Author: Daniel Lemire

People design all the time: new cars, new software, new houses. All design is guided by constraints (cost, time, materials, space) and by objectives (elegance, quality). Constraints are limitations: you only have so much money, so many days… whereas objectives are measures that you seek to either maximize or minimize. In practice, either the constraints or the objectives may dominate. You are either worried about limited ressources, or you seek to maximize the quality of your result.

Our ancestors were probably often forced into scarcity-based design. When your very survival is in question, you build whatever shelter you can in the hours you have left before nightfall. We are probably wired for good scarcity-based design as it is a survival trait.

Any monkey can live in scarcity. However, abundance-based design is crucial if you want to maximize your impact.

Facebook engineers do abundance-based design. They are mainly worried about improving Facebook and pursuing objectives such as usability, but much less worried about time or disk space. Similarly, when I build a model sailboat, costs and time are nearly irrelevant, I mostly care that my boat be pretty and that it handles well. As a researcher, most of my research papers are the result of abundance-based design. It does not matter how long I work on the research projects, as long as the result has impact. Similarly, my blog is the result of abundance-based design. Nobody is forcing me to write on a regular schedule. And I have no set limit on the time I spend on my blog.

Many people choose to simulate scarcity-based design, maybe because it comes with an adrenaline rush. In fact, the adrenaline rush is good indication that you are in scarcity mode. You will often hear scarcity-based designers say that they are running of time, money or space. They may spend much time planning or worrying about costs and deadlines. There are many examples of artificial scarcity-based design:

• One of the great fallacies of software engineering is that what matters in the software industry is how long it takes and how much it costs. But anyone who has been in the software industry long enough knows that the real problem is that most software is bad. Some of it is atrocious. For example, Apple iTunes is a disgrace.  I don’t care whether the iTunes team finished on time and within budget. Their software is crap. They failed as far as I am concerned.
• Nobody cares how long it took  you to write your novel or research paper. Yet people sign deals with publishers with fixed deadlines and others choose to publish in conferences with fixed deadline. They create external pressure, on purpose.

Frankly, if you are a designer such as an artist, a fiction writer, a scientist or a scholar, you should have a feeling of urgency, not worry. A single strategy may suffice to put you in abundance mode:

• Reduce the quantity. Apple is well known for having few products. Despite having billions of dollars, they focus on few projects. And their new project have often fewer features than the competition. By focusing your attention, you ensure abundance. Don’t start more projects than you can’t execute with ease.

Further reading: Publishing for Impact by John Regehr and The merits of chasing many rabbits at the same time by Alain Désilets.

In my previous post, I argued that people who pursue double-blind peer review have an idealized “LEGO block” view of scientific research. Research papers are “pure” units of knowledge and who wrote them is irrelevant.

Let us take this LEGO block view to its ultimate conclusion.

If science is pure industry, producing standardized elements—called research papers, why should papers be signed as if they were pieces of art? The signature is obviously irrelevant. Nobody cares who made a given LEGO block. Thus, I propose we omit names from research papers. It should not change anything, and it will be fairer.

Indeed, why not have anonymous papers all the way? Journals could publish articles without ever telling us who they are from. We would ignore, for example, which papers were written by Einstein or Turing. How is that relevant? How does it help us to appreciate a given paper to know it was written by Turing?

What would we do for conferences? Because papers are standard units, people could attend conferences and be assigned a paper, any paper, to present. Presenting your own work is a bit too egotistical anyhow.

Of course, for recruiting or promotion purposes, we would need to be able to map research papers to individuals. But, because papers are standard units, all you care about is the number of papers and related statistics. Thus, an academic c.v. would not list research papers, but instead provide a key that could be used to retrieve productivity statistics.

Of course, this is not, even at a first approximation, how science works. Science is more art than industry. That is why we put our names on research papers. It does matter that it is Turing that wrote a given paper. It helps us understand the paper better to know its author, its date and its context. When I receive a paper to review, I try to see how the authors work, what their biases are.

Research papers present a view of the world. But like Plato’s cave, this view is fundamentally incomplete. If a paper report the results from some experiments they conducted, the paper is not these experiments: it is only a view on these experiments. It is necessarily a biased view. Do you know what the biases of these particular authors are?

Let us be candid here. When reviewing research papers, there is no such thing as objectivity. Some papers are interesting to the reviewer, some aren’t. What makes it interesting has to do with whether the world view presented is compatible with the reviewer’s world view. And because different individuals have (or should have) different world views, it does matter who wrote the paper even if we omit names. It helps me to find your paper interesting if I can put myself in your shoes, get to know who you are. An anonymous paper is far more likely to be boring to me, because it is hard to have empathy for the authors.

Some days, we all wish it did not matter who we are. Can’t people just look at our work on its own? You can get your wish by becoming a bureaucrat or a factory worker. Science is for people who want to see their name in print, people who want to build their reputation and cater to their inflated ego. In short, good science is interesting.

Originally, the term computer applied to human beings. These days, it is increasingly difficult to distinguish reliably machines from human beings: we require ever more challenging CAPTCHAs.

Machines are getting so good that I now prefer dealing with computers than bureaucrats. I much prefer to pay my taxes electronically, for example. Bureaucrats are rarely updated, and they tend to require constant attention like aging servers.

In any case, a bureaucracy is certainly an information processing “machine”. If each bureaucrat is a computer, then the bureaucracy is a computer network. What does Computer Science tell us about bureaucrats?

1. Bureaucracies are subject to the halting problem. That is, when facing a new problem, it is impossible to know whether the bureaucracy will ever find a solution. Have you ever wondered when the meeting would end? It may never end.
2. Brewer’s theorem tell us that you cannot have consistency, availability and partition tolerance in a bureaucracy. For example, accounting departments freeze everything once a year. This unavailability is required to achieve yearly consistency.
3. Parallel computing is hard. You may think that splitting the work between ten bureaucrats would make it go ten times faster, but you are lucky if it goes faster at all.
4. One the cheapest way to improve the speed of a bureaucracy is caching. Keep track of what worked in the past. Keep your old forms and modify them instead of starting from scratch.
5. Pipelining is another great trick to improve performance. Instead of having bureaucrats finish the entire processing before they pass on the result, have them pass on their completed work as they finish it. If you have a long chain of bureaucrats, you can drastically speed up the processing.
6. Code refactoring often fails to improve efficiency. Correspondingly, shuffling a bureaucracy is just for show: it often fails to improve productivity.
7. Bureaucratic processes spend 80% of their time with 20% of the bureaucrats. Optimize them out.
8. Know your data structures: a good organigram should be a balanced tree.
9. When an exception occurs, it goes back the ranks until a manager can handle it. If the CEO cannot handle it, then the whole organization will crash.
10. The computational complexity is often determined by looking at the loops. That is where your code will spend most of its time. In a bureaucracy, most of the work is repetitive.

Update: Neal Lathia commented that neither bureaucrats nor computers understand humor.

Update: “This is a fairly well-known model, and no it isn’t computer science that is at the root of what you are noticing. It is early operations research. Taylorism in fact. There was a conscious effort in the 20s and 30s to bring Taylorist style a…ssembly line/operations research thinking into white collar work, starting with organizing pools of typists, secretaries and other office workers the same way banks of machine tools were organized into flow shops and assembly lines. The exact same Taylorist time-and-motion study tools were applied (in fact, in the 30s this was so popular that women’s magazines carried articles about time-and-motion in the kitchen. Example: puzzles like “what’s the fastest way to toast 3 slices of bread on a pan that can hold 2 and toast 1 side at a time?) Computer science itself was initially strongly influenced by shopfloor OR… that’s where metaphors like queues come from after all.” (Venkatesh Rao)

Douglas Rushkoff wrote in Life Inc. that our society is nothing more than an operating system upon which we (as software) live:

The landscape on which we are living “the operating system on which we are now running our social software” was invented by people, sold to us as a better way of life, supported by myths, and ultimately allowed to develop into a self-sustaining reality.

In turn, operating systems are designed and maintained by engineers who make choices and have biases. He makes us realize that corporations, these virtual beings which live forever and are granted full privileges (including free speech), are not natural but are bona fide inventions. He also stresses that central currencies, that is, the concept that the state must have a monopoly on the currency, is also an invention: why is it illegal to switch to an alternative currency in most countries?

We fail to see these things, or rather, we take them for granted because they are our operating system. Someone used to Microsoft Windows takes for granted that a desktop computer must behave like Microsoft Windows: they cannot suffer MacOS or Linux, at least initially, because it feels instinctively wrong. Anyone, like myself, who uses non-Microsoft operating systems in a predominantly Microsoft organization is constantly exposing hidden assumptions. “No, my document was not written using Microsoft Word.”

Science has an operating system as well. One of its building block is traditional peer review: you submit a research paper to an editor who picks a few respected colleagues who, in turn, advise him on whether your work is valid or not. By convention, any work which did not undergo this process is suspect. In Three myths about peer review, Michael Nielsen reminded us that traditional peer review is not a long tradition, and is not how correctness is assessed in science. Gregori Perelman by choosing to forgo traditional peer review while publishing some of the most important mathematical work of our generation could not have made Nielsen’s point stronger. Similarly, we believe that serious academics must publish books through a reputable publisher: self-publishing a book would be a sure sign that you are a crank. Years ago, scholars who had blogs were clowns (though this has changed). We also value greatly the training of new Ph.D. students, even when there is no evidence that the job market needs more doctors. We value greatly large research grants, even when they take away great researchers from what they like best (doing research) and turn them into what they hate doing (managing research). But nobody is willing to question this system because the alternative is unthinkable. “You mean that I could use something beside Microsoft Windows?”

In my previous post, I challenged public education. Some people even went so far as to admit that my post felt wrong. I suspect that this feeling is not unlike the feeling one gets when switching from Windows to Linux. “Where is Internet Explorer?”

Several people cannot imagine that you can become smart without a formal education which includes at least a high school diploma. It is not that the counter-examples are missing (there are plenty: Bobby Fischer, Walt Disney, James Bach and Richard Branson). It is simply hard to imagine that you could do away with brick-and-mortal schools and still have scholarship and intelligence. Similarly, we cannot imagine a world without corporations or without central currency, or science without formal peer review.

Challenging preconceived notions is difficult because your feelings will betray you. Radically new ideas feel wrong. The cure is to try to remember how it felt like when you were first exposed to these ideas. On this note, Andre Vellino pointed me to Disciplined Minds, a book so controversial that it got its author fired! It reminded me of my feelings as a student about exams, grades and teachers:

• Exams and grades appear neutral: on the face of it, they are merit-based challenges. While in fact, they are really tests of conformity. To get good grades, you must organize much of your life around what others expect you to do. I cannot think of a good reason why most people would care about the integral of x³ cos(x). Why do we require such technical knowledge of so many people? The reason is simple: if you can set aside all other interests to learn calculus just because you are told to do so, then you are good at learning what you are told to learn. If you refuse to hand in an assignment because you think it is stupid, you will be punished. It does not matter if you use the free time to be even more productive on some valid scholarship.
• Teachers appear unpolitical at a first glance. They teach commonly accepted facts to students. However, teachers are political because they never challenge the curriculum, and when they do, they are frequently fired. As a kid, I refused to learn my multiplication tables. I was repeatedly chastised for failing to memorize them: instead, I would design algorithms to quickly deduce the correct answer  without rote memorization. This was called cheating, and my teachers would wait for the small pause and then interrupt me: “you are cheating again, you have to memorize”. I still have not memorized my multiplication tables. Why is it that no teacher ever opposed the requirement that we memorize multiplication tables? Because their job involves teaching obedience.

So, the same way corporations and central currencies are not neutral, public education is not neutral. Kids are naturally curious. If you leave them alone, they will learn eagerly. Alas, they will also refuse to learn what you are telling them to learn. This is precisely what schools are meant to break.

Public education historically helped class mobility. Publicly funded scholar have also greatly contributed to our advancement. However, as the world is changing through increased automatization and globalization, we may need to drastically shift gear. Stephen Downes answered my previous post with a pointer to his essay Five key questions. In this essay, Downes offers a foundational principle for a renewed public education:

It represents a change of outlook from one where education is an essential service that much be provided to all persons, to one where the role of the public provider is overwhelmingly one of support and recognition for an individual’s own educational attainment. It represents an end to a centrally-defined determination of how an education can be obtained, to one that offers choices, resources and assessment.

Downes challenges conformity as a core value for education. Quite the opposite: he calls into question the idea that education should be “managed”. I believe he would agree that one of the great tragedy of public education is the centrally mandated curriculum. This was ideal preparation for the slow-moving corporations of the sixties and seventies. In 2011, why punish a kid who decides to spent five years building a robot?

Go ask your kid to name a planet. If his answer his Jupiter, Mars or Earth. Be worried. In the twenty-first century, we need kids who answer Eris or MakeMake.

Further reading: Brian Martin, Review of Jeff Schmidt’s Disciplined Minds: A Critical Look at Salaried Professionals and the Soul-Battering System that Shapes their Lives, Radical Teacher, No. 62, 2001, pp. 40-43.