Thinking Clearly .

Our plan to offer commercial support for Pellet, and to gradually transition it from an academic to an industrial-strength tool, is proceeding nicely. OWL-DL is an interesting technology; but I keep hearing and seeing signs that the killer app still for Description Logics in Web technologies is still around the corner.

One of the things I spend my time these days doing is, well, looking for that killer app. I think at some point it will be found in the area of policy management; there is some very promising research being done in this space at UMD (and many other places), and we’re excited about our chances to roll out products in this area in the next 12 to 18 months.

But I’m also on the lookout for areas that will work now, and I’m starting to think that “collective intelligence” could turn into one of those near-term wins. What I mean in particular is creating an argument or decision-support tool, using OWL-DL and Pellet, within a public policy web app, like a prediction market, policy-support tool, social-network analysis, etc.

I recently happened upon an interesting paper in this area, “Collective Intelligence for Decision Support in Very Large Stakeholder Networks: The Future US Energy System”, which describes a web app to be used in stakeholder networks, with the example domain being the energy market in the US. Now, the web app part isn’t novel: it’s roughly equal parts wiki and polling system. The novel bits are what we might call the social informatics, that is, the structure of the interaction process and that these kinds of systems are being seriously considered and, in some institutions, deployed.

Of particular note for Clark & Parsia as an R&D company is the fact that the web app is designed to allow the use of an automated tool for supporting human decision-making processes, including argumentation analysis. Now this makes me happy for at least four reasons:

1. we’re interested in what I call (I hope not idiosyncratically) “hard collective intelligence”, that is, computer-aided collective intelligence using description logics, machine learning, or other AI and KR approaches. Someone’s gotta do the soft CI work, but we’re not ready to start hiring sociologists just yet…;


2. in the US, anything that contributes to increased rationality in public policy deliberation can only be a good thing;


3. it’s precisely the kind of work we want to be doing; and


4. it’s the sort of work that will dovetail nicely with our policy management schemes, which include things like dedicated policy management appliances embedded in the enterprise fabric, and SDKs for policy-to-logic mappings, etc.

We are and will remain for some time, perhaps a long time, a description logic company; but we’re also very excited by all the great work happening in machine learning, social and network informatics, computational economics, etc. It’s a great time to be working in all of these areas, and I’m especially interested in all the overlaps and interstices. If you’re doing this kind of work towards a degree, you might want to drop us a line; we’re always looking for graduate students whose research we want to support, since they make great partners and even better employees.

This time on Logical Commonsense. Some good stuff from Davis as well as from the Common Sense Problesm page.

Now crack that egg!