BayesiaLab Webinar Series
Human-Machine Teaming in Practice: Bayesian Networks as a Collaborative Approach to Artificial Intelligence
Thursday, May 16, 2019, 11 a.m. – 12 p.m. (CST, UTC-6) — TO BE RESCHEDULED
“Currently, Bayesian Networks have become one of the most complete, self-sustained and coherent formalisms used for knowledge acquisition, representation and application through computer systems.” (Bouhamed et al., 2015)
In this seminar, we illustrate how scientists in many fields of study — rather than only computer scientists — can employ Bayesian networks as a very practical form of Artificial Intelligence for exploring complex problems. We present the remarkably simple theory behind Bayesian networks and then demonstrate how to utilize them for research and analytics tasks.
However, key to unlocking the full potential of Bayesian networks is recognizing their capacity for human-machine teaming. On the one hand, Bayesian networks can perform reasoning tasks that no human could ever perform. On the other hand, Bayesian networks can directly incorporate human causal knowledge, which computers cannot generate independently. As a result, Bayesian networks are a symbiosis based on mutual learning.