Humans make decisions and solve problems using heuristics (“thinking fast”) or abstract approaches such as modeling (“thinking slow”). Artificial intelligence approaches can similarly use either heuristics that are related to correlation and categorization, or use models that are related to causation. Predictive Engineering, which melds engineering modeling with probabilistic thinking, aligns closely with causation and an aspect of artificial intelligence called Causal Learning. Issues with some artificial intelligence approaches will be explored, with real (and sometimes controversial and provocative) examples, and promising approaches encompassing causation /predictive engineering will be discussed. [] Speaker(s): Eric Maass Virtual: https://events.vtools.ieee.org/m/445270

Feb ExCom Honolulu, Hawaii, United States, Virtual: https://events.vtools.ieee.org/m/463036

Monthly YP meeting. 733 Bishop Street, Suite 2000, Honolulu, Hawaii, United States, Virtual: https://events.vtools.ieee.org/m/468162