Six Challenges for Human-AI Co-learning

van den Bosch, K.; Schoonderwoerd, T.A.J.; Blankendaal, R.A.M.; Neerincx, M.A.

doi:10.1007/978-3-030-22341-0_45

Six Challenges for Human-AI Co-learning

Title

Six Challenges for Human-AI Co-learning

Author

van den Bosch, K.
Schoonderwoerd, T.A.J.
Blankendaal, R.A.M.
Neerincx, M.A.

Contributor

Schwarz, J. (editor)
Sottilare, R.A. (editor)

Publication year

2019

Abstract

The increasing use of ever-smarter AI-technology is changing the way individuals and teams learn and perform their tasks. In hybrid teams, people collaborate with artificially intelligent partners. To utilize the different strengths and weaknesses of human and artificial intelligence, a hybrid team should be designed upon the principles that foster successful human-machine learning and cooperation. The implementation of the identified principles sets a number of challenges. Machine agents should, just like humans, have mental models that contain information about the task context, their own role (self-awareness), and the role of others (theory of mind). Furthermore, agents should be able to express and clarify their mental states to partners. In this paper we identify six challenges for humans and machines to collaborate in an adaptive, dynamic and personalized fashion. Implications for research are discussed.

Subject

Co-active learning
Explainable AI
Artificial intelligence
Behavioral research
Cognitive systems
Human computer interaction
Active Learning
Human-agent teaming
Hybrid teams
Mental model
Theory of minds
Learning systems