Stephen Downes’ new column on e-Learn does a great job of showing that solving the informational cascade problem is more challenging than I had presented it to be in my own article on the topic. In fact, his own analysis reveals that the problem may be harder to solve than even he himself suggests. The problem, as is often the case, is largely due to those pesky externalities, i.e., reality stubbornly refuses to conform to an elegant theory (and alas, Stephen is even more of a sucker for an elegant theory than I am).Stephen writes:
Though Feldstein’s solution would certainly solve the cascade problem, it does so at the cost of adding substantial overhead. “Informational cascades can be prevented but generally only with deliberate and specific intervention,” he writes. But the cost of such intervention impairs the functioning of the network. For example, Feldstein suggests the employment of “active moderators who have the authority to direct the group’s information-sharing activities.” People would be, for example, stepped through a polling process such that they would decide simultaneously whether to adopt Plan A or Plan B, thus ensuring that no person is influenced by the choice of another.
The problem of coordination this raises is staggering. Suppose four people are ready to choose a plan but the fifth is not. Are the first four retarded in their progress, or is a hasty decision forced on the fifth? Moreover, it is not even clear that communications between the people can be managed in such a way-what prevents their use of backchannels (such as telephone calls or after-hours meetings) to circumvent the limitations imposed in the communications network? Further still, some activities are inherently serial. How could we conduct an ongoing activity such as stock-market purchases were all transactions required to be conducted at the same time?
Dead on. Even with small groups, the administrative overhead that is entailed by the solution I suggest is high and, in some cases, prohibitively so. And the problem multiplies dramatically as we scale up. In a class, where the instructors control the problems that the students must solve, we can also control the costs of the administrative overhead to a substantial degree. But this is much less true in a work environment. If you have ever participated in a real-world “coordinated” roll-out of an organization-wide initiative then you probably were nodding your head vigorously when reading the quote above.
Unfortunately, Stephen’s own solution requires that people act as perfect (or near-perfect) network nodes:
If you have no friends, your choices will not be influenced by your friends. But if you have one friend then your friend will have a disproportionate influence on you (the centralized authority model). If you have 100 friends, however, the influence of one friend is once again reduced to the point where that one opinion, by itself, is unlikely to sway your decision.
But research strongly suggests that people simply do not grow circles of friends/influence that are large enough to reach anywhere near 100 on many of the issues that matter most to them. (I used to know the numbers for various kinds of human network affiliations but I can’t seem to remember them or find them again. If anybody knows these numbers, please add a comment.) I may know 100 people, but I don’t pay attention to what they all say when picking a political candidate. (Network researchers account for this kind of a limitation in their models with a massive fudge factor that they call “connection quality.”)
Furthermore, Stephen’s solution of increasing the number of network connections can be hobbled by the same realities that he pointed out would cause problems for my solution:
To return to the practical example set out by Feldstein, let’s look at the case of various managers opting for Plan A or Plan B. In the example, where there is a small number of managers, the problem isn’t simply that one manager is being influenced by the other, the problem is that the influence of the one has a disproportionate influence on the other. But instead of cutting off communication with the other manager-Feldstein’s solution-a more robust response would be to increase the number of managers with whom the first interacts. Thus, when one manager opts for Plan A, it will not automatically cause the other manager to opt for Plan A; the other managers’ inertia (or varied choices) counsels caution, and this allows for the influence of local knowledge to be felt.
In order to increase the number of managers with which the decision-maker interacts before making the decision, you need to first wait until enough managers have opinions to put into your bias-reducing pool. This is exactly part of the solution I suggested which, as Stephen correctly points out, entails significant overhead. The problem he raises of seriality is really just a symptom of a network model that is static rather than dynamic, and I don’t think Stephen has articulated a model that is any less static than mine. (Besides, what if you only have five managers?)
Stephen then raises a another problem that he also fails to put to rest; namely, power laws. He writes,
When we look at phenomena like the Kerry nomination, we see that the structure of the communication network that conveyed voter intentions was more like the manager model and less like a densely connected network. Voters did not typically obtain information from each other; they obtained information from centralized sources, such as broadcast agencies. These broadcasters, themselves sharply limited in the number of sources of information they could receive (and receiving it mostly from each other) were very quick to exhibit cascade properties, and when transmitted to the population at large, exhibited a disproportionate influence. Were the broadcasters removed from the picture, however, and were voters made aware of each others’ intentions directly, through bilateral rather than mediated communications, the influence of any one voice on the eventual vote would be minimized.
While I’d quibble and ask for some empirical validation of Stephen’s contention that “voters did not typically obtain information from each other,” in general, Stephen is right on once again. Information hub formation is inherent in scale-free networks. Hubs happen.
Stephen’s proposed solution to the power law problem is specialized RSS feeds rather than generic news hubs:
In my view, this will remain the case so long as access to content on the web is organized by Web site authors. Because of this, it remains difficult to find content on a particular topic, and readers will gravitate to a few sites that tend to cover topics in which they are interested rather than expend the time and effort to find items more precisely matching their interests. By drawing content from a wide variety of sites and organizing these contents into customized content feeds, the range of sites made available to a reader is much greater, decreasing the power law and reducing the probability of cascade phenomena. The shift from Web sites to blogs was, in effect, this sort of transition; the development of specialized RSS feeds will be a significant move in this direction.
This amounts to mass customization, and it’s not a new thing. The trend toward more consumer choices of many diverse and specialized has been a trend in periodicals and cable TV for a long time now. And as Cass Sunstein points out in Republic.com, there’s good reason to believe that most people will choose to use their new ability to create customized collections from a diverse pool of information sources to reduce the diversity of opinions they are exposed to rather than increase it. We tend to want to create the informational equivalent of gated communities, only letting in the perspectives that we want to hear.
So the net result of Stephen’s analysis (in my opinion) is that the problem looks even more serious and less tractable than it did at the end of my own article. He pokes some holes that he can’t quite manage to sew closed again.
Pandora’s box is open.