Many analysts are predicting an election-year upturn, but they aren't accounting for the President's ability to cause more chaos. In a primetime address from the Oval Office last week, Donald Trump said, "We are poised for an economic boom the likes of which the world has never seen." This was the sort of bloviating that has convinced many voters he's hopelessly out of touch, but it did raise the question of how the economy is likely to perform in 2026, a midterm-election year. Given the data fog that the government shutdown created, the old joke applies more than ever: it's difficult to make predictions, especially about the future. But some things seem reasonably clear.

We develop new experimental paradigms for measuring welfare in language models. We compare verbal reports of models about their preferences with preferences expressed through behavior when navigating a virtual environment and selecting conversation topics. We also test how costs and rewards affect behavior and whether responses to an eudaimonic welfare scale - measuring states such as autonomy and purpose in life - are consistent across semantically equivalent prompts. Overall, we observed a notable degree of mutual support between our measures. The reliable correlations observed between stated preferences and behavior across conditions suggest that preference satisfaction can, in principle, serve as an empirically measurable welfare proxy in some of today's AI systems. Furthermore, our design offered an illuminating setting for qualitative observation of model behavior. Yet, the consistency between measures was more pronounced in some models and conditions than others and responses were not consistent across perturbations. Due to this, and the background uncertainty about the nature of welfare and the cognitive states (and welfare subjecthood) of language models, we are currently uncertain whether our methods successfully measure the welfare state of language models. Nevertheless, these findings highlight the feasibility of welfare measurement in language models, inviting further exploration.

The researchers found the algorithm used by Rotterdam to investigate some of its 30,000 welfare recipients discriminates based on ethnicity, age, gender, and parenthood. Governments all over the world are experimenting with predictive algorithms in ways that are largely invisible to the public. What limited reporting there has been on this topic has largely focused on predictive policing and risk assessments in criminal justice systems. But there is an area where even more far-reaching experiments are underway on vulnerable populations with almost no scrutiny. Fraud detection systems are widely deployed in welfare states ranging from complex machine learning models to crude spreadsheets.

A play written by an artificial intelligence (AI) program was planned to be presented in Prague this month, to mark the invention of robots (or at least the idea of robots) in the same city exactly one hundred years ago. COVID-19 got in the way of that, and it will now only be available free online late next month. The future is quite different than they expected it would be like. Josef Capek's play, Rossum's Universal Robots: RUR, was an instant hit in 1921. It was his brother, Karel, who came up with the name.

We are witnessing a new wave of technological progress with enormous potential to profoundly transform our societies. Together with globalization, climate change, demographic transformations, and the risk of pandemics such as covid-19, digital disruption is generating far-reaching changes in the global economy. Economic growth is almost exclusively a feature of industrial revolutions and is relatively recent in human history. The social adaptation to the structural changes that technology has brought about has generally been slow, making it a reasonably smooth process. In the case of the digital revolution, however, there are already some signs of a much more abrupt disruption in businesses, markets and societies, reducing the time of response to deal with the new challenges.

Nations around the world are "stumbling zombie-like into a digital welfare dystopia" in which artificial intelligence and other technologies are used to target, surveil and punish the poorest people, the United Nation's monitor on poverty has warned. Philip Alston, UN rapporteur on extreme poverty, has produced a devastating account of how new digital technologies are revolutionizing the interaction between governments and the most vulnerable in society. In what he calls the rise of the "digital welfare state", billions of dollars of public money is now being invested in automated systems that are radically changing the nature of social protection. Alston's report on the human rights implications of the shift will be presented to the UN general assembly on Friday. It says that AI has the potential to improve dramatically the lives of disadvantaged communities, but warns that such hope is being lost amid the constant drive for cost cutting and "efficiency".

All around the world, from small-town Illinois in the US to Rochdale in England, from Perth, Australia, to Dumka in northern India, a revolution is under way in how governments treat the poor. You can't see it happening, and may have heard nothing about it. It's being planned by engineers and coders behind closed doors, in secure government locations far from public view. Only mathematicians and computer scientists fully understand the sea change, powered as it is by artificial intelligence (AI), predictive algorithms, risk modeling and biometrics. But if you are one of the millions of vulnerable people at the receiving end of the radical reshaping of welfare benefits, you know it is real and that its consequences can be serious – even deadly.

All around the world, from small-town Illinois in the US to Rochdale in England, from the Pacific shore of Perth, Australia, to Dumka in northern India, a revolution is under way in how governments treat the poor. You can't see it happening, and may have heard nothing about it. It's being planned by engineers and coders behind closed doors, in secure government locations far from public view. Only mathematicians and computer scientists fully understand the sea change, powered as it is by artificial intelligence (AI), predictive algorithms, risk modeling and biometrics. But if you are one of the millions of vulnerable people at the receiving end of the radical reshaping of welfare benefits, you know it is real and that its consequences can be serious – even deadly.

Everyone likes to talk about the ways that liberalism might be killed off, whether by populism at home or adversaries abroad. Fewer talk about the growing indications in places like Denmark that liberal democracy might accidentally commit suicide. As a philosophy of government, liberalism is premised on the belief that the coercive powers of public authorities should be used in service of individual freedom and flourishing, and that they should therefore be constrained by laws controlling their scope, limits, and discretion. That is the basis for historic liberal achievements such as human rights and the rule of law, which are built into the infrastructure of the Scandinavian welfare state. Yet the idea of legal constraint is increasingly difficult to reconcile with the revolution promised by artificial intelligence and machine learning--specifically, those technologies' promises of vast social benefits in exchange for unconstrained access to data and lack of adequate regulation on what can be done with it. Algorithms hold the allure of providing wider-ranging benefits to welfare states, and of delivering these benefits more efficiently.

But if this is to happen, the Cambridge University Professor believes a political rethink is required: "As to whether that will happen or not will depend on whether this county's politicians are prepared to learn from Scandinavian countries instead of the US. "Scandinavia has a good welfare state and high taxation, the opposite to the US, with its very inadequate welfare state and low taxes. "The present government seems to admire the US system more." The celebrated cosmologist and astrophysicist does however foresee a difficulty with collecting taxes from these multinational tech giants, based on current controversies over their tax arrangements. Facebook's UK tax bill, for example, is 0.62 percent of their £1.3billion