AI: from ancient times to present day

6 September 2023 – Vol 1, Issue 1.

The desire to create intelligent machines is not a new phenomenon. Throughout history, people have been fascinated with the idea of crafting objects that could mimic human intelligence or perform autonomous tasks. From the ancient Greek myth of Talos, a bronze automaton, to Leonardo da Vinci’s intricate designs of humanoid robots, the ancient world was filled with concepts and attempts that can be considered prototypical Artificial Intelligence (AI). These ideas were not technological realities back then, but rather they were powerful expressions of human imagination and innovation (Buchanan, 2005).

This interest in creating machines that are more capable than humans is based on a human desire to transcend limitations. Whether it’s predicting the future, answering complex questions, or performing tasks beyond human capability, there has always been a longing to create powers that go beyond our natural abilities. This longing has been manifested in myths, legends as well as the relentless scientific pursuit of technological advancements (Mijwel, 2015).

'Laptops by the Acropolis’ by Gil and Natalie Dekel and image-generating AI, 2023.

‘Laptops by the Acropolis’ by Gil and Natalie Dekel and image-generating AI, 2023.

The Enlightenment era and the advent of the mechanical age saw a renewed interest in automatons and other complex machinery. Inventors and engineers of the time, like Jacques de Vaucanson or Alexandre Nicolas Théroude, were pushing the boundaries of what machines could achieve. These creations were not intelligent in the way we understand AI today, but they represented significant strides in human ingenuity and the continued pursuit of creating machines that could emulate human-like functions (Zielinski, 2013).

The librarian automaton: ancient AI in mythology

An early representation of artificial intelligence is found in the Librarian Automaton, in Greek mythology. Crafted by Hephaestus, the god of blacksmiths, the Librarian Automaton embodied a vast amount of knowledge. Likewise, modern AI systems, especially those based on neural networks, establish connections between vast amounts of data.

At the core of the Librarian Automaton was a celestial database, managed by an intricate network of gears and cogs that formed a complex web of connections, allowing it to retrieve information with precision. Likewise, neural networks, inspired by the human brain’s neural architecture, recognise patterns and relationships within data (Mayor, 2019).

The Librarian Automaton’s ability to connect seemingly unrelated pieces of knowledge provided the automaton with an understanding of various subjects, making it a revered advisor to the gods. Drawing on its vast memory, the automaton could draw connections between seemingly disparate events, offering insightful new perspectives on matters of fate, strategy, and diplomacy. Likewise, modern AI technologies can scan vast amounts of data, and make connections that humans may not be able to achieve (Klancar, Zdesar, Blazic and Skrjanc, 2017).

The parallel between the complex web of connections in the automaton and AI’s data-connecting capabilities underscores the shared pursuit of knowledge acquisition through intelligent design.

In the myth, sacred symbols were engraved on the automaton’s gears. These symbols held specific meanings that unlocked access to divine knowledge. Similarly, in the realm of AI, programming languages serve as the key to unlocking the vast reservoir of information contained within machines. Coding in languages like Python or Java enables AI systems to interpret, analyse, and process data, analogous to how the sacred symbols in ancient myths unlocked the automaton’s repository of knowledge. Both the sacred symbols and modern programming languages represent a linguistic bridge that connects human intent and technological capabilities (Evans, 2017).

Al-Jazari: inventor of the first prototypical AI from the Middle East

Al-Jazari was a medieval Islamic scholar, inventor, engineer, and artist who lived during the 12th century in what is now modern-day Turkey. He is renowned for his work on mechanical devices, which he meticulously documented in his famous book, ‘The Book of Knowledge of Ingenious Mechanical Devices’ (Hill, 2012).  Though far from modern artificial intelligence, his inventions reveal an early interest in automation and mechanical control that shares intriguing parallels with contemporary AI (Parra Pennefather, 2023).

One of Al-Jazari’s notable inventions was a mechanical water clock that used gears, floats, and other mechanisms to track time in an elaborated and visually fascinating manner. His clocks were not only functional but were artistic masterpieces, incorporating intricate design elements. These creations required an understanding of physics, mathematics, and engineering, which altogether laid the groundwork for later developments in mechanics and automation (Yassi, 2017).

In addition to his clocks, Al-Jazari designed numerous automatons, including robotic musicians, waiters, and even a hand-washing machine with humanoid figures. His designs for programmable automatons, driven by pegs and levers, could perform a sequence of actions based on a set pattern. This concept bears a resemblance to modern programming, where algorithms execute a series of operations based on predefined instructions (Dirik, 2023).

Al-Jazari’s work demonstrates a deep fascination with the replication and automation of human-like actions and natural processes. Not only he created machines that carried out specific tasks but also provided them with aesthetic qualities and human-like appearances. His focus on integrating form, function, and beauty in mechanical devices resonates with contemporary efforts in AI to create human-like robots and intelligent systems that can interact naturally with their surroundings.

The Jewish Golem: ancient AI in folklore

Rabbi Judah Loew ben Bezalel, the Maharal of Prague, is credited with creating the most famous Golem in the late 16th century. Drawing upon his deep knowledge of Kabbalah, the mystical branch of Judaism, Rabbi Loew created a giant that acted upon orders as a defender of the community (Idel, 1990).

In this folklore tale, Rabbi Judah Loew performs a ritual drawing upon Kabbalistic knowledge. He places the sacred name of God, written in Hebrew, under the tongue of the clay figure, thus infusing it with life.

In Kabbalah, Hebrew letters and words hold mystical significance and are believed to possess divine energy. The arrangement and combination of these letters enable practitioners to invoke divine attributes and alter reality. By using the sacred name of God, Rabbi Loew bridges the gap between the spiritual and material realms, breathing life into the Golem through language.

In the myth of the Golem, the sacred name of God acts as the catalyst for its animation. Similarly, in AI, the prompts (‘instructions’) provided by users act as the catalyst that triggers responses. While the sacred name of God holds divine power, AI prompts harness the power of human language to evoke meaningful interactions with the machine (Glinert, 2001).

Jacques de Vaucanson’s and Nicolas Théroude’s automatons

Jacques de Vaucanson was an 18th-century French inventor and artist known for his work in creating mechanical automatons that imitated human or animal actions. While far from being what we consider AI today, his creations exhibited an early exploration of mechanical automation that can be paralleled to contemporary AI. Similar to AI’s information network, Vaucanson’s was attempting to develop automatons that emulate the transmission of information through the nervous system (Moran, 2007).

One of Vaucanson’s most famous inventions was a mechanical duck, known as the ‘Digesting Duck’. This automaton could flap its wings, quack, and simulate eating grains and digestion. Though it did not truly digest food, the complex series of mechanical interactions mimicked the process in a realistic way. Vaucanson’s work was more than mere spectacle; it represented a serious investigation into the mechanics of life and a desire to automate complex tasks. His automatons were not only artistic achievements but scientific and engineering innovations that inspired further developments in mechanics and automation (Wang, 2020).

Another remarkable result of engineering and craftmanship is from the 19th century – a flute-playing automaton, designed by the French craftsman Alexandre Nicolas Théroude. Designed with intricate mechanisms, this automaton could mimic the nuanced actions of a human flutist, producing melodies with precision and fluidity. As it played, its fingers would move adeptly over the flute, and its chest would rise and fall to simulate breathing, adding resemblance with a real flutist (Zielinski, 2013).

The philosophical and technical implications of Vaucanson and Théroude’s work continue to echo in today’s discussions about AI, robotics, and the very nature of intelligence and creativity. Their automatons can be seen as a testament to human creativity and engineering talents, and an early quest to explore and replicate intelligent behaviour through mechanical means (Ahmed, 2023).

Alan Turing’s cryptanalysis and ‘Turing Test’

Alan Turing, often referred to as the “father of modern computing,” was a British mathematician, logician, and computer scientist whose work has had a profound influence on the development of computer science and artificial intelligence. Born in 1912, Turing’s early work in the realm of mathematical logic set the stage for what would later be recognised as pivotal contributions to the theoretical foundations of computation. His conceptualization of the ‘universal machine’ laid the groundwork for the modern computer, making it possible to envision a machine capable of executing any computable task given the right algorithms and configurations (Agar, 2017).

During World War II, Turing worked at the British codebreaking centre at Bletchley Park. Here, he played a key role in deciphering encrypted German messages, specifically those sent using the Enigma machine – a complex encryption device used by the German military. Turing and his team designed the Bombe, a machine tailored to decode Enigma-encrypted messages, significantly accelerating the codebreaking process. This accomplishment greatly contributed to the Allied forces’ ability to anticipate and counter German strategies. Similarly, it is widely acknowledged that Turing’s work shortened the war and helped save countless lives (Bowen, 2012).

Post-war, Turing shifted his attention to the burgeoning field of artificial intelligence and began pondering the question of machine intelligence. This led to the development of the Turing Test in 1950, which he proposed to determine whether a machine can exhibit human-like intelligence. The test involved a human evaluator engaged in a natural language conversation with both a human and a machine designed to generate human-like responses. If the evaluator could not reliably distinguish between the machine and the human, based solely on their responses, the machine was considered to have passed the test and demonstrated human-like intelligence (French, 2000).

While the Turing Test remains a topic of debate within AI circles, its introduction catalysed discussions about machine intelligence, consciousness, and the nature of cognition.


The transition from proto-AI concepts to modern AI has been fuelled by advancements in mathematics, computer science, and data technology. The 20th century saw the birth of formalized algorithms and computer systems, culminating in the creation of AI research as a distinct field. Alan Turing’s Turing Test laid a philosophical and practical foundation for evaluating machine intelligence. The progress from mechanical automatons to learning algorithms represents an incredible leap in our attempt to model and replicate human intelligence.

What the next century might hold? If history is any indication, our current understanding of AI may merely be a stepping stone to something far more profound and capable than ChatGPT or Midjourney – AI tools that exploded in popularity less than half a year ago. The quest for greater intelligence and predictive power seems destined to continue, guided by human curiosity and the relentless drive to explore the unknown. The future of AI is likely to be as fascinating and unexpected as its prototypical past.



Agar, J. (2017). Turing and the Universal Machine (Icon Science): The Making of the Modern Computer. Icon Books.

Ahmed, D. (2023). A History of Artificially Intelligent Architecture: Case Studies from the USA, UK, Europe and Japan, 1949–1987. Routledge.

Bowen, J.P. (2012). Alan Turing. The Scientists: An Epic of Discovery. Thames and Hudson, pp.270-275. Birmingham City University.

Buchanan, B.G. (2005). A (very) brief history of artificial intelligence. Ai Magazine, 26(4), pp.53-53.

Dirik, M. (2023). THE TECHNICAL INGENUITY OF AL-JAZARI AND ITS RELEVANCE TO CONTEMPORARY ENGINEERING AND DESIGN. Indonesian Journal of Islamic History and Culture, 4(1), pp.24-42.

Evans, G.W. (2017). Artificial intelligence: where we came from, where we are now, and where we are going. University of Victoria, the Department of Computer Science.

French, R.M. (2000). The Turing Test: the first 50 years. Trends in cognitive sciences, 4(3), pp.115-122.

Glinert, L. (2001, January). Golem! The making of a modern myth. In Symposium: a quarterly journal in modern literatures, 55(2), pp. 78-94.

Hill, P. (2012). The Book of Knowledge of Ingenious Mechanical Devices:(Kitāb fī ma’rifat al-ḥiyal al-handasiyya). Springer Science & Business Media.

Idel, M. (1990). Golem: Jewish magical and mystical traditions on the artificial anthropoid. State University of New York Press.

Klancar, G., Zdesar, A., Blazic, S. and Skrjanc, I. (2017). Wheeled mobile robotics: from fundamentals towards autonomous systems. Butterworth-Heinemann.

Mayor, A. (2019). Gods and robots: Myths, machines, and ancient dreams of technology. Princeton University Press.

Mijwel, M. M. (2015). History of Artificial Intelligence. College of science, University of Baghdad.

Moran, M.E. (2007). Jacques de Vaucanson: The father of simulation. Journal of endourology, 21(7), pp.679-683.

Parra Pennefather, P. (2023). Being Creative with Machines. In Creative Prototyping with Generative AI: Augmenting Creative Workflows with Generative AI, pp. 27-63. Berkeley, CA: Apress.

Yassi, Y. (2017). Al-Jazari’s Water Clocks: An Archaeological Reconstruction and Comparative Analysis of the Peacock Clock and the Dragon Clock. Nuncius, 32(1), pp.1-24.

Wang, Y. (2020). Jacques de Vaucanson (1709–1782)., Part 4, pp.15-46.

Wang, Y. (2020). Jacques de Vaucanson (1709–1782). Distinguished Figures in Mechanism and Machine Science: Their Contributions and Legacies In: Ceccarelli, M., Fang, Y. (Eds) History of Mechanism and Machine Science. Springer, Cham.

Zielinski, S. (2013). Expanded animation: A short genealogy in words and images. In: Buchan, S. (Ed) Pervasive Animation. Routledge.

About the authors

Doctor Gil Dekel holds a PhD in Art, Design and Media, from The University of Portsmouth. His speciality is in processes of creativity and inspiration in artmaking. Dr. Dekel is Associate Lecturer at the Open University, Reiki Master/Teacher, and a visionary artist. He co-wrote ‘The Energy Book’.

Ekaterina Pretsch, MS, is a graduate of the Blekinge Technical University in Karlskrona, Sweden. She received her Master’s degree in Strategic Leadership towards Sustainability in 2015. Since then, she has been working on the topic of sustainable development both in academia and corporate sector.