As Elon Musk prepares to step back from his service in the Trump administration, the nation owes him a debt of gratitude for breaking through decades of empty promises about exposing and ending waste, fraud and abuse in Washington. Musk shared on Tuesday that his time focused on the Department of Government Efficiency (DOGE) would "drop significantly" as he moves to refocus on the businesses and ventures he left behind to serve Trump and the American people. As head of the DOGE, Musk has actually done something about out-of-control spending, and more importantly, he has put systems in place to further and continue this vital work even once he is gone. According to its website, DOGE has saved the federal government 106 billion dollars thus far, or about a thousand bucks per American citizen, which is not chump change. In fact, it is exactly the kind of change our country has long needed.

Sign up for the Slatest to get the most insightful analysis, criticism, and advice out there, delivered to your inbox daily. What's wrong with these darn institutions, and why does nobody trust them? That's the question lurking behind every postmortem about why Democrats lost the 2024 presidential election and what they could do to start winning future ones. The thinking goes like this: Donald Trump, as a political figure, represents blowing up the status quo; Trump won and the incumbent vice president lost; ergo, a majority of voters are unhappy with the people and groups responsible for the status quo. But the evidence that residents of the United States don't trust their institutions goes beyond election results.

On Aug. 29, the California Legislature passed Senate Bill 1047 -- the Safe and Secure Innovation for Frontier Artificial Intelligence Models Act -- and sent it to Gov. Gavin Newsom for signature. Newsom's choice, due by Sept. 30, is binary: Kill it or make it law. Acknowledging the possible harm that could come from advanced AI, SB 1047 requires technology developers to integrate safeguards as they develop and deploy what the bill calls "covered models." The California attorney general can enforce these requirements by pursuing civil actions against parties that aren't taking "reasonable care" that 1) their models won't cause catastrophic harms, or 2) their models can be shut down in case of emergency. Legislation from State Sen. Scott Wiener would introduce standards for product safety testing and liability. Many prominent AI companies oppose the bill either individually or through trade associations.

We study a setting in which a community wishes to identify a strongly supported proposal from a space of alternatives, in order to change the status quo. We describe a deliberation process in which agents dynamically form coalitions around proposals that they prefer over the status quo. We formulate conditions on the space of proposals and on the ways in which coalitions are formed that guarantee deliberation to succeed, that is, to terminate by identifying a proposal with the largest possible support. Our results provide theoretical foundations for the analysis of deliberative processes such as the ones that take place in online systems for democratic deliberation support. Earlier versions of this article have been accepted for presentation at the 35th AAAI Conference on Artificial Intelligence, AAAI-21 [Elkind et al., 2021] and at the 8th International Workshop on Computational Social Choice, COMSOC-21.

Meredith Whittaker is the president of Signal – the not-for-profit secure messaging app. The service, along with WhatsApp and similar messaging platforms, is opposing the UK government's online safety bill which, among other things, seeks to scan users' messages for harmful content. Prior to Signal, Whittaker worked at Google, co-founded NYU's AI Now Institute and was an adviser to the Federal Trade Commission. After 10 years at Google you organised the walkout over the company's attitude to sexual harassment accusations, after which in 2019 you were forced out. How did you feel about that?

This article is an installment of Future Explored, a weekly guide to world-changing technology. You can get stories like this one straight to your inbox every Thursday morning by subscribing here. Patient outcomes are almost always better when a disease is diagnosed and treated early, but some illnesses don't trigger symptoms until a patient is already really sick -- ovarian cancer, for example, can go undetected for 10 years or more, giving it time to spread to other organs. By screening healthy patients for these sneaky diseases, doctors can spot them earlier -- and new artificial intelligence (AI) tools promise to help in the hunt. The challenge: Cardiovascular diseases (CVDs) kill nearly 18 million people every year, making them the leading cause of death worldwide.

Joshua Pantony is the CEO of Boosted.ai, a machine learning company for financial professionals. Portfolio managers are constantly adapting to the ever-evolving environment of the investing landscape. Shifting market trends, government regulation and macroeconomic factors can all affect the way investors form their strategies. A few things are constant though: Investment professionals need to mitigate risk, and hedge fund managers need to hedge their bets. This is especially important during volatile times.

Robots, AI and Automation are going to take over a lot of the jobs. We are constantly hearing this phrase all the time but the more pertinent question is how humans will find meaning in life. Just for a moment think if a lot of our jobs are taken away and even if we are provided universal basic income as it is being proposed (hotly debated of course) we will still have a lot of free time. The only way to be happy in those circumstances will be to find the real meaning of life. Here I have expanded each letter of the word meaning to see how we can handle ourselves.

Surveillance cameras have an identity problem, fueled by an inherent tension between utility and privacy. As these powerful little devices have cropped up seemingly everywhere, the use of machine learning tools has automated video content analysis at a massive scale -- but with increasing mass surveillance, there are currently no legally enforceable rules to limit privacy invasions. Security cameras can do a lot -- they've become smarter and supremely more competent than their ghosts of grainy pictures past, the ofttimes "hero tool" in crime media. Now, video surveillance can help health officials measure the fraction of people wearing masks, enable transportation departments to monitor the density and flow of vehicles, bikes, and pedestrians, and provide businesses with a better understanding of shopping behaviors. But why has privacy remained a weak afterthought?

The history of decision-making has always been intrinsically tied to the history of technology. Charts and compasses have guided explorers for centuries, and a level is an indispensable instrument for construction workers. New tools allow us to make more informed choices which, in turn, may positively impact technological advancements. This dependence suggests that a change in the technological landscape will have implications in how we make decisions. The last half-century has seen one of the most radical revolutions: the emergence of artificial intelligence (AI), powered by the ever-increasing data we gather.