Healthy skepticism in AI: a data visualization research agenda

Key points

• It is increasingly clear that human trust levels in AI span, in fact, a wide range from critical to over-reliant.1
• There is an urgent need to support both trust and healthy skepticism in AI solutions.1
• We argue that it is healthy for humans to adopt a skeptical view both on the results of AI models and on the use of such AI models.1
• We share our thoughts on the rising phenomenon of over-reliance on AI models, the risks and opportunities in using AI models, and the role of data visualization in over-reliance situations where humans are not motivated to engage in critical thinking.1

Sources (1)

• [1]Healthy skepticism in AI: a data visualization research agenda
  arXiv (AI, ML, NLP, CV, robotics, multi-agent) · Oct 7, 09:31 AM

  Research in data visualization of artificial intelligence (AI) models has historically focused on enhancing trust through visual explanations of AI.

  It is increasingly clear that human trust levels in AI span, in fact, a wide range from critical to over-reliant.

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