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The Obvious Value of Communication is Perhaps Not So Obvious


A Non-Obvious Question

In a recent podcast interview, the host asked me: “what’s something that seems obvious to you, but not to most other people?”

It was a good question because it spurred me to articulate an idea that has long lurked in the background of my thinking on work and productivity in a digital age. Here is (more or less) how I answered:

“When it comes to the world of work, more connectivity and more communication is not necessarily better. In fact, it often makes things worse.”

People are quick to admit that some of their habits surrounding workplace communication tools could use some improvement, but it’s widely agreed that the tools themselves — email, slack, smartphones — are a positive development. These technologies make communication faster and easier, providing a pleasing patina of industriousness and agility to your daily efforts.

To not use these tools would make communication slower and more difficult: how could that possibly be a good thing?

There seems to be wide agreement about this point, but as my above quote indicates, this consensus does not include me. There’s a good reason for this dissension: the idea that more communication is better goes against everything I’ve learned as a computer scientist.

Reducing Message Complexity

I should probably elaborate my previous statement. There are many types of computer scientists: I’m the type who studies algorithms that help distributed systems run reliably and efficiently.

Here’s the thing about designing these distributed algorithms: communication is something you’re almost always trying to minimize. The fewer messages you need to send or receive to accomplish your task, the better.

There are several reasons for this: communication tends to be slow compared to local processing, networks can be unpredictable, and sitting around waiting for messages to arrive, while your powerful processor sits idle, is frustratingly inelegant.

A well-designed distributed algorithm sends just enough of the right information to allow all parties to efficiently complete the task. And this goal is not always easy…

  • People in my field have written whole doctoral dissertations on how to reduce the number of back and forth messages required for a group of faulty agents to agree on a decision.
  • There’s a whole community of theoreticians who do nothing but try to prove the absolute minimum number of bits required for two agents to work together to solve various problems.
  • I co-authored a paper last fall that proved the surprising speed with which a rumor can spread through a crowd, even if people restrict themselves to talking to only a single neighbor at a time. This wasn’t easy to figure out.

As a distributed algorithm theorist, in other words, when I encounter a typical knowledge economy office, with its hive mind buzz of constant unstructured conversation, I don’t see a super-connected, fast-moving and agile organization — I instead see a poorly designed distributed system.


In discussing my perspective as a computer scientist, I’m not trying to claim that our approach necessarily applies to the workplace. I’m instead trying to underscore that some of the professional behaviors and trends that might seem so obvious in the moment, might be less obvious than most assume.

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