Implications of Adaptive vs. Adaptable UIs on Decision Making: Why “Automated Adaptiveness” is Not Always the Right Answer

Miller, C., Funk, H., Goldman, R., Meisner, J., and Wu, P. (2005)
In Proceedings of the 1st International Conference on Augmented Cognition, Las Vegas, NV; July 22-27.

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Keywords: fully adaptive systems, reduced situation, system awareness, degradation, user acceptance

Abstract: In this paper, we begin by contrasting the “adaptive” automation systems prevalent in Augmented Cognition research and development with “adaptable” systems that provide the same range of modifications and behaviors but place control over those adaptations in the hands of the human operator. While there are many obvious reasons to seek adaptive systems, there are also some less well-known consequences to high levels of automation control in human-machine systems. We review the literature on human interaction with high levels of automation in complex and critical work environments to illustrate various problematic effects including loss of situation awareness, poorly tuned trust, skill degradation, unbalanced mental workload, lack of user acceptance and, most importantly, poorer overall human + machine system performance and decision making. We illustrate how these effects may be mitigated by maintaining a more adaptable approach to automation use and suggest an approach to flexible adaptability, our PlaybookTM delegation approach, which seeks to provide the best of both approaches.

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