Azeem Azhar: Ultimately, we're living beings who've lived in a world that hasn't moved at exponential rates, and so we get caught out by the speed with which these technologies improve. Annie Veillet: Is it too late to start, and to start putting in the right frameworks and controls? Azeem: Society was really disengaged. It looked at technology as manna from heaven that bright and brilliant people produced as gifts from the gods--and far be it for us to ever ask a critical question of it. And we need to stop doing that, right? We need to be there and ask those questions. Lizzie O'Leary: From PwC's management publication strategy and business, this is Take on Tomorrow, the podcast that brings together experts from around the globe to figure out what business could and should be doing to tackle some of the biggest issues we face. Developments such as AI are changing the way we live. But what happens when those changes happen too quickly for business to deal with?

In a new study, researchers at the Indian Institute of Science (IISc) show how a brain-inspired image sensor can go beyond the diffraction limit of light to detect miniscule objects such as cellular components or nanoparticles invisible to current microscopes. Their novel technique, which combines optical microscopy with a neuromorphic camera and machine learning algorithms, presents a major step forward in pinpointing objects smaller than 50 nanometers in size. The results are published in Nature Nanotechnology. Since the invention of optical microscopes, scientists have strived to surpass a barrier called the diffraction limit, which means that the microscope cannot distinguish between two objects if they are smaller than a certain size (typically 200-300 nanometers). Their efforts have largely focused on either modifying the molecules being imaged, or developing better illumination strategies--some of which led to the 2014 Nobel Prize in Chemistry.

I-Chiao Lin is a computer vision specialist who builds AI applications for virtual reality headsets. Previously, she developed computer vision systems for baby monitors that detect a child's sleep quality. She spoke to us about how she prepares for job interviews, the lessons she has learned developing consumer products, and how a Pixar movie inspired her to pursue a career in AI. Tell me about your current job. What are your main responsibilities and what is your day-to-day work like?

These executives are not flesh and blood, but rather, are sophisticated AI-powered systems capable of simulating human-like decision-making and leadership. Back in 2017, Jack Ma, the visionary founder and CEO of Alibaba, made a bold prediction that may have sounded like science fiction at the time. In an interview with CNBC, Ma proclaimed, "A robot will probably be on the cover of Time Magazine as the best CEO in 30 years". Jack Ma's prediction seemed like a distant dream. Fast forward to today, and the landscape has shifted dramatically.

Tuomas Sandholm is the winner of the 2023 AAAI Award for Artificial Intelligence for the Benefit of Humanity. This award recognizes positive impacts of artificial intelligence to protect, enhance, and improve human life in meaningful ways. Tuomas delivered an invited talk at the AAAI Conference on Artificial Intelligence, during which he spoke about the work that won him the award – using algorithms for organ exchanges. Kidney disease is becoming more prevalent in the world, and, in the USA alone, over 90,000 people are waiting for a kidney transplant. This waiting list keeps growing year on year.

Abstract: An Artificially Intelligent system (an AI) has debatable personhood if it's epistemically possible either that the AI is a person or that it falls far short of personhood. Debatable personhood is a likely outcome of AI development and might arise soon. Debatable AI personhood throws us into a catastrophic moral dilemma: Either treat the systems as moral persons and risk sacrificing real human interests for the sake of entities without interests worth the sacrifice, or don't treat the systems as moral persons and risk perpetrating grievous moral wrongs against them. The moral issues become even more perplexing if we consider cases of possibly conscious AI that are subhuman, superhuman, or highly divergent from us in their morally relevant properties. We might soon build artificially intelligent entities - AIs - of debatable personhood. Our systems and habits of ethical thinking are currently as unprepared for this decision as medieval physics was for space flight.

Automated machine learning (AutoML) is envisioned to make ML While machine learning (ML) has been successfully applied to solve techniques accessible to ordinary users. Recent work has investigated many challenging tasks across various domains, building performant the role of humans in enhancing AutoML functionality ML solutions still requires substantial resources and extensive throughout a standard ML workflow. However, it is also critical to human expertise [34]. Automated machine learning (AutoML), a understand how users adopt existing AutoML solutions in complex, novel concept for automating the whole ML pipeline without (or real-world settings from a holistic perspective. To fill this gap, this as little as possible) human intervention [39], has emerged as a study conducted semi-structured interviews of AutoML users ( way to significantly reduce expensive development costs [75]. As = 19) focusing on understanding (1) the limitations of AutoML encountered illustrated in Figure 1, envisioned to enable domain experts without by users in their real-world practices, (2) the strategies considerable ML backgrounds (e.g., marketing and business analysts) users adopt to cope with such limitations, and (3) how the limitations to build ML solutions more easily, AutoML holds the promise and workarounds impact their use of AutoML.

Recent years have seen growing interest among both researchers and practitioners in user-engaged approaches to algorithm auditing, which directly engage users in detecting problematic behaviors in algorithmic systems. However, we know little about industry practitioners' current practices and challenges around user-engaged auditing, nor what opportunities exist for them to better leverage such approaches in practice. To investigate, we conducted a series of interviews and iterative co-design activities with practitioners who employ user-engaged auditing approaches in their work. Our findings reveal several challenges practitioners face in appropriately recruiting and incentivizing user auditors, scaffolding user audits, and deriving actionable insights from user-engaged audit reports. Furthermore, practitioners shared organizational obstacles to user-engaged auditing, surfacing a complex relationship between practitioners and user auditors. Based on these findings, we discuss opportunities for future HCI research to help realize the potential (and the mitigate risks) of user-engaged auditing in industry practice.

Former UN ambassador Nikki Haley joined'Fox News Sunday' to discuss her bid for the White House in 2014 and how her candidacy differs from Trump. This is a rush transcript of'Fox News Sunday' on February 19, 2022. This copy may not be in its final form and may be updated. A grim milestone as we near one year since Russia invaded Ukraine and kicked off a defining moment for the West. World leaders gathered this week to show strength and to press the Russian president. LLOYD AUSTIN, DEFENSE SECRETARY: Putin thought that he could divide NATO. But his aggression achieved just the opposite. BREAM: But there is still no end in sight, and Ukraine is asking for new help now. We'll ask White House national security spokesperson John Kirby about the latest U.S. efforts to aid Ukraine and the president's upcoming travel to Europe. And we'll bring in retired four-star General Jack Keane for analysis on Ukraine and China's threats now that the U.S. has shot down one of its surveillance devices. Then, former U.N. Ambassador Nikki Haley throws her hat in the ring. NIKKI HALEY (R), PRESIDENTIAL CANDIDATE: I am running for president of the United States of America. BREAM: Nikki Haley joins us for her first Sunday show appearance as a candidate. We'll get her on the record about her case to voters and the criticism she's taking just a few days into her campaign. Plus -- UNIDENTIFIED FEMALE: Our town needs help. MIKE DEWINE (R), OHIO: We've gone into hundreds and hundreds of people's houses to test that air, it's good. MICHAEL REGAN, EPA ADMINISTRATOR: The data shows that there are no elevated levels and we are relying heavily on that data. BREAM: We'll bring you a live report from East Palestine and we'll ask our Sunday panel about trust and transparency as concerns about contamination grow. We begin this morning with breaking news that former President Jimmy Carter is now in home hospice care. The Carter Center says the 98-year-old will spend his remaining time with his loving family. His grandson said Saturday the Carters are at a peace. A Secret Service spokesperson tweeting: Rest easy, Mr. President. We'll keep up on that story. And it was a year ago this week, Russian President Vladimir Putin launched the largest military assault in Europe since World War II.

So much has changed in the past year, it can feel like everything is ripe for disruption, but in spite of the most disruptive year in tech I have ever seen, the biggest surprise for me on this year's list is how little the framework ecosystem has changed. There are lots of new players on the board (shout out to SolidJS) but the big winners from last year still dominate this year and don't seem to be giving up much if any ground in the job market, yet (see below for data-backed evidence). When I conducted my first video interview with GPT-3 in 2020, few people believed that it actually understood anything, let alone that it could produce useful code. Fast forward to today -- every developer is already at a huge disadvantage if they're not using an AI tool like Copilot or reviewing their code for issues, bugs, and suggestions with ChatGPT. GitHub ran a test to discover the impact of AI development tools on developer productivity (specifically, GitHub Copilot), and what they found was very interesting.