Semantic Scholar Open Access 2019 323 sitasi

Counterfactuals in Explainable Artificial Intelligence (XAI): Evidence from Human Reasoning

R. Byrne

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Abstrak

Counterfactuals about what could have happened are increasingly used in an array of Artificial Intelligence (AI) applications, and especially in explainable AI (XAI). Counterfactuals can aid the provision of interpretable models to make the decisions of inscrutable systems intelligible to developers and users. However, not all counterfactuals are equally helpful in assisting human comprehension. Discoveries about the nature of the counterfactuals that humans create are a helpful guide to maximize the effectiveness of counterfactual use in AI.

Topik & Kata Kunci

Computer Science

Penulis (1)

R. Byrne

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Byrne, R. (2019). Counterfactuals in Explainable Artificial Intelligence (XAI): Evidence from Human Reasoning. https://doi.org/10.24963/IJCAI.2019/876

Akses Cepat

Lihat di Sumber doi.org/10.24963/IJCAI.2019/876

Informasi Jurnal

Tahun Terbit: 2019
Bahasa: en
Total Sitasi: 323×
Sumber Database: Semantic Scholar
DOI: 10.24963/IJCAI.2019/876
Akses: Open Access ✓