AI Advisor and Human Performer. To reduce cognitive workload for the human partic-
ipant, the task of analyzing plausible choices is outsourced to the AI agent. While the AI
analyses the resources and provides recommendations, the human agent has final deci-
sion on the choice of alternatives, as shown in Table 1. Examples of how this pattern can
be implemented are seen in the maintenance (the AI recommends steps to the technician;
Sect. 4.2) and wildlife monitoring (the AI suggests hypotheses to the expert; Sect. 4.3)
use cases. This design pattern also allows co-learning among the team members. On one
side, feedback from the human participant is used to improve the AI’s recommendations
over time. On the other hand, the suggestions provided to the human actor can expand
their knowledge and give them new perspectives.
AI Performer and Human Assistant. The AI and the human agent have their own ca-
pabilities, which are inherently limited. While the AI is good at performing a particular
DevelopingTeamDesignPatternsfor HybridIntelligenceSystems