Abstract
The modern world is evolving rapidly, especially with respect to the development and proliferation of increasingly intelligent, artificial intelligence (AI) and AI-related technologies. Nevertheless, in many ways, what this class of technologies has offered as return on investment remains less impressive than what has been promised. In the present paper, we argue that the continued failure to realize the potential in modern AI and AI-related technologies is largely attributable to the oversimplified, yet pervasive ways that our global society treats the relationship between these technologies and humans. Oversimplified concepts, once conveyed, tend to perpetuate myths that in turn limit the impact of such technologies in human society. To counter these oversimplifications, we offer a theoretical construct, which we call the landscape of human-AI partnership. This construct characterizes individual capability for real-world task performance as a dynamic function of information certainty, available time to respond, and task complexity. With this, our goal is to encourage more nuanced discourse about novel ways to solve challenges to modern and future sociotechnical societies, but without defaulting to notions that remain rooted in today’s technologies-as-tools ways of thinking. The core of our argument is that society at large must recognize that intelligent technologies are evolving well beyond being mere tools for human use and are instead becoming capable of operating as interdependent teammates. This means that how we think about interactions between humans and AI needs to go beyond a “Human–or–AI” conversation about task assignments to more contextualized “Human–and–AI” way of thinking about how best to capitalize on the strengths hidden within emergent capabilities of unique human-AI partnerships that have yet to be fully realized.
Highlights
O UR global society is in the midst of what some consider to be one of the most sweeping and disruptive periods of technology evolution in history [1]–[3]
We argue that the fundamental nature of future human-artificial intelligence (AI) partnerships is task relative, depending on the certainty of information forming the basis of the problem, the amount of time available to resolve the situation, and, most critically, task complexity
In the following two sections, we provide evidence to substantiate the capability maps shown in Figure 1 above, in order to frame our discussion about role expectations in human-AI partnership
Summary
O UR global society is in the midst of what some consider to be one of the most sweeping and disruptive periods of technology evolution in history [1]–[3]. The three oversimplifications presented here were chosen based on their recurrence as barriers to communicating and achieving common understandings of the challenges and opportunities for integrating AI into humans’ daily lives It seems that discussions of AI relative to humans end up devolving into debates fueled by the exact notions captured above: "Human jobs will be lost to AI and robots." "AI can’t possibly replace artists, therapists, and managers." "Complex decisions will be offloaded to advanced, intelligent computers and yet, we will always need human mediators when other people do not accept those decisions." Though new AI and machine learning approaches are continually being developed and brought to bear within each of these exemplar sectors, few have seen marked success in terms of broad acceptance and full integration as a de facto part of our society. Humans are able to understand the broader context and, given time, are able to draw conclusions based on sparse data more effectively than the AI that may not be fully likely to track relevant context cues
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