May 2017
The n^2 Problem (1 May 2017)
Physicality and Comprehensibility (8 May 2017)
Patching is Hard (12 May 2017)
Who Pays? (16 May 2017)

The n^2 Problem

1 May 2017

At the Knight First Amendment Institute’s symposium on Disrupted: Speech and Democracy in the Digital Age, both Zeynep Tufekci and Tim Wu noted the problem of the concentration of news media, especially online. The trouble is that a fair amount of concentration more or less has to exist. The challenge is to figure out how to get the good effects without the bad ones.

Let’s assume that there were no intermediaries. This means that everyone can speak, but also that everyone has to monitor everyone else to know what’s going on. This figure shows the patterns for 10 people:

Every arrowhead represents "listening". I’ll save you the trouble of counting; for 10 people, there are 90 arrowheads. More generally, for n people, there are approximately arrowheads. If we assume that there are 100,000,000 people in the US, any one of whom can make news (if only by being dragged off an airplane), there would be about 10,000,000,000,000,000 arrowheads—far too many!

Assume, though, that in addition to the n people, there are m media outlets. In that model, while the media sites have to listen to all n people, each person only has to listen to m outlets.

There are many fewer communications channels here: m · n arrowheads. This is much more reasonable: for the same 100,000,000 people and, say, 1,000 media outlets, there are only 100,000,000,000 arrowheads, fewer by a factor of 100,000.

We give something up, of course. For one thing, the media outlets have great power. A federal court once noted that "the Internet has achieved, and continues to achieve, the most participatory marketplace of mass speech that this country—and indeed the world—has yet seen." If we rely exclusively on the media, only they participate. They can be biased—we all know the litany of partisan and even mendacious outlets. They may miss minor speakers, e.g., speaker s9 in this picture.

They may not even know about everyone—though they’ll probably do a better job than you will.

As Zeynep has pointed out, media outlets can also be "captured". That is, they’ll pay far too much attention to a minor, irrelevant, or downright false narrative, drowning out everything else.

Readers can get captured, too, by selecting only outlets that agree with their biases. This can interact with outlets (e.g., social media sites) whose only goal is financial: they show readers what they or their friends want, to keep them on-site. The result is the same: a "filter bubble".

So: pure decentralization can’t work, because its not scalable, and media outlets, whether traditional or new, are biased. What do we do?

An ideal solution will have several characteristics. First, it has to scale the way media outlets do, i.e., have m · n arrowheads. It has to avoid bias, whether intentional, out of unawareness, or due to filter bubbles. It has to accomodate differences in interest—I, for example, am much more interested in technology and tech policy news than I am in auto racing or fashion, and my news feeds should reflect that. It should be decentralized, to avoid dominance by any one source. Finally—and this is often overlooked—it needs a sustainable business model; large-scale newsgathering (to say nothing of competent reporting!) is expensive, and needs sources of support.

What’s the answer?