Dive into the world of AI and contract design. This article explores the potential for algorithmic collusion and its implications for fairness, efficiency, and the future of AI in business.
Explore how Synthetic Combinations, a cutting-edge causal inference framework, is making personalized interventions and data-efficient experimentation a reality across industries.
Explore how 'logical differencing' overcomes traditional limitations in network modeling, offering fresh insights into why we form connections and how these networks shape our world.
Many historical documents are inaccessible, but digital history is about to change with an emerging OCR technology using AI, which aims to preserve knowledge for generations to come.
Discover how CLIPPINGS, a novel AI model, is transforming historical record linkage by leveraging multimodal contrastive learning to overcome challenges in noisy OCR data and unlock valuable economic insights from the past.
Discover how sequential treatment allocation, enhanced with covariate analysis, can lead to more informed and effective decision-making in healthcare, business, and beyond. Learn to minimize regret and maximize positive outcomes through innovative strategies.
Forget what you thought you knew about solving multiplayer games. A new study reveals that Fictitious Play, an older, simpler algorithm, surprisingly outperforms the modern Counterfactual Regret Minimization in finding Nash equilibrium strategies. Learn how this discovery could revolutionize AI and game theory.
Are you being charged more because of your browsing history? This article dives into the world of personalized pricing, exploring how companies use your data, and what you can do to protect your privacy and wallet.
Generative AI is revolutionizing the workplace, with the most significant productivity gains seen among less experienced workers. Learn how AI is leveling the playing field, improving job satisfaction, and driving innovation.
New research reveals that augmented balancing weights in AutoDML, often perceived as complex, are surprisingly equivalent to simple linear regressions. Learn how this revelation simplifies machine learning and enhances performance, offering a fresh perspective on automated causal inference.
