This chapter covers work and corresponding insights gained while building an artificially intelligent coworker, named Charlie. Over the past year, Charlie first participated in a panel discussion and then advanced to speak during multiple podcast interviews, contribute to a rap battle, catalyze a brainstorming workshop, and even write collaboratively (see the author list above). To explore the concepts and overcome the challenges when engineering human–AI teams, Charlie was built on cutting-edge language models, strong sense of embodiment, deep learning speech synthesis, and powerful visuals. However, the real differentiator in our approach is that of recognizing artificial intelligence (AI). The act of “recognizing” Charlie can be seen when we give her a voice and expect her to be heard, in a way that shows we acknowledge and appreciate her contributions; and when our repeated interactions create a comfortable awareness between her and her teammates. In this chapter, we present our approach to recognizing AI, discussing our goals, and describe how we developed Charlie’s capabilities. We also present some initial results from an innovative brainstorming workshop in which Charlie participated with four humans that showed that she could not only participate in a brainstorming exercise but also contribute and influence the brainstorming discussion covering a space of ideas. Furthermore, Charlie helped us formulate ideas for, and even wrote sections of, this chapter.
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The authors would like to acknowledge the larger team that has helped make Charlie a reality through design, development, deployment, testing and analysis. This team includes Laura Cassani, Peter Cinibulk, Will Dupree, Deirdre Kelliher, Manuel Moquete, Ryan Mullins, Louis Penafiel.
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Cummings, P., Schurr, N., Naber, A., Charlie, Serfaty, D. (2021). Recognizing Artificial Intelligence: The Key to Unlocking Human AI Teams. In: Lawless, W.F., Mittu, R., Sofge, D.A., Shortell, T., McDermott, T.A. (eds) Systems Engineering and Artificial Intelligence . Springer, Cham. https://doi.org/10.1007/978-3-030-77283-3_2
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