Working the Double Bottom Line: The Promise and Limits of Social Enterprises in the Shadow of AI

Special Event | May 13 | 4-6 p.m. | 202 South Hall

 Mary L. Gray and Prayag Narula

 Information, School of

Sponsored by the Algorithmic Fairness and Opacity Group (AFOG)

Join us for a conversation with Mary L. Gray, Harvard Berkman Klein fellow, senior researcher at Microsoft Research, and associate professor of informatics, computing, and engineering at Indiana University and Prayag Narula, president and co-founder of LeadGenius, a social enterprise started by UC Berkeley students that uses a combination of data mining, technology and crowdsourcing to automate and accelerate outbound sales and marketing.

Gary and Narula will discuss Ghost Work: How to Stop Silicon Valley from Building a New Underclass (Houghton Mifflin Harcourt 2019), Grayâs new book, co-authored with computer scientist Siddharth Suri. Ghost Work blends ethnographic fieldwork, interviews, surveys, and large-scale transactional data analysis to chronicle the lives of workers based in India and across the U.S. working on platforms, like LeadGenius, to train artificial intelligence or substitute for AI when the algorithms fall short, often without a consumer ever knowing they were there.

Gray and Suri coined the term âghost workâ to describe the labor conditions that all too often accompany task-based jobs that are, at least in part, sourced, scheduled, managed, billed, and shipped through a mix of application programming interfaces (APIs) and the internet. Thereâs no evidence that humans will be eliminated from this type of task-based ghost work anytime soon. People do the evaluative, creative work that stymies computation and automation. And businesses, like LeadGenius, depend on this pool of humans in the loop to execute quicks decisions and move on to the next problem pushed in front of them from a different client.

Narula and Gray will talk about how LeadGenius creates ways for workers to control their own destinies, offering a model for how to support teams that are collaborative, cooperative units. The start-up aspires to meet a âdouble bottom lineâ of exceptional fiscal gains and positive social impact, offering an example of how this work need not be ghostly and could be done differently today. But, even with innovative platforms designing with the best of intentions, those doing ghost work still shoulder a disproportionate share of the costs in the digital economy.

What are the promises and limits of the âdouble bottom lineâ strategy? What else can policy makers, technologists, and the general public do to hold companies accountable to AIâs long and distributed labor supply chain?