Important stories and good content

Via David Weinberger I read about an interesting discussion at Foocamp. The question was "how to decide which [news] stories are important and interesting without human intervention", and the various answers propose different ways of harnessing the wisdom of the crowds: via voting (as in Digg), by tracking commentary (Techmeme) or watching users reading the news (Newsvine). Never mind that all these approaches involve human intervention: the point, I suppose, is not so much about humans generally as about about editors specifically.

If you've been reading this blog for some time you will know that I question some of the premises behind such attempts: namely, that human editors offer a unique value that machines or crowds can't provide - namely, expression and commitment (I won't repeat my arguments here -- you can read them in an earlier post).

But the aggregators above have an even more fundamental problem: they are not automatic at all. Inasmuch as they rely on popularity they are not autonomous. Nothing would be popular if it wasn't discovered in some way first; and that initial discovery usually happens via an authored, 'manual' aggregate.

 

There is a school of thought (which may or may not be subscribed to by the people in the discussion above) that holds that, in the future, media consumption will only be a matter of finding the 'content that's right for you', and that hence human aggregators will become redundant. Its proponents cite examples like YouTube that can identify 'good' or 'popular' content long before any human aggregator does. These are animals of a different species from Digg or Newsvine and deserve separate treatment (see my later post on this).

For now, I would like to comment on some basic assumptions that inform this second school of thought, assumptions about nature of two types of thing: content and people.

In this view, the world of content is made up of discrete, self-contained things (pieces of 'content'), each with its properties. These properties (subject matter, style, quality, etc) may be factual (e.g. how long a video clip is), matters of unarguable judgement (e.g. that a clip is about George Bush), or matters of subjective preference (e.g. that 80% of people 'like' a clip).

On the other hand we have another type of thing: people, i.e. those who consume content. They also have their properties: their preferences, the communities they belong to, their demographics, age, sense of taste, interests, past, etc

In the middle we have media, and a challenge: how to pair up these two types of things - people and content - in the best way. The basic assumption is that this best way is a function of the properties of people and content - i.e. a matter of compatibility. To be sure, the picture is sometimes more complicated: to be realistic we also need to consider people's moods, their expressed desires (e.g. via a search query), and time (only fresh news are news). But the basic -compatibility- idea still applies.

Powerful as this view may be, note what it misses:

1. It doesn't account for people who want to see what a trusted human editor may want to offer. This is crucial in the case of news
2. It makes authorship and attribution secondary: good content is good content is good content, quite apart of where it came from
3. Assuming that human editors are here to stay (a point I've argued before), it fails to account for how these will influence popularity, and hence what 'automatic' aggregators will offer. I'll write more about this in a later post
4. It fails to account for content that is consumed because others are consuming it. By presenting consumption as a matter of compatibility, it suggests that media habits are a selfish affair, aimed at personal, self-contained satisfactions and not at communing with others or communicating as part of the ongoing conversation that is social life (even watching Terminator is a conversational act)

I will have more constructive things to say about this in later posts.