# Expert Systems and the First AI Winter (1970s–1980s)

Expert systems brought AI to practical, narrow domains but also fueled overpromising that led to funding collapse. This sub-article expands [Section 4 of History](../history.md).

## Expert Systems
- **Rule-based systems** encode human expertise as if–then rules.
- **MYCIN** (1975) diagnosed infections and recommended antibiotics; **XCON** configured computer systems.
- **Knowledge representation** — frames, semantic networks, and logic programming (Prolog) aimed to capture domain knowledge.

## The Fifth Generation Project
- Japan's **Fifth Generation Computer Systems** (1982) aimed at logic-based AI.
- Western programs (UK Alvey, US Strategic Computing) responded; the project ultimately delivered less than promised.

## The First AI Winter
- **Funding collapse**: overpromising, underdelivery, and the LISP machine market crash (1987) reduced funding.
- Many commercial AI firms failed or pivoted.
- Lesson: hype cycles recur; capability must be separated from marketing.

## Why It Matters
Expert systems proved AI could be economically useful, but also revealed that hand-coded knowledge does not scale. This tension set the stage for statistical learning.

## Sources
- Buchanan, B. & Shortliffe, E. (1984). *Rule-Based Expert Systems: The MYCIN Experiments.*
- Feigenbaum, E. et al. (1988). *The Fifth Generation Project.*

*Back to [History](../history.md) · See also [AI Winters](ai-winters.md) · Next: [Statistical Learning](statistical-learning.md).*