Kyle speaks with Cornell Tech professor Wendy Ju about implicit interaction: designing robots and autonomous vehicles to understand unwritten rules of human behavior. The description points to Wizard of Oz prototyping and observations of pedestrians, self-driving cars, and robotic furniture as examples for…
Data Skeptic examines Recommender Systems Today and Tomorrow. The publisher describes it as: “In the final episode of our Recommender Systems season, we explore the growing questions of trust, manipulation, privacy, fairness, sustainability, and user control. From fake reviews”. This is a cre…
Data Skeptic examines Recommender Systems Optimization Goals. The publisher describes it as: “In part two of the Data Skeptic Recommender Systems season finale, Kyle asks a deceptively difficult question: what should recommender systems actually optimize for? Drawing on”. This is a cre…
Data Skeptic examines Recommender Systems Origin Story. The publisher describes it as: “Where did recommender systems come from, and how do we know when they’re actually working? In part one of Data Skeptic’s three-part Recommender Systems finale, Kyle”. This is a creator-led account, not an indepen…
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