Qian Yang
Artificial Intelligence (AI) plays an increasingly important role in improving HCI and user experience. Yet many chal lenges persist in designing and innovating valuable human-AI interactions. For example, AI systems can make unpredictable errors, and these errors damage UX and even lead to unde sired societal impact. However, HCI routinely grapples with complex technologies and mitigates their unintended conse quences. What makes AI different? What makes human-AI interaction appear particularly difficult to design? This paper investigates these questions. We synthesize prior research, our own design and research experience, and our observations when teaching human-AI interaction. We identify two sources of AI’s distinctive design challenges: 1) uncertainty surround ing AI’s capabilities, 2) AI’s output complexity, spanning from simple to adaptive complex. We identify four levels of AI sys tems. On each level, designers encounter a different subset of the design challenges. We demonstrate how these findings reveal new insights for designers, researchers, and design tool makers in productively addressing the challenges of human-AI interaction going forward. Author Keywords User experience, artificial intelligence, sketching, prototyping. CCS Concepts •Human-centered computing → Human computer inter action (HCI); Interaction design process and methods;