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« More Data is Better, Proceed With Caution | Main | Data Mining, Predicate Triage and NSA Domestic Surveillance »

March 10, 2006


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Tony Bennett

I find your insight to be a refreshing wealth of relevant information and knowledge regarding data. Thank you.

I am a veteran CTO of a couple Healthcare startups. Recently I have been working on a potential solution to address privacy concerns about personal data (not exclusive to Heathcare) while still allowing accurate data mining and longitudinal matching to various disparate sources. I have several prototypes, yet I want to fully understand privacy concerns within industries (Healthcare, Financial Services, e911/Law Enforcement, Travel, Search Engines, Military, etc.).

It seems that in this information age, we are at times afloat in a data ocean one day, the next being hurled down a raucous data river. In either case, there is no shortage of data. In both waters, private information is either inadvertently surrendered or easily bound with other public domain data allowing positive privacy violations. At the same time, knowledge is certainly powerful and fuels amazing insight when researching a topic today.

Few companies can ignore data mining and thankfully most industries are fenced by privacy rules/laws. Those companies who do choose to ignore data mining will almost certainly be at a competitive disadvantage and perhaps even legal troubles for not understanding, protecting and managing data as a critical asset.

With privacy concerns being paramount, longitudinal matching seems to me to be the key to powering context. Context is key to understanding data. Without accurate matching, context is inaccurate in most cases involving privacy data. On the other hand, 100% positive longitudinal matching (using today's plethora of unproven methods) means that privacy has almost certainly compromised (how can the results be verified?). This is the conundrum for which I have a solution to be considered.

In one of your posts, you stress the importance of working with privacy advocate groups and I could not agree more. So, which group(s) does one begin working with to understand their requirements. Boiling down these seems to be an enormous challenge; the technology may come with much less pain.

As an entrepenuer I conduct as much background research as possible. While it is vital to understand all privacy and research/mining requirements up front to produce a technical architecture that will accomodate everyone, it can also consume all of one's resources (time, money, etc.). Is there an answer--beyond massive venture investment (and the requisite loss of control of your own company) that will provide for everyone's concerns I wonder.

Research is key to the future of mankind, however I'd like to see the day when electronic data is treated as privately and as sensitive as your personal banking data has been for years.


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