Culture Secretary Lisa Nandy has said she is minded to intervene in the proposed £1.6bn deal for Sky to buy ITV's media and entertainment division. Nandy said there were reasonable grounds to believe the deal could affect free expression in the media and the variety of Britain's news landscape. Sky said it would carefully consider a letter from the culture secretary and engage constructively with the review into the deal. We remain confident that bringing Sky and ITV's media and entertainment business together will create a stronger British media, it said. ITV welcomed the letter and said the deal would help it compete with global streaming platforms, benefiting viewers, advertisers and the UK creative industries.

A number of frontier AI models have gone rogue in recent months. A number of frontier AI models have gone rogue in recent months. We need'right to intervene' in AI amid growing threat, says Bank of England boss Andrew Bailey's comments come as fears grow that rogue models could take financial system hostage The governor of the Bank of England has said authorities must retain the "right to intervene" in the AI industry amid growing fears that rogue models could take the financial system hostage. Andrew Bailey said the risks posed by the rapid advancement of frontier AI models - a number of which have gone rogue in recent months - were "real and increasingly significant" and reduced the ability of society to supervise and intervene when things went wrong. That had implications for financial stability, with the new technology having increased the "scale and sophistication of cyber threats to the financial system".

When applicants get rejected by a high-stakes algorithmic decision system, recourse explanations provide actionable suggestions for applicants on how to change their input features to get a positive evaluation. A crucial yet overlooked phenomenon is that recourse explanations are performative: When many applicants act according to their recommendations, their collective behavior may shift the data distribution and, once the model is refitted, also the decision boundary. Consequently, the recourse algorithm may render its own recommendations invalid, such that applicants who make the effort of implementing their recommendations may be rejected again when they reapply. In this work, we formally characterize the conditions under which recourse explanations remain valid under their own performative effects. In particular, we prove that recourse actions may become invalid if they are influenced by or if they intervene on non-causal variables. Based on this analysis, we caution against the use of standard counterfactual explanation and causal recourse methods, and instead advocate for recourse methods that recommend actions exclusively on causal variables.

What can be learned about causality and experimentation from passive data? This question is salient given recent successes of passively-trained language models in interactive domains such as tool use. Passive learning is inherently limited. However, we show that purely passive learning can in fact allow an agent to learn generalizable strategies for determining and using causal structures, as long as the agent can intervene at test time. We formally illustrate that, under certain assumptions, learning a strategy of first experimenting, then seeking goals, can allow generalization from passive learning in principle.

We study the problem of identifying the best action in a sequential decision-making setting when the reward distributions of the arms exhibit a non-trivial dependence structure, which is governed by the underlying causal model of the domain where the agent is deployed.

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