Reflections on Challenges and Promises of Mixed-Initiative Interaction

Research on mixed-initiative interaction and assistance is still in its infancy but is poised to blossom into a wellspring of innovation that promise to change the way we work with computing systems--and the way that computing systems work with us. I share reflections about the opportunities ahead for developing computational systems with the ability to engage people in a deeply collaborative manner, founded on their ability to support fluid mixed-initiative problem solving. Such collaborative intelligence sits at the veritable heart of human civilization. In the course of daily life, we assume and rely on a rich interleaving of efforts to achieve goals while immersed in shared context. We continue to engage one another in efficient, tightly woven collaborations, reasoning with remarkable efficiency about the beliefs, preferences, intentions, and skills of potential collaborators. The inferences underlying successful collaborations typically stream in such an effortless and subconscious manner that we often fail to recognize the elegance and sophistication of these capabilities. The magic of human collaborative competency comes to the foreground with attempts to extend these skills to computational systems. Developing a better understanding of the core aspects of intelligence that enable people to collaborate with fluidity promises to enable new kinds of human-computer collaboration. The nascent area of research on mixed-initiative interaction centers on developing methods that enable computing systems to support an efficient, natural interleaving of contributions by people and computers, aimed at converging on solutions to problems. In mixed-initiative interaction, people and computers take initiatives to contribute to solving a problem, achieving a goal, or coming to a joint understanding. Conversational dialogue is an oft-cited example of mixed-initiative interaction, referring to the ability of each participant in a dialogue to take initiative to guide or add to a discussion. Endowing an automated dialogue system with the ability both to take initiative ("What city do you wish a flight to?") and to allow people to take conversational initiative ("Wait, I'd like to add a side trip.") However, mixed-initiative interaction extends beyond spoken conversations to include a broad spectrum of collaborative problem solving marked by an interleaving of contributions by different participants. Mastering mixed-initiative interaction poses a constellation of fascinating challenges and opportunities for AI researchers. Figure 1 highlights the core challenge of seeking mutual understanding or grounding of joint activity. Joint activity describes the behavior displayed by people working together to solve a mutual goal.