Fox News Flash top headlines for Sept. 16 are here. Check out what's clicking on Foxnews.com The Massachusetts Institute of Technology (MIT) computer scientist who said the alleged sex-abuse victims of an associate of deceased convicted sex offender Jeffrey Epstein were "entirely willing" has resigned. Richard Stallman, a famed open-source advocate, announced his departure in an email published online Monday. "I am resigning effective immediately from my position in CSAIL at MIT," he wrote.

Last year, Reuters broke the news that Amazon had been working on a secret AI recruiting tool that showed bias against women. I found it interesting as a case study of an AI project with broad implications for business people and machine learning professionals. After all, everyone has either hired or been hired at least once. We all have a stake in the recruiting game. Sadly, most reporting was sensationalist trash, and the news cycle quickly moved on. It seems nobody tried to answer the question of how a company of the caliber of Amazon -- with seemingly infinite resources -- could stumble so badly. Is AI technology inherently evil? Are all software engineers and data scientists sexist brutes? Is the technology too immature for complex business problems? Or is there something specific about AI projects that makes them difficult -- even for the best companies? The Reuter article was widely circulated and became a prime example of the pitfalls of AI projects.

Artificial intelligence (AI) and automation more broadly continue to be identified as the next frontier in productivity enhancement and growth. Last year, McKinsey estimated AI could potentially increase economic outputs by $13 trillion by 2030, and add to global GDP by approximately 1.2%.[1] Consistent with the trend, it is likely that Australian boards will increasingly look to AI and machine learning to improve the quality of their decision making. But can an algorithm run a company instead of a director? The term'AI' is often used synonymously with machine learning, but this is not strictly correct. True AI exhibits features of human-like intelligence and the ability to use human-like judgement in decision-making.

A local defense company hopes artificial intelligence can help stop mass shootings. Training started on Saturday, all with the goal of eventually saving lives. The training was as realistic as possible and put on by the security company Defendry. A host of actors came together to replicate a scene where an active shooter comes toward them. Recordings of the drill will be marked down and uploaded to program artificial intelligence; all to develop a system that spots a gunman before any shots ring out.

Understanding how political attention is divided and over what subjects is crucial for research on areas such as agenda setting, framing, and political rhetoric. Existing methods for measuring attention, such as manual labeling according to established codebooks, are expensive and can be restrictive. We describe two computational models that automatically distinguish topics in politicians' social media content. Our models---one supervised classifier and one unsupervised topic model---provide different benefits. The supervised classifier reduces the labor required to classify content according to pre-determined topic list. However, tweets do more than communicate policy positions. Our unsupervised model uncovers both political topics and other Twitter uses (e.g., constituent service). These models are effective, inexpensive computational tools for political communication and social media research. We demonstrate their utility and discuss the different analyses they afford by applying both models to the tweets posted by members of the 115th U.S. Congress.

Many readers will remember The Jetsons – a futuristic world in which sophisticated robots in both the home and the workplace had the ability to do, think, learn, and interact with humans. While The Jetsons' rendering of the "future" has not come to fruition, robots and artificial intelligence (AI) have made and continue to make their way into the modern workplace at breakneck speed, creating unprecedented opportunities and challenges for employers in nearly every sector of the economy. This series will explore those challenges, a topic of considerable importance to employers but one that has been overshadowed by the cost-savings and potentially positive economic impact that robots and AI can bring to a workplace. As the use of robots and AI in the workplace have increased and will continue to do so, employers must be proactive about identifying, understanding, and mitigating risks and areas of potential exposure. The future is coming, and in many ways is already here.

But now a new generation of cameras is beginning to be used. Like the one perched on the top of the Cardiff police van, these cameras feed into facial recognition software, enabling real-time identity checks -- raising new concerns among public officials, civil society groups and citizens. Some members of Parliament have called for a moratorium on the use of facial recognition software. The mayor of London, Sadiq Khan, said there was "serious and widespread concern" about the technology. Britain's top privacy regulator, Elizabeth Denham, is investigating its use by the police and private businesses.

Artificial intelligence and the use of smart machines are shaking up law and society. Companies, governments, and universities implement AI without a full understanding of its legal and regulatory threats. This new guide provides a comprehensive overview of the legal issues surrounding artificial intelligence and smart machines. Beginning with a history of AI to exploring the special legal problems such as intellectual property development and labor replacement, this guide discusses risks imposed by artificial intelligence and how to effectively mitigate those risks. The concept of artificial intelligence influences affects broad aspects of business and society.

It would appear that the goal of every second headline on the topic of "the future of work" is to instill an inherent fear in workers regarding what is to come and concerning the status of their careers and their future AI coworkers. The message seems to be: "Robots are coming for your jobs and there isn't much you can do about it." The former portion of this message is somewhat true, automation is on the rise, which will cause many positions to be filled by high-speed, data-crunching technology. But the latter, rather uninspiring portion, is not true. Working humans are not doomed as long as the companies they work for recognize the skills of the future and focus on building and developing the areas robots cannot do well.

Greta Thunberg is 16 and lives in Sweden. Until February last year, she was just another student concerned about the environment. Today, she's become the world's most influential climate activists, after founding'Fridays for Future', a movement that encourages school students to take time off from class to participate in demonstrations against their countries' governments for breaching environmental laws. Greta believes that we're heading towards a natural disaster and the planet's destruction if we fail to change our habits as a society. And that includes everyone, from large industries to the individual citizen.