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Conveying Agent Behavior to People: A User-Centered Approach to Explainable AI

CORDIS · observation · Publication date unknown

Conveying Agent Behavior to People: A User-Centered Approach to Explainable AI From self-driving cars to agents recommending medical treatment, Artificial Intelligence (AI) agents are becoming increasingly prevalent. These agents have the potential to benefit society in areas such as transportation, healthcare and education. Importantly, they do not operate in a vacuumpeople interact with agents in a wide range of settings. To effectively interact with agents, people need to be able to anticipate and understand their behavior. For example, a driver of an autonomous vehicle will need to anticipate situations in which the carfails and hands over control, while a clinician will need to understand the treatment regime recommended by an agent to determine whether it aligns with the patients preferences. Explainable AI methods aim to support users by making the behavior of AI systems more transparent. However, the state-of-the-art in explainable AI is lacking in several key aspects. First, the majority of existing methods focus on pr

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award

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SIGNED

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EU

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1470250

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EUR