In November 2023, the first global AI Safety Summit was held in Bletchley Park in the UK to discuss the
near and far term risks of AI and the possibility of mandatory and voluntary regulatory frameworks.[314]
28 countries including the United States, China, and the European Union issued a declaration at the start
of the summit, calling for international co-operation to manage the challenges and risks of artificial
intelligence.[315][316] In May 2024 at the AI Seoul Summit, 16 global AI tech companies agreed to safety
commitments on the development of AI.[317][318]
The study of mechanical or "formal" reasoning began with philosophers and mathematicians in antiquity.
The study of logic led directly to Alan Turing's theory of computation, which suggested that a machine,
by shuffling symbols as simple as "0" and "1", could simulate any conceivable form of mathematical
reasoning.[319][320] This, along with concurrent discoveries in cybernetics, information theory and
neurobiology, led researchers to consider the possibility of building an "electronic brain".[r] They
developed several areas of research that would become part of AI,[322] such as McCullouch and Pitts
design for "artificial neurons" in 1943,[115] and Turing's influential 1950 paper 'Computing Machinery
and Intelligence', which introduced the Turing test and showed that "machine intelligence" was
plausible.[323][320]
The field of AI research was founded at a workshop at Dartmouth College in 1956.[s][6] The attendees
became the leaders of AI research in the 1960s.[t] They and their students produced programs that the
press described as "astonishing":[u] computers were learning checkers strategies, solving word problems
in algebra, proving logical theorems and speaking English.[v][7] Artificial intelligence laboratories were
set up at a number of British and U.S. universities in the latter 1950s and early 1960s.[320]
Researchers in the 1960s and the 1970s were convinced that their methods would eventually succeed in
creating a machine with general intelligence and considered this the goal of their field.[327] In 1965
Herbert Simon predicted, "machines will be capable, within twenty years, of doing any work a man can
do".[328] In 1967 Marvin Minsky agreed, writing that "within a generation ... the problem of creating
'artificial intelligence' will substantially be solved".[329] They had, however, underestimated the difficulty
of the problem.[w] In 1974, both the U.S. and British governments cut off exploratory research in
response to the criticism of Sir James Lighthill[331] and ongoing pressure from the U.S. Congress to fund
more productive projects.[332] Minsky's and Papert's book Perceptrons was understood as proving that
artificial neural networks would never be useful for solving real-world tasks, thus discrediting the
approach altogether.[333] The "AI winter", a period when obtaining funding for AI projects was difficult,
followed.[9]
In the early 1980s, AI research was revived by the commercial success of expert systems,[334] a form of
AI program that simulated the knowledge and analytical skills of human experts. By 1985, the market for
AI had reached over a billion dollars. At the same time, Japan's fifth generation computer project inspired
the U.S. and British governments to restore funding for academic research.[8] However, beginning with
the collapse of the Lisp Machine market in 1987, AI once again fell into disrepute, and a second, longer-
lasting winter began.[10]
History