AIn a search for lessons learned from 50 years of history of AI, this paper presents a brief, subjective and personal history of the field. It then introduces five theses-prescriptions for what makes good AI research. The theses stem form the author's understanding of successes and failures of the field, and from his own experience as a long-standing and active member of the AI community. The five theses promote practicality, embeddedness, empirical verification, mathematical foundation, and scrutiny.
Financed by the National Centre for Research and Development under grant No. SP/I/1/77065/10 by the strategic scientific research and experimental development program:
SYNAT - “Interdisciplinary System for Interactive Scientific and Scientific-Technical Information”.