Automation Reliability and Decision Strategy: A Sequential Decision Making Model for Automation Interaction

The question of how people make use of automation to support their decision making is becoming increasingly important. As computers provide ever greater input to the collection, analysis and interpretation of data, so they are more likely to be partners in decision making. However, when automation makes recommendations that the human disagrees with or that might be based on erroneous analysis, then this could result in a change in decision strategy. It is not simply a matter of ignoring or rejecting the recommendation but rather a matter of deciding how best to make use of the automation’s output. By modeling information search and decision strategies under different levels of information reliability, we demonstrate that it makes sense to adapt decision strategy to the information context.

[1]  Keith L. Downing,et al.  Physiological applications of consistency-based diagnosis , 1993, Artif. Intell. Medicine.

[2]  Peter Dayan,et al.  Q-learning , 1992, Machine Learning.

[3]  Oguzhan Alagoz,et al.  Markov Decision Processes: A Tool for Sequential Decision Making under Uncertainty , 2010, Medical decision making : an international journal of the Society for Medical Decision Making.

[4]  Brendan Walsh,et al.  Cost of care for cancer patients in England: evidence from population-based patient-level data , 2016, British Journal of Cancer.

[5]  W. Hamilton Cancer diagnosis in primary care. , 2010, The British journal of general practice : the journal of the Royal College of General Practitioners.

[6]  Richard L. Lewis,et al.  Human Visual Search as a Deep Reinforcement Learning Solution to a POMDP , 2017, CogSci.

[7]  Christopher D. Wickens,et al.  The benefits of imperfect diagnostic automation: a synthesis of the literature , 2007 .

[8]  Antti Oulasvirta,et al.  The Emergence of Interactive Behavior: A Model of Rational Menu Search , 2015, CHI.

[9]  Peter Dayan,et al.  Technical Note: Q-Learning , 2004, Machine Learning.

[10]  Andrew Howes,et al.  A Cognitive Model of How People Make Decisions Through Interaction with Visual Displays , 2017, CHI.

[11]  John D. Lee,et al.  Trust in Automation: Designing for Appropriate Reliance , 2004, Hum. Factors.

[12]  Kris K. Hauser,et al.  Artificial intelligence framework for simulating clinical decision-making: A Markov decision process approach , 2013, Artif. Intell. Medicine.