Making the Right Thing: Bridging HCI and Responsible AI in Early-Stage AI Concept Selection

Early AI decisions have outsized impact: AI projects often fail due to financial, technical, ethical, or user acceptance problems that originate in early-stage concept choices, suggesting that decisions made at the beginning of a project are critical intervention points for preventing costly failures later.

Multidisciplinary teams can effectively spot ethical risks early: The study found that when practitioners from different backgrounds collaborated to evaluate AI concepts, they were able to identify which ideas posed low risks and high benefits, demonstrating that diverse perspectives help catch ethical concerns before significant resources are invested.

Industry practitioners are ready for responsible AI practices: Participants in the study showed "strong receptivity" to addressing responsible AI concerns from the start, indicating that commercial teams don't need to be convinced of the importance of ethics—they're willing to engage with these questions if given practical tools to do so.

Design thinking can bridge ethics and business goals: A design-led approach that combines ethical reasoning with service design thinking can help companies embed responsible AI principles into innovation processes without treating ethics as separate from commercial objectives.

Early-stage innovation is an underutilized opportunity for ethical engagement: The research identifies the concept selection phase as a "critical space" where HCI and responsible AI communities should focus more attention, as this is where ethical and commercial considerations can be meaningfully integrated before projects become locked into problematic directions.