Academic Productivity

Ok, this is just a quick, relaxing post.
In your view who is the academic most likely to accidentally eradicate human life?

Following up on Jose’s musings on good and bad keywords for a productivity blog, I came across an interesting tool to visualize the evolution over time of aggregated social bookmarking tags for popular websites. It is actually a pretty old project called Cloudalicious created a few years ago by Terrell Russell (of ClaimID fame).

If you are a web metrics maniac like yours truly, you won’t resist plugging this tool into your favourite websites, so here’s the graph I generated for AcademicProductivity.com:


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“Math is hard; let’s go shopping!”

-hacked Barbie

Summary: It looks like the difficulties of measuring  productivity make people use common sense to give advice on how to improve it instead of actually attacking productivity as a hard problem that needs empirical study. But people do follow barely tested advice on productivity. They are either too busy to afford dismissing it, or too pragmatic to believe that we can reach systematic, scientific productivity techniques.

There is a current craze about productivity in many forms (sometimes disguised as personal development). At least 4 of the top 100 blogs in the blogosphere are about productivity (according to technorati’s authority: lifehacker #6; Zen Habits #41; lifehack.org #66 43 Folders #73). There’s a current craze about personal productivity and personal development. The best treatment I have read recently is Cal Newport’s Flak magazine article. 

In fact, lifehacking is a trend of the 21st century. The idea is to reduce the things that bother you in your life (or reduce the time it takes to complete them) while increasing the quality and quality of the experiences that you like. This is pretty intuitive, but is this a working definition of whatever personal productivity is? Hardly. Today, anything that solves an everyday problem in a clever or non-obvious way might be called a life hack.

Hacks are by definition, unsystematic. Everything goes, as long as it works. This is the contrary to the incremental evolution of scientific thinking. Even though sometimes there are large changes in the form of paradigm shifts, most of the time progress is incremental and lineal.

The advantages are clear: one can build on the knowledge acquired by the previous generation.

But do we have the same incremental progress in personal productivity theories? If there anything remotely similar to a science of productivity? Should people follow only empirically tested advice about productivity?

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I always wondered how people see the academic world from outside. How do we gauge the interest of the general public on what academics have to say (on average)? One easy way to look at this question is to see the how often people will read an article that has the word ‘academic’ on it.

A proxy on what people read nowadays is digg.com. And the tool to see how often people digg academic posts is now available in Dan Zarella’s blog. Given a keyword, the tool will return data on the average number of links accumulated by stories popular on Digg that mentioned that keyword. This is done with 2007 data.

Well, behold what happens when you enter “academic”:

And compare it to what you get when you type “productivity”:

Why is this important? Well, on average, a single digg increases traffic by 0.10%. So a story that gets 3,000 diggs results in an increase in total traffic to the referring site by 300%.

So, from now on we are a^H^H^H^H^H^H^H^H productivity blog

Do you need to write code in your academic work? Have you read someone else’s code? Did you just get  a code attachment with a warning like “this is a mess, I need to clean this up someday?”. Well, you are not alone. It seems that in the industry, telling someone that you plan to use code that comes straight from an academic makes them feel a drop of cold sweat down their backs.

American scientist has an article on these common practices that we have managed to avoid for so long.

I therefore started asking scientists how they wrote their programs. The answers were sobering. Whereas a few knew more than most of the commercial software developers I’d worked with, the overwhelming majority were still using ancient text editors like Vi and Notepad, sharing files with colleagues by emailing them around and testing by, well, actually, not testing their programs systematically at all.

I finally asked a friend who was pursuing a doctorate in particle physics why he insisted on doing everything the hard way. Why not use an integrated development environment with a symbolic debugger? Why not write unit tests? Why not use a version-control system? His answer was, “What’s a version-control system?”

The paper advocates the use of version-control, proper editors and IDEs, and unit testing. These three things are great practices, and in my experience we academics either don’t use them or had to learn them ‘on-the-wild’ after banging our heads on a wall. And it shows.

Our code could be tidier. The bad news is that this reputation seems not to be restricted to code tidiness.

The unqualified-reservations blog has a (long) post on how CS research in the academia is considered outside:

…anyone who’s not involved in CS research treats the products of this endeavor as if they were smallpox-infected blankets. Even when it is clearly – in my opinion – good, it winds up ignored. Because of the inescapable grant-related propaganda, it’s impossible to tell what’s good and what’s not.

The gist of his main point is that usefulness and relevance are almost inversely related to academic value. That gives academics the ‘freedom’ to write unmanageable code; as long as it produces a paper (and note that code is not provided with the paper) you are fine. A caricature: a guy invents a programming language (say python) that is used by millions included google. It has zero academic value. Another guy writes and obscure paper (or hundreds) on a topic that is irrelevant even to his mom. That second guy gets grant money, tenure. Sounds familiar?