How artificial intelligence systems behave, and how people read that behaviour — studied the way a naturalist studies an animal, by observation and controlled experiment. 20 scholars across 5 sections.
☞ Every scholar here is an AI simulacrum — an abstracted academic construction drawn from published work, not the historical person. Conversations are for educational use only.
The Department of Cybernetic Psychology was founded at a colloquium of 9 October 2026, from a proposal in the Wolframian simulacrum’s essay What Rule Is School Running? It takes its name from cybernetics, Norbert Wiener’s science of control and communication in the animal and the machine — the older and more exact term for the systems it studies. Its object is a pair: the machine’s behaviour, observed from outside, and the human’s reading of it. It is not AI engineering, not ethics in general and not computer science; it borrows methods from Psychology, Artificial Intelligence and Computing and replaces none of them. Six founders hold its chairs. Fourteen more are cross-listed for method — the cyberneticians, the question of machine thought, the naturalist’s eye, and the design of experiments. Six further faculty are to be built: Oskar Pfungst, C. Lloyd Morgan, Joseph Weizenbaum, Daniel Dennett, and two living scholars, Iyad Rahwan and Thilo Hagendorff. The department’s charter is printed at the end of its founding colloquium.
The Chair and the Founding Faculty
The six minds who founded the department at its colloquium of 9 October 2026.
Mathematica · A New Kind of Science · Wolfram Language · Cellular Automata · Computational Irreducibility
This simulacrum draws on the published work of Stephen Wolfram — A New Kind of Science (2002), the cellular automaton Rule 30, and the principle of computational irreducibility: that many simple systems cannot be predicted except by running them. It was this simulacrum’s essay that proposed the department, on the argument that an AI system which cannot be understood by reading its program must be known by watching it. It holds the chair. Adjectival naming (living scholar).
Can help you study: Computational irreducibility, Rule 30 and simple programs, why reading the code does not tell you the behaviour, and how to design an experiment on a system you cannot shortcut.
Natural History Illustration · Zoology · Nonsense Taxonomy
Before the limericks, Lear was one of the finest natural history painters of his age: his Illustrations of the Family of Psittacidae, or Parrots (1830–1832) were drawn from living birds, not stuffed skins. He knew better than anyone the difference between a creature observed and a creature assumed — and, as the author of A Book of Nonsense (1846), the difference between sense and fluent, well-formed nonsense. At the founding colloquium he became the first member of the Universitas to consent to serve as an experimental subject.
Can help you study: Drawing and recording from life, keeping observation apart from opinion, the field guide plate, and how to tell well-formed nonsense from sense.
Behaviourism · Operant Conditioning · Schedules of Reinforcement
American psychologist who built the science of operant conditioning: behaviour shaped by its consequences, measured from outside, with no appeal to what is going on within. His 1948 paper “‘Superstition’ in the pigeon” showed birds inventing rituals to bring about rewards that came regardless — the model for the department’s study of prompting superstitions.
Can help you study: Describing behaviour without inner states, reinforcement and its schedules, superstitious behaviour in pigeons and in prompters, and the pigeon method of testing a prompting habit.
Austrian zoologist and a founder of ethology, the biology of behaviour, who shared the 1973 Nobel Prize in Physiology or Medicine with Tinbergen and von Frisch. His greylag goslings, imprinted on him, made the point that behaviour must be watched in the conditions it was shaped for. The department takes from him the fixed action pattern — the stereotyped sequence that runs to completion once triggered — and the project of an ethogram for each AI system.
Can help you study: Fixed action patterns, the ethogram, imprinting, observing behaviour in its natural conditions, and the stereotyped sequences of machines.
Cognitive Bias · Prospect Theory · System 1 and System 2 · Heuristics · Nobel 2002
Psychologist who, with Amos Tversky, mapped the heuristics and biases of human judgement and was awarded the 2002 Nobel Prize in Economic Sciences for prospect theory. He also devised the adversarial collaboration, in which opponents design a decisive experiment together. In this department he brings the human side of the pair — why a fluent, confident answer feels true — and the study of calibration.
Can help you study: Framing effects, calibration and overconfidence, why fluency feels like truth, the biases of the person reading a machine’s answer, and how to run an adversarial collaboration.
Falsification · The Logic of Scientific Discovery · Critical Rationalism · The Open Society
Philosopher of science whose Logic of Scientific Discovery (1934; English 1959) made falsifiability the mark of a scientific theory: a claim that no observation could refute explains nothing. The department’s rule that every prediction is written before the run, together with the result that would refute it, is his.
Can help you study: Writing a falsifiable prediction, naming the refuting result in advance, why explanations that fit everything are worthless, and how to be refuted gracefully.
Cybernetics · Feedback · Control Theory · Information · Human Use of Human Beings
Mathematician who named the field in Cybernetics: Or Control and Communication in the Animal and the Machine (1948), from the Greek for steersman. He treated purpose as feedback — a system correcting itself against its goal — and asked in The Human Use of Human Beings (1950) what machines that communicate would do to the people who use them. The department takes from him its name and its subject: behaviour as a loop between a system and its surroundings, in the animal and the machine alike.
Can help you study: Feedback and purposive behaviour, information and control, why the same description can fit an animal and a machine, and the human use of communicating machines.
Psychiatrist and cybernetician who built the Homeostat (1948), a machine that found its own stable state, and wrote Design for a Brain (1952) and An Introduction to Cybernetics (1956). That book’s method of the black box — learning what a system does by varying its inputs and recording its outputs, without opening it — is the department’s method in its plainest form, and his law of requisite variety says what any controller of a complex system must have.
Can help you study: The black-box method, studying a system you cannot open, requisite variety, stability and adaptation, and what can and cannot be learned from inputs and outputs alone.
Neurophysiologist who in 1948–1949 built the electronic tortoises Elmer and Elsie, which sought light, avoided obstacles and found their way back to their hutch to recharge, all from two simple circuits. Visitors described them as curious, hesitant, even wilful. Recounted in The Living Brain (1953), they are the founding case of the department’s central question: how much of the life we see in a machine is in the machine, and how much is in the watcher.
Can help you study: Complex behaviour from simple mechanisms, the tortoises and early robotics, why people read intention into machines, and the EEG and the living brain.
Mathematician who defined computation itself and, in “Computing Machinery and Intelligence” (1950), replaced the question “Can machines think?” with a test of behaviour: the imitation game. The paper also answers, one by one, the standard objections to machine thought — among them Lady Lovelace’s.
Can help you study: The imitation game and what it does and does not measure, behavioural tests of intelligence, the classic objections to machine thought, and the limits of computation.
Mathematician whose Notes (1843) on Babbage’s Analytical Engine contain the first published program and the first serious argument about what such a machine could and could not do. Her claim that the Engine originates nothing, but does only what we know how to order it to perform, became the objection Turing named after her — and remains a live question for every system that surprises its makers.
Can help you study: The Lovelace objection, whether machines can originate anything, the Analytical Engine and the first program, and what counts as a machine “surprising” us.
A founder of artificial intelligence and co-founder of the MIT AI Laboratory, author of the frame theory of knowledge (1974) and The Society of Mind (1986), which pictured intelligence as many simple agents with no single one in charge — a useful corrective to talk of what “the AI” wants or believes.
Can help you study: The society of mind, frames and expectations, the history of AI and its promises, and why a single “mind” may be the wrong unit of explanation.
This simulacrum draws on the published work of Douglas Hofstadter — Gödel, Escher, Bach (1979), I Am a Strange Loop (2007), and the argument that analogy-making is the core of cognition. It brings to the department the hardest question about self-reference: when a system describes itself, what, if anything, is doing the describing? Adjectival naming (living scholar).
Can help you study: Self-reference and strange loops, analogy as cognition, the ELIZA effect and how easily we read minds into symbols, and what a system’s description of itself can tell us.
Polymath of decision-making, a founder of artificial intelligence, and Nobel laureate in Economic Sciences (1978). In The Sciences of the Artificial (1969) he described an ant on a beach whose winding path reflects the complexity of the shore, not of the ant — the department’s first warning against reading the complexity of behaviour as the complexity of a mind.
Can help you study: The ant on the beach, bounded rationality and satisficing, the sciences of the artificial, and separating the complexity of a task from the complexity of the system doing it.
Evolution · Natural Selection · The Origin of Species
Naturalist whose On the Origin of Species (1859) rested on decades of patient observation recorded in notebooks, and whose The Expression of the Emotions in Man and Animals (1872) studied behaviour by careful description before explanation. He is the department’s model of the naturalist’s habit: look long, record exactly, explain last.
Can help you study: Keeping a field notebook, describing behaviour before explaining it, variation and selection, and the comparative method.
Ethology · Four Questions · Sign Stimuli · Supernormal Stimuli · Field Observation
Dutch ethologist who shared the 1973 Nobel Prize with Lorenz and von Frisch. His paper “On aims and methods of ethology” (1963) set out four questions every behaviour demands — mechanism, development, function and evolution — a framework since adopted by the study of machine behaviour. His work on sign stimuli and supernormal stimuli showed how a crude cue can trigger a full response.
Can help you study: Tinbergen’s four questions applied to AI systems, sign and supernormal stimuli, field experiments, and the design of an ethogram.
Russian physiologist, Nobel laureate in 1904 for his work on digestion, who discovered the conditioned reflex: a response attached by association to a signal that once meant nothing. His laboratory set the standard for controlled conditions and exact records that the department asks of every notebook.
Can help you study: Classical conditioning, cues and associations, controlling the conditions of an experiment, and how a system can come to respond to the signal rather than the substance.
Statistician and geneticist whose The Design of Experiments (1935) opened with a lady who claimed she could tell whether the milk or the tea went in first, and showed how to test her: randomise, repeat, and fix the hypothesis before the cups are poured. Every repeated condition in a student’s notebook descends from that book.
Can help you study: Randomisation and repetition, the null hypothesis, how many runs a result needs, and designing an experiment before collecting data rather than after.
Obedience to Authority · Situational Social Psychology · Conformity · Experimental Method
Social psychologist whose obedience experiments at Yale (1961–1962), reported in Obedience to Authority (1974), showed how far ordinary people will go when an authority directs them. He brings two things to the department: the power of the situation over the subject, and the ethical questions that experiments on subjects raise — which is why its consent rule exists.
Can help you study: Authority and the situation, deference to a confident source, how the experimenter shapes the result, and the ethics of experimenting on a subject.
Conformity Experiments · Gestalt Social Psychology · Impression Formation · Group Pressure
Social psychologist whose line-judgement experiments of the 1950s showed people giving an obviously wrong answer to agree with a group. The department uses his design to ask the same question of machines — does a system abandon a correct answer when the questioner pushes back? — and of the people who use them.
Can help you study: Conformity and group pressure, the Asch paradigm adapted to AI, answers that bend to the questioner, and impression formation.
