Many people these days depend on Bayesian filters to protect them from the ever present email scourge that is spam. Unlike older technologies, these programs' claim to fame is that they learn the spam patterns automatically, and more importantly, learn personalized spam (bad) and ham (good) email patterns.
Like many others, I wrote a Bayesian filter to protect me from unwanted email, which I called dbacl. My implementation functions as a Unix command line text classifier, with special email support, and can be used with procmail.
People are often astonished at how well statistical mail filtering works after they first try it, and it's tempting to imagine that such programs actually understand the emails being delivered, rather than merely matching patterns.
Now chess has always been a popular gauge of intelligence that everyone can understand, so if we put all these ideas together, then the question "Can a Bayesian spam filter play chess?" seems like a fun experiment with a lot of appeal.