3rd century BCEEuclid and repeatable procedure
Book VII of the Elements describes a procedure for finding the greatest common divisor through defined and repeatable steps.
Modern connection: a precise, finite and repeatable procedure is the basis of an algorithm.
Source: Euclid, Elements, Book VII — Perseus ↗
3rd century BCEThe sieve of Eratosthenes
The procedure identifies prime numbers by progressively eliminating those that do not satisfy the condition.
Modern connection: filtering invalid cases resembles workflow rules, filters and checks.
Source: MacTutor, History of prime numbers ↗
4th century BCEAristotle: categories and inference
Aristotelian logic organises forms of inference; the Categories provides a structure for distinguishing general kinds of beings and predication.
Modern connection: classifying concepts, representing rules and separating premises from conclusions.
Does correctly applying a rule amount to understanding?
Source: Stanford Encyclopedia of Philosophy, Aristotle’s Logic ↗
Source: Stanford Encyclopedia of Philosophy, Aristotle’s Categories ↗
2nd–1st century BCEThe Antikythera mechanism
A complex geared device represented calendrical and astronomical information and performed calculations relating to celestial cycles.
Modern connection: a model of the world can be embedded in a device that transforms initial settings into a calculated result.
It did not learn from data and was not artificial intelligence: it executed relationships designed by people.
Source: Nature Astronomy, Our current knowledge of the Antikythera Mechanism ↗
1st century CEHero of Alexandria and automata
The Automata describes mechanical devices capable of executing sequences designed in advance, including mobile automata and theatrical displays.
Modern connection: a prepared sequence is executed automatically in the same order, a useful analogy for automation but not machine learning.
Source: University of Glasgow, critical edition of the Automata ↗
9th centuryAl-Khwārizmī and the name of the method
The Persian mathematician sets out systematic procedures for calculation with positional notation. The Latin form of his name, Algoritmi, enters European usage and becomes the word we still use.
Modern link: the word "algorithm" comes not from an abstract theory but from a working manual.
Source: MacTutor, al-Khwārizmī biography ↗17th centuryLeibniz: binary and the calculus of reasoning
Leibniz formalises the binary number system and imagines a calculus ratiocinator: a notation that would settle disputes by calculation rather than argument.
Modern link: two separate ideas that now live inside every machine: binary representation, and the ambition to reduce reasoning to mechanical operation.
Source: Stanford Encyclopedia of Philosophy, Leibniz ↗1854Boole and the laws of thought
An Investigation of the Laws of Thought treats propositions as algebraic objects: true and false become values manipulated by explicit rules.
Modern link: every condition, filter and gate in an automated sequence is Boolean algebra in use.
Source: Boole, An Investigation of the Laws of Thought (1854) ↗1804–1843Jacquard, Babbage and Lovelace
The Jacquard loom separates the machine from its instructions, punched onto cards. Babbage designs the Analytical Engine; Ada Lovelace observes it could operate on any symbols, not only numbers.
Modern link: the split between machine and program, and the insight that computation is not only about quantity.
Source: MacTutor, Ada Lovelace biography ↗1936–1950Turing: computability and a behavioural criterion
Turing defines what a machine can compute in principle, and in 1950 moves the question "can it think?" onto observable ground, proposing an imitation game in place of a definition.
Modern link: the boundary of what is computable, and the habit of judging systems by measurable behaviour rather than stated intent.
Source: Turing, Computing Machinery and Intelligence, Mind (1950) ↗1948Shannon and the measure of information
A Mathematical Theory of Communication separates content from meaning: information becomes a measurable quantity, with noise, redundancy and channel capacity.
Modern link: why data can be abundant and uninformative, and why quality checks measure noise before signal.
Source: Shannon, A Mathematical Theory of Communication (1948) ↗1956Dartmouth: the term is coined
The proposal for the Dartmouth summer workshop introduces the phrase "artificial intelligence" and sets a research agenda. From here on the history stops being analogy and becomes that of the field itself.
Modern link: this is where the page stops: everything after it is no longer a conceptual antecedent but the direct history of the field.
Source: Stanford Encyclopedia of Philosophy, Artificial Intelligence ↗