Issue No. 09 - September (2018 vol. 51)
Hani Hagras , University of Essex
Recent increases in computing power, coupled with rapid growth in the availability and quantity of data have rekindled our interest in the theory and applications of artificial intelligence (AI). However, for AI to be confidently rolled out by industries and governments, users want greater transparency through explainable AI (XAI) systems. The author introduces XAI concepts, and gives an overview of areas in need of further exploration—such as type-2 fuzzy logic systems—to ensure such systems can be fully understood and analyzed by the lay user.
Artificial intelligence, Machine learning, Learning systems, Fuzzy logic, Intelligent systems
H. Hagras, "Toward Human-Understandable, Explainable AI," in Computer, vol. 51, no. 9, pp. 28-36, 2018.