Constructing AI ethics narratives based on real-world data: Human-AI collaboration in data-driven visual storytelling

AI ethics narratives are critically needed but largely missing: The paper identifies that existing AI ethics discussions are dominated by science fiction and corporate marketing rather than grounded in real-world data, which can mislead the public about how AI actually works and its real impacts.

"Socio-technical imaginary" can undermine responsible AI development: When speculation about AI is presented without clear distinction from reality, it blurs public understanding and makes it harder for policymakers and regulators to make informed decisions about technology governance.

Human-AI collaboration can create more authentic stories: Rather than relying solely on human storytellers or AI systems alone, the paper proposes that combining human judgment with generative AI capabilities can produce data-driven visual narratives that are both engaging and factually grounded.

Real-world data should anchor AI ethics discussions: By using actual case studies and concrete data rather than hypothetical scenarios, AI ethics narratives can help different stakeholders (technologists, policymakers, the public) have more productive conversations based on shared understanding of real impacts.

Better AI ethics narratives can improve policy outcomes: The authors argue that authentic, accessible storytelling about AI ethics has the potential to increase public engagement and informed participation in policy discussions, ultimately leading to more responsible AI development and regulation.