Interactive AI/ML

Interactive Machine Learning (IML) is concerned with the development of algorithms for enabling machines to cooperate with humans for the purpose of solving a shared prediction, learning, or teaching task. Despite its potential, knowledge transfer between different sub topics of IML and between research and applications has been limited. Join Oznur Alkan, Lead Software Engineer, to discuss:

• How to best integrate people into the IML learning loop in a way that is transparent, efficient, and beneficial to the human-AI team as a whole, supporting different requirements and users with different levels of expertise.
• The huge challenges the introduction of IML solutions creates to allow users to understand the impact of their influence to instill trust and confidence.
• The risks of introducing of biases or unplanned consequences by users or model creators.