Friday, May 3, 2019

Fromer: Machines as Keepers of Trade Secrets

I really enjoyed Jeanne Fromer's new article, Machines as the New Oompa-Loompas: Trade Secrecy, the Cloud, Machine Learning, and Automation, forthcoming in the N.Y.U. Law Review and available on SSRN. I think Professor Fromer has an important insight that more use of machines in businesses, including but not limited to increasing automation (i.e. using machines as the source of labor rather than humans), has made it easier for companies to preserve the trade secrecy of their information. Secrecy is not only more technologically possible, Fromer argues, but the chances that information will spill out of the firm are reduced, since human employees are less likely to leave and transfer the information to competitors, either illegally in the form of trade secret misappropriation or legally in the form of unprotectable "general knowledge, skill, and experience."

Professor Fromer's main take-home is that we should be a little worried about this situation, especially when seen in light of Fromer's prior work on the crucial disclosure function of patents. Whereas patents (in theory at least) put useful information into the public domain through the disclosures collected in patent specifications, trade secret law does the opposite, providing potentially indefinite protection for information kept in secret. Fromer's insight about growing use of machines as alternatives to humans provides a new reason to worry about the impact of trade secrecy, which does not require disclosure and potentially lasts forever, for follow-on innovation and competition.

Here was what I see as a key passage:
In addition to the myriad of potential societal consequences that a shift toward automation would have on human happiness, subsistence, and inequality, automation that replaces a substantial amount of employment also turns more business knowledge into an impenetrable secret. How so? While a human can leave the employ of one business to take up employment at a competitor, a machine performing this employee’s task would never do so. Such machines would remain indefinitely at a business’s disposal, keeping all their knowledge self-contained within the business’s walls. Increasing automation thereby makes secrecy more robust than ever before. Whereas departing employees can legally take their elevated general knowledge and skill to new jobs, a key path by which knowledge spills across an industry, machines automating employees’ tasks will never take their general knowledge and skill elsewhere to competitors. Thus, by decreasing the number of employees that might carry their general knowledge and skill to new jobs and in any event the amount of knowledge and skill that each employee might have to take, increasing automation undermines a critical limitation on trade secrecy protection.

For more on trade secret law's "general knowledge, skill, and experience" status quo, see my new article, The General Knowledge, Skill, and Experience Paradox. I recently discussed this work on Brian Frye's legal scholarship podcast, Ipse Dixit  in an episode entitled "Camilla Hrdy on Trade Secrets and Their Discontents".

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