Contributors:
Reading list
survey/review/perspective paper book/book chapter Encyclopedia
Required - Explainable Artificial Intelligence (XAI)
- The Nature of Explanation, Cambridge University Press (1943)
- Performance vs. competence in human-machine comparisons, PNAS 2020
- A tale of two explanations: Enhancing human trust by explaining robot behavior, Science Robotics 2019
Required - Teaming
- In situ bidirectional human-robot value alignment, Science Robotics 2022
Optional - Debate over LLM
- On the Dangers of Stochastic Parrots: Can Language Models Be Too Big? 🦜, ACM FAccT 2021
- Language Models Represent Space and Time, arXiv 2310.02207
Optional - Explainable Artificial Intelligence (XAI)
- Explanation in artificial intelligence: Insights from the social sciences, Artificial Intelligence 2019
- Interpretable CNNs for Object Classification, PAMI 2021
- Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI, Information Fusion 2020
- The Emerging Landscape of Explainable Automated Planning & Decision Making, IJCAI 2020
- Explanation Perspectives from the Cognitive Sciences-A Survey, IJCAI 2020
Essay
In this lecture, we discussed XAI as a communication process. Given the materials in the lecture and the reading list, discuss
- The major challenges to be resolved in future XAI research;
- Possible ways to resolve these challenges. You can start by identifying essential components in the communicative XAI framework and analyze the limitation beared by every components. Be bold when proposing possible solutions but try to be specific. Your tentative approaches will be more convincing if you include appropriate settings to verify your thoughts.