The Collaborative Research Centre/Transregio 318's fresh take on explainable AI (xAI) highlights a fundamental rethink many of us in the AI community have been nudging towards but haven't fully embraced—explanations are not a one-way street. Instead of AI systems just unloading information and hoping for understanding, the idea of "social explainable AI" (sXAI) introduces a dynamic where explanation becomes a dialogue, adapting to the user's reactions. This might sound like common sense if you’ve ever taught someone something new, but embedding this conversational, responsive behavior deeply into AI systems is a huge leap forward.
Their research brings in an important human element: understanding is co-created through interaction, not just received. By analyzing real-life conversations and how gestures and language scaffold understanding, they illuminate why many current, static explainability tools fall short—they don't listen or adjust, they just speak.
What I find particularly valuable is the interdisciplinary approach, combining computer science, linguistics, psychology, and more. These fields must often speak different "languages," but when they come together, they generate richer, more nuanced solutions. Challenges with ChatGPT and other LLMs underscore the urgency: these models are amazing at generating text, but they don't truly "get" who they’re talking to or adapt explanations to the moment. That’s where the future of AI explainability lies—context-aware, socially intelligent interactions.
The practical takeaway? AI shouldn't just be a know-it-all but a good listener and an engaged conversational partner. This reframes AI explainability from a brittle technology box-check to a human-centered, evolving dialogue where users can intervene and guide the explanation. It’s a step closer to making AI genuinely useful and trustworthy.
For innovators and developers, the call is clear: focus less on delivering perfect post-hoc rationales and more on building systems that can read the room, sense confusion, and pivot their communication style on the fly. This is real progress toward AI that doesn’t just talk at us but talks with us—and that’s a future worth building. Source: Artificial intelligence: developing explanations together
