From the general to the particular
Let's look again at the problem posed by Tillman Pearce. How can cancer patients be helped in finding out about all the treatments that might be available to help their condition?.
The treatment of cancer is a typical example of a rapidly expanding technological field where new research is continuously creating an abundance of new developments in many different parts of the world. For a patient seeking treatment, it would be impossible to keep track of all the activities taking place. Realistically, a cancer patient couldn't be expected to study all the technical papers relating to their condition. Neither could they be expected to be able to discuss matters with many specialists. As discussed already, any databases available to them on the subject would almost certainly be incomplete, probably out of date and unlikely to address their specific individual situation.
The only option left open for them is to mix with other cancer patients who have a similar condition and find out what is happening to them. This is where they can be helped: by providing them with the means a bot creation program and a formatted space where they can get together in niche groupings to pool their knowledge. After all, collectively as a group, the patients are as much aware of all the possible treatments as the physicians.
If a conceptual framework can be designed to arrange for cancer patients with a similar condition to find each other, this would be far more valuable to them than any informational database. They can compare treatments, swap, information, inform each other of new developments and trials. Many of them will have built up specialist knowledge on their condition that they can share with the others. Perhaps some of them will have Web sites, where they have recorded the extent of their knowledge within the niche area of their particular condition. Between them, the patients are likely to have more experience and knowledge of treatments and outcomes relating to their condition than most individual cancer specialists.
If special areas of interest are created in a people space relating to different types of cancer, types of treatment and other associated topics - it is likely to attract more than just the patients themselves. It will also attract friends and relatives who use the Internet to help find the best treatment for their loved ones. It will be of interest to researchers, drug companies, doctors and surgeons who will have a professional interest in knowing about the work of others and the treatment options outside of their own particular approach.
The use of bots as personal electronic agents to represent people in the meeting spaces will facilitate any degree on anonymity desired, yet, at the same time be able to reveal sufficient of their owner's details and background to identify them as interesting people to know in the relevant situation.
Visualising these communities as forming spontaneously in a formatted space with changing circumstances and new technological developments causing them to move around, dividing them up into more specialised grouping as their number increase would seem to be a far more realist approach to obtaining knowledge than trying to create a conventional database of information.
Such an approach can be usefully applied to many other areas of technology especially where there is an impossibly large knowledge base that is continuously changing, expanding and evolving. This is evidenced with the popularity of Internet newsgroups, where a similar organic, self-organising structures have successfully evolved. These have similar ways of creating new sub divisions when groups grow too large.