outputs: guide users in writing effective prompts. Help them identify where and how to add their expertise.
To limit “swivel-chairing” between tools: support users in micro-editing outputs from within the generative AI system. Example: give users a way to choose from output options, re-prompt, or tweak specific words or phrases in-app.
Motivate over mandate
Unavoidable and seemingly arbitrary friction, without an explanation of the benefits or reasons for the friction, can cause frustration. When possible, inspire users to participate, rather than requiring them to do so. To drive willing human participation, generative AI systems should be designed to:
Provide inspiration. Example: offer output options to choose from.
Foster exploration and experimentation. Example: provide the opportunity to easily iterate and micro-edit outputs.
Prioritize informative guardrails over restrictive america phone number list guardrails. Example: flag potential risk. Empower users to determine the appropriate course of action, rather than completely blocking them from taking a certain action.
Embrace different strokes for different folks (and scenarios)
In our research, we prioritized inclusivity by actively involving neurodivergent users and those with English as a second language as experts in digital exclusion. We collaborated with them to envision solutions that ensure the technology benefits everyone from the outset.