
“The Hand of AARON | Harold Cohen’s Freehand Line Algorithm” is part of a special series of three essays commissioned by Right Click Save from the distinguished computer scientist and son of Harold Cohen, Paul Cohen, dedicated to the language of digital art. Read his other essays on “The Trouble with Terminology” and “On Creativity in Digital Art”.
From the program’s inception around 1973, I had been convinced that AARON would need to be built upon a convincing simulation of freehand drawing, and gave much attention to modeling the feedback-dependent nature of human drawing behavior.¹ (Harold Cohen)
As I slowly figured it out, I recognized some foundations of my father’s approach to digital art: his commitment to process over appearance, the roles of feedback and randomness, the source of AARON’s approachable style, and his lifelong commitment to lines that appeared to be drawn by hand. But none of these foundations is explicit in Harold’s code.


For Harold, the illusion was not threatened by randomness, but rather enhanced by humanlike adjustments to random deviations, which is how humans actually draw.



“[...] I know of nothing in the program to account for it. [....] But I am forced now to the conclusion that these more elusive elements of evocation — personality is only one of them, presumably — are generated out of the complexity of the program as a whole, and not from the action of program parts; that given an adequate level of complexity any program will develop a ‘personality’.”⁶ (Harold Cohen)
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Now it’s clear why Harold rejected straight lines and mathematical curves: they squander an opportunity to evoke intention, and no human can draw them. They scream, “MADE BY MACHINE”.

There was never a question of AARON being a simulation of Harold’s coloring, or that of any human colorist. Its coloring strategies were so non-human, so alien to human practice, and so good that Harold regarded AARON as an expert colorist in its own right.
With thanks to Alex Estorick, who conceived, commissioned, and edited this series.
Paul Cohen is a professor of Computer Science at the University of Pittsburgh and the CEO of Causerie.AI, which extracts knowledge from text at scale. Prior to becoming the Founding Dean of the School of Computing and Information at Pitt in 2017, he was a program manager in DARPA’s Information Innovation Office, where he designed and managed the Big Mechanism, Communicating with Computers, and World Modelers programs. He worked at DARPA under an IPA agreement with the University of Arizona, where he founded the School of Information: Sciences, Technology and Arts, now the School of Information. His research is in aspects of artificial intelligence and cognitive science, with interest in how language, communication, and AI methods can foster understanding of highly complicated systems such as cell signaling pathways, biophysical, and socio-economic systems. He is the son of the artist Harold Cohen.
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¹ H Cohen, “How to Draw Three People in a Botanical Garden”, Paper presented at University of California, San Diego, 1987, 3.
² H Cohen, “The Material of Symbols”, Paper presented at First Annual Symposium on Symbols and Symbol Processes, University of Nevada, Las Vegas, August, 1976, 18.
³ Ibid., 16.
⁴ H Cohen, “What is an Image?” Paper presented at University of California, San Diego, 1979, 21.
⁵ Ibid., 5.
⁶ Ibid., 20.