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The Working Families Party Is Riding The Anti-AI Wave

Mother Jones

Maurice Mitchell of the Working Families Party spoke at a press conference in Washington, DC on April 21, 2026. Get your news from a source that's not owned and controlled by oligarchs. Voters are anxious about losing their jobs to artificial intelligence, and key players across the political spectrum have started to notice. Now, the Working Families Party has rolled out a slate of policy proposals for the midterms, backed by more than two dozen Democratic candidates and representatives, that aims to address that anxiety. Their plan to counter AI-related job losses?


Causal Bandits: Learning Good Interventions via Causal Inference

Neural Information Processing Systems

We study the problem of using causal models to improve the rate at which good interventions can be learned online in a stochastic environment. Our formalism combines multi-arm bandits and causal inference to model a novel type of bandit feedback that is not exploited by existing approaches. We propose a new algorithm that exploits the causal feedback and prove a bound on its simple regret that is strictly better (in all quantities) than algorithms that do not use the additional causal information.





Optimistic Bandit Convex Optimization

Neural Information Processing Systems

We introduce the general and powerful scheme of predicting information re-use in optimization algorithms. This allows us to devise a computationally efficient algorithm for bandit convex optimization with new state-of-the-art guarantees for both Lipschitz loss functions and loss functions with Lipschitz gradients.