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AI and ML are now essential parts of many systems that are currently being built. What should CHI practitioners know about the possibilities and potential drawbacks of building AI systems? Understanding the human side of AI/ML based systems requires understanding both how the system-side AI works, but also how people think about, understand, and use AI tools and systems. This course will cover what AI components and systems currently exist, how to design and build usable systems with AI components, along with how the mental models of AI/ML tools operate. These models lead to user expectations of how AI systems function, and ultimately, to design guidelines that avoid disappointing end-users by accidentally creating unintelligible AI tools. We'll also cover the ethics of AI, including data collection, algorithmic and data fairness considerations, along with other risks of AI.
Russell et al. (Sat,) studied this question.