This study discusses the interplay between metrics used to measure the explainability of the AI systems and the proposed EU Artificial Intelligence Act. A standardisation process is ongoing: several entities (e.g. ISO) and scholars are discussing how to design systems that are compliant with the forthcoming Act and explainability metrics play a significant role. This study identifies the requirements that such a metric should possess to ease compliance with the AI Act. It does so according to an interdisciplinary approach, i.e. by departing from the philosophical concept of explainability and discussing some metrics proposed by scholars and standardisation entities through the lenses of the explainability obligations set by the proposed AI Act. Our analysis proposes that metrics to measure the kind of explainability endorsed by the proposed AI Act shall be risk-focused, model-agnostic, goal-aware, intelligible & accessible. This is why we discuss the extent to which these requirements are met by the metrics currently under discussion.

A study published in Social Psychological and Personality Science presents evidence that people make judgments about strangers' personalities based on how closely their resting faces resemble emotional expressions. It was found that among seven classes of facial characteristics, resemblance to emotional expressions was the strongest predictor of impressions of both trustworthiness and dominance. It has long been demonstrated that people form rapid impressions of others based on their physical appearances. Such quick judgments can have strong repercussions -- for example, when juries are forming impressions of the accused during criminal trials or when hiring managers are screening potential candidates. "One thing I find fascinating about first impressions is how quickly and intuitively they come to mind. For example, I might see a stranger on the train and immediately get the feeling that they cannot be trusted. I want to understand where these intuitions come from. What is it about a person's appearance that makes them appear untrustworthy, intelligent, or dominant to us?" said study author Bastian Jaeger, an assistant professor at the Vrije Universiteit Amsterdam.

The robotic artist known as Ai-Da was scheduled to display her artwork alongside the great pyramids of Egypt on Thursday, though the show was nearly called off after both the robot and her human sculptor, Aidan Meller, were detained by Egyptian authorities for a week and a half until they could confirm that the artist was actually a spy. The incident began when border guards objected over Ai-da's camera eyes, which it uses in its creative process, and its on-board modem. "I can ditch the modems, but I can't really gouge her eyes out," Meller told The Guardian. The robot artist, which was built in 2019, typically travels via specialized cargo case and was held at the border until clearing customs on Wednesday evening, hours before the exhibit was scheduled to begin. "The British ambassador has been working through the night to get Ai-Da released, but we're right up to the wire now," Meller said, just before Ai-Da was sprung from robo-jail.

The symposium on Artificial Intelligence – or AI – organized by the Pontifical Council for Culture, in cooperation with the German Embassy to the Holy See, will open in Rome on Thursday. The theme for the gathering is, "The Challenge of Artificial Intelligence for Human Society and the Idea of the Human Person". The aim of the meeting is to promote a better awareness of the profound cultural impact AI is likely to have on human society. The symposium will feature six experts from the fields of neuroscience, philosophy, Catholic theology, human rights law, ethics and electrical engineering. Experts from the Allen Institute for Brain Science, Goethe University, Boston College, and Google will discuss questions regarding AI and whether it can reproduce consciousness, AI and philosophical challenges, and AI and religion, and what it would mean in relation to Catholic doctrine.

Carnegie Mellon University researchers are challenging a long-held assumption that there is a trade-off between accuracy and fairness when using machine learning to make public policy decisions. As the use of machine learning has increased in areas such as criminal justice, hiring, health care delivery and social service interventions, concerns have grown over whether such applications introduce new or amplify existing inequities, especially among racial minorities and people with economic disadvantages. To guard against this bias, adjustments are made to the data, labels, model training, scoring systems and other aspects of the machine learning system. The underlying theoretical assumption is that these adjustments make the system less accurate. A CMU team aims to dispel that assumption in a new study, recently published in Nature Machine Intelligence.

Like transformative technologies that came before, the ethics of AI is coming under increased scrutiny, giving birth to regulations and policies constraining the scope of its application. Artificial Intelligence is a dynamic technology sector, powering a broad spectrum of emerging applications in the fields of industrial robotics and robotic process automation (RPA). Like transformative technologies that came before, the ethics of AI is coming under increased scrutiny, giving birth to regulations and policies constraining the scope of its application. What are the risks and what's being done to promote an ethical application of one of today's most empowering technologies? What exactly is AI and what role does it play in robotic technologies?

New York City has launched its first artificial intelligence (AI) strategy, with an emphasis on digital ethics. It aims to help the city establish a shared understanding of AI and capitalise on the benefits while managing the risks. The 116-page AI Strategy focuses on how to use AI to better serve residents; building AI know-how within government; modernising data infrastructure; city governance and policy around AI; developing partnerships with external organisations; and promoting equitable access to opportunities. It is the latest in a series of initiatives that aim to make New York City'future-ready', following on from the IoT Strategy and the Internet Master Plan. "As a global epicentre of innovation, New York City has a key role to play in shaping the future of AI," said New York City Chief Technology Officer, John Paul Farmer.

Activision Blizzard has confirmed that more than 20 employees have "exited" the company as part of its efforts to change its internal culture following allegations of fostering a "frat boy" workplace. The video game company has published the letter Executive VP for Corporate Affairs Fran Townsend sent to employees revealing the move, in which she also said that more than 20 other individuals faced different types of disciplinary action. Back in July, the California Department of Fair Employment and Housing filed a lawsuit against the developer for allowing a work environment wherein female employees were allegedly subjected to constant sexual harassment. The agency, which sued the company after a two-year investigation, detailed several of its findings in the lawsuit. It said female employees constantly have to fend off unwanted sexual comments, and that they have to endure being groped by male colleagues. They're also not paid as much as their male counterparts, are typically promoted more slowly and fired more quickly.

Lily Xu is a PhD student at Harvard University, applying machine learning and game theory to wildlife conservation. She is particularly focused on the prevention of illegal wildlife poaching, and she told us about this interesting, and critically important, area of research. Green security is the challenge of environmental conservation under some unknown threat. The three domains that we focus on are illegal wildlife poaching, illegal logging and illegal fishing. Across all of these settings we have an environmental challenge, which is to preserve our natural ecosystems.

As AI makes dramatic inroads in enterprises, the U.S. government has quietly started to regulate the use of AI in the consumer credit industry and other areas by banning the use of biased and unexplainable algorithms in decisions that affect consumers. In recent years, the Federal Trade Commission has tried to regulate AI in lending with laws that are already in place, chief among them the Fair Credit Reporting Act (FCRA). The federal agency has also included AI regulation under the FTC Act and the Equal Credit Opportunity Act (ECOA). While the federal laws don't contain explicit language regulating AI, the FTC, which enforces the laws, has issued guidance over the last two years stipulating that under the FCRA, lenders can't use biased or unexplainable algorithms for not only consumer credit, but also employment, housing, insurance and other benefits. The FTC has also clarified that the sale or use of racially biased algorithms, for example, is a deceptive practice banned by the FTC Act.