Law and Probability, Part III


When someone tells you they have “x years of experience,” they have performed a significant number of trials in their professional career. More trials means more certainty. And any professional who learns from mistakes will, presumably, improve over time.

But as we have seen with George Will and Dick Morris, lots of experienced, well-respected, and famous people get it wrong all the time.

Legal advocacy, like political predictions, will be better served with better data and more data points. The law, like baseball, like politicians, is a conservative discipline, and has been reluctant to adopt new methods. But our own experience is limited. The best attorneys and other professionals seek out data to help them transcend their own experience and use the experience of all professionals to inform their judgment.

In many ways, the open source legal documents provided by TechStars and Y Combinator are examples of this.

There are examples of big-data analysis in the the law, but they are few and far between.

In law school, I co-authored a law review article with a few colleagues analyzing the largest medical malpractice databases in existence, and we came up with a number of conclusions that I think were helpful in shaping policy in that arena.

I’d like to do something similar with the law of entrepreneurs and startups and make it open source. For the medical malpractice article I wrote, we relied on a database collected by Florida that surveyed every malpractice incident in the state over a series of years. That helped us reach many useful conclusions that helped shape future law with medical malpractice and inform public policy.

No such database exists for startups, to my knowledge. But with the help of the broader startup community, such a database could exist.

More to come on this in the not-so-distant future.

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