There is widespread concern over the ways speech assistant providers currently use humans to listen to users' queries without their knowledge. We report two iterations of the TalkBack smart speaker, which transparently combines machine and human assistance. In the first, we created a prototype to investigate whether people would choose to forward their questions to a human answerer if the machine was unable to help. Longitudinal deployment revealed that most users would do so when given the explicit choice. In the second iteration we extended the prototype to draw upon spoken answers from previous deployments, combining machine efficiency with human richness. Deployment of this second iteration shows that this corpus can help provide relevant, human-created instant responses. We distil lessons learned for those developing conversational agents or other AI-infused systems about how to appropriately enlist human-in-the-loop information services to benefit users, task workers and system performance.
https://doi.org/10.1145/3313831.3376310
The ACM CHI Conference on Human Factors in Computing Systems (https://chi2020.acm.org/)