Decision-making

Motional and MIT have developed CW-Net, a system that translates self-driving car neural network logic into human-understandable concepts. Tested in real-world Las Vegas scenarios, CW-Net provides real-time explanations for vehicle decisions, aiding in debugging and building trust. This “causally faithful” approach maintains performance while significantly enhancing AI transparency, a crucial step for autonomous vehicle adoption and regulatory compliance.

First Insight launches Ellis, an AI platform democratizing consumer intelligence. It allows executives to access insights via natural language queries, bypassing traditional analytics teams. This aligns with the trend of broader analytics access, which research shows boosts adoption and ROI, but requires strong governance for accuracy. Ellis aims to integrate predictive insights directly into decision-making, speeding up strategic choices without sacrificing confidence.

MicroCloud Hologram is researching a universal quantum probability theory to address the limitations of existing definitions when applied to complex decision-making scenarios involving interconnected factors and “non-commutative observables.” This theory aims to provide a consistent mathematical foundation for describing any measurement or event, bridging the gap between quantum measurement and decision-making. It seeks to be broadly applicable to both individual and group decisions, and initial results suggest improved accuracy in predicting choices in risk assessment experiments compared to classical models. The company envisions applications in psychology, economics, and social governance.