American Idol, Crowdsourcing and What Startups Can Learn From It

My wife watches American Idol. I try not to, but invariably I get sucked in because I like music and singing. I do not like the show because the competition is not about talent as much as who the american public likes. VentureBeat wrote about this in their post about American Idol and Crowdsourcing:

In my view, this American Idol result completely refutes James Surowiecki’s book, The Wisdom of Crowds, about how crowdsourced results always get it right.

I agree with VentureBeat somewhat, more on the point that an open vote like this is not a judge of “talent”. The question I have is whether this is really crowdsourcing. If you look at the Wikipedia entry on crowdsourcing, you will notice a common theme.

The public may be invited to develop a new technology, carry out a design task (also known as community-based design and distributed participatory design), refine or carry out the steps of an algorithm (see Human-based computation), or help capture, systematize or analyze large amounts of data (see also citizen science).

This does not sound like voting on a very subjective matter like talent or who makes the better pop star. This sounds more like which solution works best, or what is the common pattern in a large set of data. These are very objective measures. There are specific requirements in order to determine whether a “wise crowd” can be formed as well:

  • Diversity of opinion – Each person should have private information even if it’s just an eccentric interpretation of the known facts.
  • Independence – People’s opinions aren’t determined by the opinions of those around them.
  • Decentralization – People are able to specialize and draw on local knowledge.
  • Aggregation – Some mechanism exists for turning private judgments into a collective decision.

Probably the main issue when you get into American Idol style voting is the independence of opinion. People are highly influenced by the opinions of others around them. This causes small herds to form around that one opinion.

How Does This Apply To Startups?

Obviously, you are wondering how this applies to a startup. First, let’s look at more relevant examples. Digg is a website that “crowdsources” blog posts to determine the most interesting. I am not sure if it is truly defined as crowdsourcing because there is a popularity factor that needs to be included. For example, if I come up with an interesting theory that redefines what “Web 3.0” could be, it is likely that the post does not get very far on Digg. My blog has had some success on Digg, but it is not a typical thing. If TechCrunch runs a story with the same ideas, it is very likely to hit the front page of Digg. Why does this happen? TechCrunch is an established brand that many people know on Digg. RegularGeek is “yet another technical blog”, so there is a definite bias against that kind of thing.

However, the community of Digg does reward certain topics because that is what the community tends to know about. Posts about anything Apple related and programming posts tend to do very well, especially if there is a slightly controversial opinion. The Digg community has always been into technology, so Apple and programming continue to be major centers of attention in Digg.

What this means is that if your targeted community has specific knowledge, then crowdsourcing can become a very useful tool. This is likely true when the solutions are subjective as well. If the community is specialized, the wisdom of the crowd may be able to overcome the smaller biases of subjectivity.

So, if you are looking to create some great application on the web, and crowdsourcing is how you are going to solve some problem, think about what your crowd should be. Who should be in your crowd? Should it be a bunch of technology-loving early adopters? Maybe, or maybe not. You do not need to go after the largest crowd, just a crowd that is relevant to your problem.