But technology changes all that, and therein lies the revolution. Technology enables cheap and redundant connections across which reputation can emerge. It enables parallel information channels (“trust technologies”) for aggregating reputation: people (deliberately or implicitly) contribute information, and the technology summarizes the data, publishing the results at negligible cost. The blogo-sphere, for example, now comprises 27 million bloggers. Bloggers “vote” for each other through their blogrolls (fixed hyperlinks) and by citations. Sites such as Technorati provide navigation services and measure the “Authority” of bloggers on the basis of traffic patterns and citation.
Bloggers’ ability to bestow reputation increases with the reputation they already have. Rather than the chaotic or random patterns one might expect, the resulting patterns of citation readership and Authority are quite ordered, bestowing on the top bloggers in each content domain extraordinary influence, extraordinary reputation. All without hierarchy, market transactions, reciprocity, or an ad budget.
As described in the second Perspective in this series, eBay’s technology for aggregating ratings of buyers and sellers, Amazon’s for creating reputations for books and for Amazon Marketplace vendors, and Google’s for aggregating hyperlinks into votes on content all work in similar ways. But so too do Vault as a platform for employers’ reputations; Slashdot, in which the karma of chatroom moderators is voted up or down by those who are moderated; del.icio.us, which aggregates 100,000 new bookmarks a day into a “folksonomy” of the Internet; and—the latest manifestation—virtual escort ratings within online games.
Edmunds.com (the site, not the company) probably has a bigger influence on car-buying decisions than the TV budget of the automotive industry. A recent Forrester study found that whereas about 5 percent of consumers trust telemarketing “somewhat” and nobody trusts it “completely,” 50 percent trust consumer posts (as on Epinions) somewhat and a further 15 percent trust them completely. According to that crude metric, trust is 13 times higher in weak, unbiased signals than in strong, biased ones.
Moreover, we are at the beginning of all this. Reputation requires persistence of identity: I cannot build my reputation from anonymous transactions. And pseudonymous transactions in different domains build incommensurate reputations for my pseudonyms but not for me.
Technologies such as Trufina and Opinity already address those issues on a small scale, but in its next-generation Vista operating system, Microsoft will begin distributing an “identity metasystem” to hundreds of millions of desktops. This comprises a set of secure and open protocols that allow different authentication systems to work with one another. At first, the new protocols will make the current management of identity (logins, passwords, encryption, and so on) more user-friendly and much more secure. But very quickly the information covered by these technologies will broaden (under the control of the user). My “identity,” if I choose, will become not just my username and password but also a vector of attributes (some legal, some descriptive, some preferential, some moral) that are variously relevant in various contexts, unambiguously tied to me, and certified by mechanisms as objective as a secure authentication from VeriSign and as subjective as the reviews of my last book.
With Vista and the technologies it enables, we will acquire the ability to aggregate and port this information costlessly and securely (but still under our own control) into any network we choose and to reveal it selectively to someone whose trust we need. We will have the ability to deploy certified information about ourselves in any way that builds the reputation(s) we desire.
The more people do this, and the more interconnected the human networks within which their reputations are embedded, the more valuable are those reputations, both in their information content (signal-to-noise) and—more important—as an earnest sign of their owners’ moral reliability. Moreover, whatever the size of the population not participating in the reputational network, there is a self-sustaining process of positive selection: it will always pay for the “upper half” of nonparticipants to reveal their reputations, to achieve advantage over the “lower half,” with whom they are otherwise being averaged. The bigger the reputation-sharing network, the greater the pressure to join: the classic increasing returns pattern of network economics.