The 2008 Financial Crash posed a stark reminder about how out-gunned government regulators were compared to the big financial services companies that leveraged state-of-the-art computer technologies to design super-complex deals and make lightning-fast trades. It was like one used machine guns while the other fought back with bows and arrows.
Tim O’Reilly has some big ideas about how to rectify the situation by dramatically modernizing the entire notion of government regulation. He talks about “algorithmic regulation” that harnesses computer power much like top tech companies in Silicon Valley do. Those overseeing Google search, for example, set their sights on ultimate outcomes (getting accurate answers), try multiple paths forward, constantly runs tests and study the data, and incrementally make adjustments to fine-tune the best results. Government regulators could use a similar iterative, data-driven approach.
Tim O’Reilly, who we once described as a model reinventor, lived up to his billing in what turned out to be a model roundtable too. Tim hit the highest bar that we strive to achieve in this roundtable series. He came to the table with some big but unfinished ideas about how to reinvent government regulation by borrowing new approaches and best practices from the Silicon Valley technology world. He handpicked the exact people he wanted at the table to help him (and us) learn how to improve on those nascent ideas. Our lively 90-minute conversation did iterate the ideas and together we moved the ball forward, ending with some concrete suggestions for next steps.
It all started with Tim making the case that quite a few technology companies in Silicon Valley are essentially in the business of regulation in the broadest sense. Google delivers accurate search results by regulating the process and ensuring that bad guys who try to game the system with spam lose out, while those websites that play by the rules succeed. The way they regulate largely differs from how government regulators work. Google is constantly trying to improve its regulation by running tests, collecting and studying vast amounts of data, and then incrementally adjusting the rules. O’Reilly thinks governments could try much more of this iterative, data-driven “algorithmic regulation.”