial Intelligence could cost the bloc's economy up to €31 billion over the next 5 years and cause investments to shrink by as much as 20%, according to a study published on Monday (26 July). The assessment by the Centre for Data Innovation looked into the administrative costs of the Artificial Intelligence Act (AIA), a horizontal EU regulation to introduce increasing obligations based on the level of risk associated with the application of the groundbreaking technology. The study author stresses the administrative burden the new legislation is expected to create, which they say will disincentivise innovation and technology uptake. "The Commission has repeatedly asserted that the draft AI legislation will support growth and innovation in Europe's digital economy, but a realistic economic analysis suggests that argument is disingenuous at best," said senior policy analyst and report author Ben Mueller. That goal would require roughly 10 times the level of current investment in the technology, yet the study author says compliance costs would eat up just under 20% of those investments.

Predictive coding offers a potentially unifying account of cortical function -- postulating that the core function of the brain is to minimize prediction errors with respect to a generative model of the world. The theory is closely related to the Bayesian brain framework and, over the last two decades, has gained substantial influence in the fields of theoretical and cognitive neuroscience. A large body of research has arisen based on both empirically testing improved and extended theoretical and mathematical models of predictive coding, as well as in evaluating their potential biological plausibility for implementation in the brain and the concrete neurophysiological and psychological predictions made by the theory. Despite this enduring popularity, however, no comprehensive review of predictive coding theory, and especially of recent developments in this field, exists. Here, we provide a comprehensive review both of the core mathematical structure and logic of predictive coding, thus complementing recent tutorials in the literature. We also review a wide range of classic and recent work within the framework, ranging from the neurobiologically realistic microcircuits that could implement predictive coding, to the close relationship between predictive coding and the widely-used backpropagation of error algorithm, as well as surveying the close relationships between predictive coding and modern machine learning techniques.

Designers of online deliberative platforms aim to counter the degrading quality of online debates and eliminate online discrimination based on class, race or gender. Support technologies such as machine learning and natural language processing open avenues for widening the circle of people involved in deliberation, moving from small groups to ``crowd'' scale. Some design features of large-scale online discussion systems allow larger numbers of people to discuss shared problems, enhance critical thinking, and formulate solutions. However, scaling up deliberation is challenging. We review the transdisciplinary literature on the design of digital mass-deliberation platforms and examine the commonly featured design aspects (e.g., argumentation support, automated facilitation, and gamification). We find that the literature is heavily focused on developing technical fixes for scaling up deliberation, with a heavy western influence on design and test users skew young and highly educated. Contrastingly, there is a distinct lack of discussion on the nature of the design process, the inclusion of stakeholders and issues relating to inclusion, which may unwittingly perpetuate bias. Another tendency of deliberation platforms is to nudge participants to desired forms of argumentation, and simplifying definitions of good and bad arguments to fit algorithmic purposes. Few studies bridge disciplines between deliberative theory, design and engineering. As a result, scaling up deliberation will likely advance in separate systemic siloes. We make design and process recommendations to correct this course and suggest avenues for future research.

We believe these statements have damaged our ongoing quest for equality inside and outside of our industry,