MIT Sloan Management Review Article on Use Open Source for Safer Generative AI Experiments

Integrating artificial intelligence into the daily workflow of employees across organizations, from upper management to front-line workers, holds the promise of increasing productivity in tasks such as writing memos, developing software, and creating marketing campaigns. However, companies are rightly worried about the risks of sharing data with third-party AI services, as in the well-publicized case of a Samsung employee exposing proprietary company information by uploading it to ChatGPT.

These concerns echo those heard in the early days of cloud computing, when users were worried about the security and ownership of data sent to remote servers. Managers now confidently use mature cloud computing services that comply with a litany of regulatory and business requirements regarding the security, privacy, and ownership of their data. AI services, particularly generative AI, are much less mature in this regard — partly because it is still early days, but also because these systems have a nearly inexhaustible appetite for training data.

About the Author

Aron Culotta is an associate professor of computer science and director of the Center for Community-Engaged Artificial Intelligence at Tulane University. Nicholas Mattei is an assistant professor of computer science at Tulane University.

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