Chapter 5: Delegation, relinquishment, and responsibility: The prospect of expert robots
Jason Millar and Ian Kerr
Some day we may come to rely on robotic prediction machines in place of human experts. Google’s search engine, IBM’s Watson, and the Google Driverless Car (GDC) project each give an idea of what that world will look like. Yet actually letting go of the wheel may be a tough sell to humans. Will we really delegate human tasks to expert machine systems and what will be the outcomes of those choices? This chapter suggests that in the near future we will have to make difficult decisions about whether to relinquish some control to robots. The normative pull of “evidence-based practice” and the development of Watson-like robots will leave us few reasons to remain in control of expert decisions where robots excel. Thus we will have to choose between either accepting the relative fallibility of human experts and remaining in total control or deciding to relinquish some control to robots for the greater good. If we do relinquish some control to robots, there are important questions about the justification to do so with highly specialized expert tasks and how that would that bear on the determination of responsibility, particularly in cases of disagreement. On the other hand, if we choose to remain in control and advocate the status quo, we may deliver less than optimal outcomes relative to what “co-robotics” might achieve. Cases of disagreement between human and robot experts, generally favor delegation to robots, but also provide time for human experts to understand and make decisions on the underlying rationale for the disagreement. Watson and the GDC are able to achieve high degrees of something like “expertise” by acting on sets of rules that underdetermine their success. By describing Watson-like robots as “experts,” rather than merely “tools,” we realize a philosophical gain that accounts for both a robot’s unique abilities and social meaning.
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