The Most Dangerous Bug, or What Is Computer Science About?

Isn’t it obvious? As the name suggests, computer science must be about computers.

And yet Edsger Dijkstra, one of the early pioneers of computer science, is often credited with saying:

Computer science is no more about computers than astronomy is about telescopes.

If astronomy were about telescopes, Hubble would be the star and the universe just the backdrop.

Science is a tool. Tools matter. But they are means, not ends. The ends are human.

Computer Science Is About Choices

Computer science isn’t about computers. It’s about choices. What we model. What we measure. What we reward. And which story we hard-code into the future, the story that frames reality and assigns value.

Every dataset is a decision about what counts. Every objective function is a decision about what matters. Every default is a decision about who decides.

A hiring algorithm trained on yesterday’s résumés doesn’t predict talent. It predicts yesterday.

As Lawrence Lessig put it back in 1999, “code is law.” And I would add that law is context.

Today, AI is turning every science into computer science. And it is turning computer science into applied ethics.

Why? Because every decision has immediate practical consequences, explicit or implicit. And every system must give at least a tentative answer to questions philosophy has struggled with for centuries. What is fair? What is true? What is a person worth? Who is responsible when nobody is in the room?

Philosophers had the luxury of debating those questions. Engineers have to ship an answer by Friday.

Asking Why Is the Real Power

Computer scientists often forget that computer science isn’t about computers.

That’s how some of our brightest minds spent the last two decades optimizing ads. In 2011, Jeff Hammerbacher, who built and led Facebook’s data team, put it plainly: “The best minds of my generation are thinking about how to make people click ads. That sucks.”

Nobody set out to build a machine for distraction. They set out to solve an interesting problem. The how was brilliant. The why was never asked. The question was “how do we get more clicks?” Not “why would we want them?”

Now we’re doing it again, at scale, with AI. Except this time the code doesn’t just sort our feeds. It writes, diagnoses, hires, lends, and decides.

Asking why is the real power. Without it, you aren’t the programmer. You’re the program.

Technology is the How. It is not, and never should be, the Why or the What. Those remain our job. And when we skip them, someone else’s why gets hard-coded into all of our lives.

Computers, code, algorithms, even AI: all of it is content. The why is the context that gives it meaning. A telescope can point at a galaxy or at your neighbor’s window. The lens doesn’t care. We have to.

Shelley called poets the unacknowledged legislators of the world. Today, that title belongs to the people writing code, and none of them ran for office. Yet every program is a policy.

So the most dangerous bug in computer science is the one no compiler will ever catch: a missing why.