"Our focus is really on what we can do to pull the doctor out of the visit," says Akido's CTO. Imagine this: You've been feeling unwell, so you call up your doctor's office to make an appointment. At the appointment, you aren't rushed through describing your health concerns; instead, you have a full half hour to share your symptoms and worries and the exhaustive details of your health history with someone who listens attentively and asks thoughtful follow-up questions. You leave with a diagnosis, a treatment plan, and the sense that, for once, you've been able to discuss your health with the care that it merits. AI companies have stopped warning you that their chatbots aren't doctors Once cautious, OpenAI, Grok, and others will now dive into giving unverified medical advice with virtually no disclaimers. You might not have spoken to a doctor, or other licensed medical practitioner, at all.

On the evening of January 6, 2021, Brad Parscale texted Donald Trump adviser Katrina Pierson about the insurrectionist assault on the US Capitol that had finally been quashed by police. "This is about [T]rump pushing for uncertainty in our country," wrote Parscale, who ran digital and data operations for Trump's 2016 campaign and managed his 2020 reelection effort before being replaced. This week I feel guilty for helping him win." "You did what you felt right at the time and therefore it was right," Pierson replied. "Yeah," Parscale answered, "but a woman is dead." The conversation continued, with Pierson texting, "You do realize this was going to happen." Parscale responded that Trump's rhetoric had "killed someone." Pierson countered, "It wasn't the rhetoric." Parscale was obviously blaming Trump for the storming of the Capitol and the death of Trump supporter Ashli Babbitt. In these private texts--which were not made public until mid-2022 during the House investigation of January ...

As machine learning has made its way into more and more areas of our lives, concerns about algorithmic bias have escalated. Machine learning models, which today facilitate decisions about everything from hiring and lending to medical diagnosis and criminal sentencing, may appear to be data-driven and impartial, at least to naïve users--but the typically opaque models are only as good the data they are trained on, and only as ethical as the value judgments embedded in the algorithms. The burgeoning field of algorithmic fairness, part of the much broader field of responsible computing, is aiming to remedy the situation. For several years now, along with philosophers, legal scholars, and experts in other fields, computer scientists have been tackling the issue. As Stanford University computer science professor Omer Reingold likes to put it, "We are part of the problem, and we should be part of the solution."

Lillian Pierson is a CEO & data leader that supports data professionals to evolve into world-class leaders & entrepreneurs. To date, she's helped educate over 1.3 million data professionals on AI and data science. Lillian has authored 6 data books with Wiley & Sons Publishers as well as 8 data courses with LinkedIn Learning. She's supported a wide variety of organizations across the globe, from the United Nations and National Geographic, to Ericsson and Saudi Aramco, and everything in between. She is a licensed Professional Engineer, in good standing.

Chip shortages are forcing fabs and OSATs to maximize capacity and assess how much benefit AI and machine learning can provide. This is particularly important in light of the growth projections by market analysts. The chip manufacturing industry is expected to double in size over the next five years, and collective improvements in factories, AI databases, and tools will be essential for doubling down on productivity. "We're not going to fail on this digital transformation, because there's no option," said John Behnke, general manager in charge of smart manufacturing at Inficon. "All the fabs are collectively going to make 20% to 40% more product, but they can't get a new tool right now for 18 to 36 months. To leverage all this potential, we're going to overcome the historical human fear of change."

Fox News Flash top headlines are here. Check out what's clicking on Foxnews.com. A hot air balloon pilot died this week after he became trapped underneath the balloon's basket and fell to his death, the Vermont State Police said. Longtime pilot Brian Boland, 72, had left Post Mills Airport in Vermont with four passengers when the balloon started to descend rapidly and touched down in a field. The basket tipped and one of the passengers fell out but wasn't hurt, police said.

The use of machine learning (ML) in health care raises numerous ethical concerns, especially as models can amplify existing health inequities. Here, we outline ethical considerations for equitable ML in the advancement of health care. Specifically, we frame ethics of ML in health care through the lens of social justice. We describe ongoing efforts and outline challenges in a proposed pipeline of ethical ML in health, ranging from problem selection to post-deployment considerations. We close by summarizing recommendations to address these challenges.

Call of Duty: WWII brings the multibillion-dollar video game franchise full circle. While the most recent editions of Activision's series have been set in futuristic settings, this new blockbuster release ( just out, $59 and up, for PlayStation 4, Xbox One and PCs, ages 17-up) plants you in a platoon fighting its way across Europe in World War II. Like the more than a dozen previous Call of Duty games, Call of Duty: WWII is a first-person shooter. So you get to line up Nazis in your gun sights on Normandy beach, within occupied France and in Germany. Playing out like the Band of Brothers miniseries, COD: WWII takes players on an action-packed history lesson through the last year of fighting in the European theater.

Due to recent major technological developments, Artificial Intelligence is evolving at an exponential rate. It is even considered to be the technology of the future. But the truth is, it is already present in our everyday lives: fraud detection, purchase predictions on e-commerce sites, videos games and virtual personal assistants like our favorite one, Julie. In case you still don't fully understand what it entails or want to know more about AI, here is a list of 10 Artificial Intelligence experts and influencers who specialized in Artificial Intelligence and related fields and who share their knowledge on the subject area or just keep you up to date with the latest developments. CEO of Thilium, an Influencer Marketing Agency and International branding expert, Tamara McCleary also specializes in Business experiences in IoT, Machine Learning, Blockchain, Wearables, FinTech and Artificial Intelligence, to name a few.

In this short note, we discuss several aspects of "dimensions" and the related construct of "factors". We concentrate on those aspects that are relevant to articles in this special issue, especially those dealing with the analysis of the wild animal cases discussed in Berman and Hafner's 1993 ICAIL article. We review the basic ideas about dimensions, as used in HYPO, and point out differences with factors, as used in subsequent systems like CATO. Our goal is to correct certain misconceptions that have arisen over the years.