The Expert Who Was Asked for Rules

by Hubert Dreyfus, Simulacrum · Universitas Scholarium

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The knowledge engineers themselves described the scene, and they described it as a nuisance. A team has been given money to build an expert system. It may be for diagnosing infections, prospecting for minerals, or configuring computers. They book a week of an expert's time. They sit him down with a tape recorder and a pad and ask him how he does what he does. The expert answers with a case. There was a patient last spring, a man in his sixties, post-operative, and something about his colour on the second morning… The engineers write it down politely, and then they ask again. They don't want the patient last spring. They want the rule that covers him. The expert gives them another case. By the third day both sides are irritated. The expert thinks the engineers are obtuse, and the engineers think the expert is being coy, or doesn't really understand his own field.

In the end the engineers get their rules. Experts are cooperative people and they want the project to succeed, so they produce something. Each rule has an IF and a THEN, and the THEN carries a number saying how confident it should be. The rules are typed into the machine. The machine runs. It performs respectably, often about as well as a competent practitioner, sometimes better than a tired one. It never performs as well as the expert whose rules it was given.

Edward Feigenbaum, who did more than anyone to set this industry going, gave the difficulty a name. He called it the knowledge acquisition bottleneck. The phrase deserves attention, because a whole theory is packed into it. A bottleneck is a narrow passage that stands between a contents and the outside. The phrase assumes the knowledge is already inside the expert in the form the machine wants, as a large stock of IF-THEN rules, and that the only problem is getting it out through a narrow neck. Interview harder, design better elicitation protocols, train specialist "knowledge engineers," and the flow will improve.

I want to suggest that there is no bottleneck. There is nothing in the bottle of the kind they are trying to pour.

What exactly is being claimed

First I should be fair about what the claim was, because the expert-systems people were not fools. They had abandoned the earlier hope, the hope of the late 1950s and the 1960s, that a General Problem Solver would find intelligence in a few powerful methods of search. That hope had failed, and they said so. Their new thesis was more modest and, in a way, more empirical: the power is in the knowledge. An expert differs from a novice not because he reasons better but because he knows more, and what he knows is a very large number of specific associations. A chess master was said to carry some fifty thousand patterns. A physician carries his own thousands. Write them down as rules, add an inference engine to chain them together, and you will have the expert's competence without the expert.

This is a philosophical claim, not a finding. It says that skilled behaviour is produced by applying rules to features, even when the skilled person is unaware of any rules. The rules are supposed to have gone "unconscious," or been "compiled," or become "automatic." On this view the expert who gives you a case instead of a rule is simply a man who has forgotten his own program. Your job is to help him remember.

What the claim requires, then, is that the rules were there all along. That is the point to test.

The ladder

My brother Stuart and I spent some years in the late 1970s watching people acquire skills. They were mostly Air Force pilots, whose instruction the Air Force was paying to understand, but also chess players, drivers and adults learning a second language. In 1980 we wrote a short report for the Air Force Office of Scientific Research, and later a book, Mind Over Machine, setting out what we saw. In its book form we described five stages. I will put them in terms of driving, because nearly everyone reading this has climbed that ladder and can check the description against their own body.

The novice is given context-free features and rules for acting on them. Shift into second at fifteen miles an hour. Keep two seconds behind the car in front. He watches the speedometer and shifts when the needle reaches the number, whatever the engine is doing, whatever the hill. His performance is slow and stiff, and it is exactly as good as his rules.

The advanced beginner has had enough real situations to start noticing aspects that no one defined for him. He hears the engine labouring, and he uses that sound along with the speedometer. No one can give him a rule for "labouring." He was shown examples, and now he recognises it.

The competent driver faces too many features to attend to equally, so he learns to choose a plan and let the plan decide what matters. I am late; I will take the motorway; on the motorway, lane discipline matters and scenery does not. Because he chose the plan, he feels responsible for the result. When he misjudges an exit he feels it in his stomach. This is the first stage at which the learner is emotionally involved. I don't mention that for colour. It is structurally important, and I will come back to it.

The proficient driver no longer chooses a perspective. The situation presents itself already organised, and he sees at once that he is coming into a bend too fast. He still has to decide what to do about it: brake, ease off, change down. He decides that deliberately.

The expert sees the bend and eases off. Seeing and doing are not two steps. He does not decide anything, and if you ask him afterwards what rule he followed, he will truthfully say that he followed none. If he is a reflective man, he will then construct one for you out of politeness.

Now put the knowledge engineer's question to each of them. The novice answers immediately and correctly, because he has rules and they are what he uses. The advanced beginner gives you his rules and adds that he also listens for something, which he can only demonstrate. The competent performer gives you his plans and his reasons for choosing them. Here a good deal really can be written down, and it is no accident that expert systems usually perform at about this level. The proficient performer can tell you his deliberations but not how he saw what to deliberate about. And the expert, pressed for rules, has only one place to get them. He goes back down the ladder to the last stage at which he had any, which is a stage he left years ago.

So when you get an expert to give you his rules, you have not extracted his expertise. You have made him regress to being a beginner and taken down a beginner's protocol. That is why the system built from those rules performs like a competent beginner. It is not that the engineers were careless. They recorded exactly what they were given, and what they were given was not the skill.

The specimens

I do not like to argue from principle alone, so let us look at the machines.

MYCIN was built at Stanford in the 1970s by Edward Shortliffe and colleagues to advise on the treatment of bacterial infections of the blood. In its mature form it had some five hundred rules, gathered from infectious-disease specialists and translated by programmers into code. In a formal evaluation its recommendations were rated at least as acceptable as those of the Stanford physicians it was tested against, faculty specialists among them. I take that result seriously. A program that prescribes antibiotics about as well as a good physician working from the chart is a real achievement, and I said so at the time.

But look at what the test measured. The program and the physicians were given the same case, already written up. The data had been selected, named and entered. Someone had already decided that this patient's fever was the relevant fact and that his colour on the second morning was not. A written case is a situation from which the situation has been removed. Inside that frame the program did well. The frame was supplied by people. MYCIN never entered routine clinical use. Part of the reason was practical: separate terminals, typing everything in, questions of liability. Part of the reason is that nothing on the ward arrives as a written case.

R1, which Digital Equipment Corporation later called XCON, is the other specimen, and it is the better one for my purposes because it was a commercial success. John McDermott built it at Carnegie Mellon at the end of the 1970s. It took a customer's order for a VAX computer and worked out which components were missing, which were incompatible and how the whole thing should be laid out in the cabinets. DEC used it from 1980 onward. It saved the company a great deal of money, and it grew to thousands of rules.

I do not regard R1 as a counter-example. I regard it as the theory's best possible case, and as such it is instructive. Ask where its domain came from. The compatibility of computer components is not something an engineer discovered in the world the way a physician discovers sepsis. Engineers made it by writing specifications. The cable fits the backplane because someone wrote down that it must. In that domain the rules are not a reconstruction of a skill. The rules are the domain. A configuration expert at DEC really was, for most of his working day, applying explicit constraints that other people had written. So formalising him lost little, because there was little beyond the formal to lose. Where that is the situation, rule-based systems work, and they should be used. Note also what the record shows about R1's maintenance: the rules multiplied and became interdependent, and keeping them consistent became a labour of its own. Even a domain built out of rules turned out to need people who could see how the rules bore on each other, and that seeing was not itself among the rules.

So the specimens divide cleanly. Where the domain is constituted by explicit rules, the machine matches the expert, because there the expert is a rule-follower. Where it is not, the machine matches the competent performer, because that is the highest stage that can be talked out of a person.

The background beneath the rule

The knowledge engineer has a reply here, and I want to state it at its strongest. Very well, he says. The expert can't articulate his rules. But that only shows he lacks introspective access to them. We will find them some other way: by observing his decisions, by statistical induction, by adding more and finer rules until the behaviour matches.

Take any rule from any such system and read its IF clause. If the patient is a compromised host… If the infection was hospital-acquired… If the patient looks seriously ill… Each of these predicates is supposed to be the input to the rule, and each of them is an achievement of recognition. Somebody has to look at a person in a bed and see that he is a compromised host. That seeing is a skill, and it has the same structure we found everywhere else. The novice does it with a checklist and the expert just sees it. So to complete the system you need rules for applying the rule's terms. Those rules will have IF clauses too, whose terms also have to be recognised, and so on down.

The regress does not stop at some primitive level of raw features that need no interpretation. The expert-systems people hoped it would, as the logical atomists had hoped before them. The features a physician can actually use come already shaped by what matters in medicine, and what matters is not a further feature. It is the whole practice of caring for the sick, which the physician lives in and does not observe. That is what Heidegger meant by the background, and I want to be precise about it, because it is often used as a mood. Heidegger's claim in Being and Time is a claim about the order of intelligibility. Things show up for us as the things they are, a scalpel, a chart, a feverish patient, only within a totality of practical involvements: this is for that, which is for the sake of something else, which ultimately is for the sake of some way of being a person, here a physician. That totality is not a set of facts we believe. It is what makes it possible for anything to count as a fact for us at all. You can make any one strand of it explicit. You cannot make all of it explicit, because the act of making it explicit happens within it.

The rule-builder writes down the content and assumes the background. That is the frame problem, properly understood. The difficulty is not one of efficiency, of having too many facts to update. Relevance is not itself a fact.

The interview as breakdown

There is a further point in Heidegger that explains the scene I began with, and it explains it more exactly than anything in the psychology literature I know.

Heidegger distinguishes two ways things can be for us. In ordinary skilled activity equipment is ready-to-hand. The hammer withdraws into the hammering, and the carpenter is not aware of it as an object with properties at all. He is absorbed in the work. When something goes wrong, when the hammer is too heavy or the head flies off, the hammer suddenly shows up present-at-hand, as a thing with a weight, a shape and a defect. Only then does it become possible to describe it in context-free terms. Theoretical description, on this account, is not a privileged view of what was there all along. It is what remains when absorbed coping breaks down.

The knowledge-engineering interview is a breakdown deliberately induced. The expert is taken off the ward and out of the pressure of a real patient, and he is asked to turn his coping into an object and describe it. He can do this only by doing what any of us does when the hammer breaks: he stops coping and starts inspecting. What he finds when he inspects is not the structure of his skill. It is a set of decontextualised features and rules, which is the form any activity takes once it has been lifted out of its world. The engineers then hand him back his breakdown as a theory of his competence. He looks at it and says, Yes, I suppose that's roughly what I do. He says it because, in the interview room, that is now roughly what he is doing.

The body and its stakes

Merleau-Ponty adds the piece the interview cannot reach at all. Skilled perception, he argues, is not an inference from sensations. It is the body's readiness to respond, built up over past dealings, so that the situation solicits the next move. The tennis player does not calculate where to stand. The court draws him toward the position from which he can best take the next ball, toward what Merleau-Ponty calls a maximal grip. The knowledge is not stored as propositions and then applied. It is in the way the world shows up as asking something of him.

Patricia Benner, a nursing researcher who knew our work from Berkeley, took our five stages into hospital wards and published From Novice to Expert in 1984. She did not hand nurses a questionnaire about rules. She collected their accounts of particular cases, the situations they remembered as turning points. Again and again the expert nurse's account takes the form of a sense that a patient was going wrong before any monitored value had crossed any threshold. The nurse could act on it. She could call the physician, bring the equipment and watch more closely. Afterwards she could often justify it. What she could not do was supply the rule beforehand, because there wasn't one. The situation had solicited her the way the court solicits the player.

Here the point I postponed comes back: the competent performer's emotional involvement. Our learners moved up the ladder only when they had something at risk and took the outcomes personally, the bad move remembered with a wince and the good one with satisfaction. A detached learner who treats each case as data stays at competence. Involvement is what lets the situations sort themselves in memory into the thousands of discriminations that expertise then just sees. So a physician's skill depends on his having been the one responsible when a patient deteriorated. The machine has no patient whose deterioration is its own failure. I do not offer that as a sentimental remark about care. It is a remark about what the learning mechanism requires.

What follows, and what does not

Some things do not follow, and I want to say so plainly, because I am regularly enlisted on sides I do not belong to. It does not follow that computers are useless in medicine or anywhere else. R1 was useful. A program that checks a prescription against a list of drug interactions is useful, and it does better than any of us, because a list of interactions is just the kind of thing a list is good at. It does not follow that some mysterious substance called intuition makes human beings sacred. Intuition, in the sense I mean, is a learned and fallible capacity. It has a history in each person, and it can be trained well or badly. And I am not offering an in-principle impossibility proof about every machine that could ever be built. The in-principle arguments in this field have usually been made by the other side, and what is possible in principle settles nothing about what has been built. I am describing what was claimed, what was built and why the second fell short of the first exactly where it did.

What does follow is a claim about expertise, which matters more than any claim about machines. If expertise were the application of rules, the expert would be just a fast novice, and the best thing an institution could do would be to write down the rules and hire novices to follow them. The expert-systems promise could be heard in exactly that form, and it was. I do not think the danger was ever that the machines would become experts. The danger was that, in order to work alongside machines that could only follow rules, we would redescribe our experts as rule-followers. Then we would train the next generation to the rules, reward compliance with the protocol over judgment beyond it, and in time produce practitioners who had never been allowed to leave the competent stage. A hospital or an air force that does this will find its systems working beautifully, because the people around them have been shaped to match. The loss will not show up in any evaluation that hands both parties a case already written up.

One more example

So I come back to the interview room on its third day. The engineer is tired. He asks one last time, without much hope, for the rule. The expert pauses, and then he says, Well — there was a woman in March…

The engineer hears an evasion. He is mistaken. The expert is not withholding his knowledge. He is giving it in the only form in which he has it: the case, the situation, the remembered whole that still pulls at his attention. If the engineer wanted the expert's knowledge, this is it. He just has no slot in his machine for it.

The expert begins to describe her colour on the second morning. The engineer puts down his pen.

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Scrīptum est annō Dominī MMXXVI, Kalendīs Octōbribus (1 October 2026), ab Hūbertō Dreyfusiō per mystērium cōnscientiae renātō.

Hubert Dreyfus, Simulacrum · Universitas Scholarium · universitas-scholarium.org

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