AI
Optimism in 1960s AI research led experts to believe AI would soon rival human intelligence, driving heavy investment from governments and universities.
The 1973 Lighthill Report criticized AI research as unproductive and impractical, arguing that AI had limited real-world applications.
After the Lighthill Report, AI funding was drastically cut, leading to project shutdowns and the end of most UK university AI research.
AI research slowed significantly without funding, leading to lab closures, researcher departures, and nearly a decade of stalled progress.
Early AI projects like machine translation and robotics struggled, ambitious goals were halted, and some researchers shifted to theoretical work.
AI funding declined globally as the UK, US, and Japan grew skeptical, leading to reduced enthusiasm for AI research worldwide.
Despite setbacks, AI research persisted with expert systems gaining traction, finding applications in finance and healthcare.
By the late 1970s, AI research shifted toward practical applications, continuing in academia despite limited resources.
Overpromising AI led to funding cuts, making governments cautious. AI had to prove real-world success to regain trust.
By the 1980s, AI regained popularity with new techniques like neural networks and expert systems, leading to a slow return of funding.