Context: This article concerns building an artificial intelligence (AI) to do a non-algorithmic task that requires real intelligence. Problem: The literature and practice of AI development does not clarify what is a requirements specification (RS) of an AI that allows determining whether an implementation of the AI is correct. Principal ideas: This article shows how (1) measures used to evaluate an AI, (2) criteria for acceptable values of these measures, and (3) information about the AI’s context informing tradeoffs in these meaures constitute an RS of the AI. Contribution: This article shows two related examples of how such an RS can be used and lists some open questions that will be the subject of future work.

Daniel M. Berry got his Ph.D. in Computer Science from Brown University in 1974. He was on the faculty of the Computer Science Department at the University of California, Los Angeles, USA from 1972 until 1987. He was in the Computer Science Faculty at the Technion, Israel from 1987 until 1999. From 1990 until 1994, he worked for half of each year at the Software Engineering Institute at Carnegie Mellon University, USA, where he was part of a group that built CMU’s Master of Software Engineering program. During the 1998-1999 academic year, he visited the Computer Systems Group at the University of Waterloo in Waterloo, Ontario, Canada. In 1999, Berry moved to what is now the Cheriton School of Computer Science at the University of Waterloo. Between 2008 and 2013, Berry held an Industrial Research Chair in Requirements Engineering sponsored by Scotia Bank and the National Science and Engineering Research Council of Canada (NSERC). Berry’s current research interests are software engineering in general, and requirements engineering and electronic publishing in the specific.