I just got back from a Distinguished Lecture talk by Dr. Carley, a CS prof at CMU. The talk was titled Dynamic Network Analysis Applied to Counter Terrorism. Even though I read the abstract, I went into it expecting discussions of adaptive Internet network devices and using traffic/flow systems to isolate cyber-terrorist behavior. The talk was a little looser than that; using any intel to map relationships, communication, resources between role players in terrorist organizations (and corporate espionage.) She talked about her research allowed quick mining of this information, and estimated projections of how social networks would reform if certain evens happened (elections, assassinations, etc.)

Does that sound like Computer Science to you? Maybe not, but what it reinforced (again) for me is that CS isn’t a standalone discipline. Really, what she is doing is information science… taking data in some form, figuring out how to assemble and internally construct and associate that data, and then finding effective and useful ways to get current and logical near-term projections from it. Social networks overlap all of my academic interests; CS, Speech Comm, LIS. Even though the talk was not directly tied to my interests, I enjoyed it.

At the Q&A in the end, I asked her if her expertise and her challenges fall more into Computer Science or Sociology/Anthropology. She said that currently, it’s almost all CS. The intelligence organizations know what information they want to track and have available, and what results to desire; they just need new, fast, dynamic, accurate ways of creating and modeling that data. These are certainly computer science issues. But, she acknowledged that in a few years, once the CS is up to speed, the social scientists will have to look at that data and come up with new theories and new requirements.

This is very close to where I think we are across all computer systems. They’re good enough, or shortly will be good enough, to do whatever we want. The really cool stuff involves reapplying those systems for previously unconsidered means (and thus, make them inadequate again.) And so the cycle begins again. It also starts to answer the question of why Computer Science keeps doing all these things that don’t seem to have a relevant cause today… it seeds the future capabilities and research in nameless/countless other areas.

The really important, influencial people in the future will be ones who understand the current limits and capabilities of technology, and also understand the future direction of (information, entertainment, transportation, investing, marketing, you name it.) Using Professor Carley’s software, we could probably start to map and interpolate that data.