Ellen Pao is back, with some new insight into her famous sex discrimination lawsuit. In 2012, Pao sued Kleiner Perkins Caufield & Byers, a prominent venture capital firm, accusing it of gender discrimination and retaliation. Pao ultimately lost that suit, but her story helped spawn conversations about diversity and discrimination in Silicon Valley and captured the nation’s attention with its salacious details.
Now Pao is once again putting her story before the public, with a forthcoming book, “Reset,” in which she delves into her time at Kleiner and the details of her lawsuit, coming to a surprising conclusion: The discovery process that was partly to blame for her courtroom loss.
A Headline-Making Case, Decided by the Burden of eDiscovery?
At the time, Pao’s suit was one of the most talked about events in the technology and venture capital worlds. The details were lurid and sometimes baffling: Allegations that Kleiner’s CEO discussed his favorite pornstars with coworkers, details of Pao’s affair-gone-bad with coworker Ajit Nazre, Kleiner's curious failure to adopt a sexual harassment policy.
More substantively, Pao's suit focused attention on the ways, both large and small, woman can be marginalized in the workforce. Pao claimed she was told she should be flattered when a partner propositioned her and that she was punished for ending a relationship with another, that female partners were often treated like secretaries and evaluated on a double standard—critiqued for being both too pushy and too timid.
A jury didn’t seem to buy her version of events however. In 2015, jurors rejected each of Pao’s four claims, agreeing with Kleiner that it was Pao’s own performance which hindered her.
After Kleiner, Pao went on to complete a brief and tumultuous stint at Reddit, before largely stepping out of the spotlight for the intervening years, during which she’s become an advocate for diversity in the tech industry and written a book, an excerpt of which was recently republished online in The Cut. The excerpt surveys “how sexism works in Silicon Valley” and includes a telling litigation postmortem.
Her claim failed in part, Pao says, because she was outspent and outgunned:
Since the trial, I have had time to think of all the things I wished I’d done differently. I might have had better luck with public opinion, for instance, if I’d spent more time with the press and prepared a few pages of talking points every day, like Kleiner had. But Kleiner also had tremendous resources that I couldn’t match, and it made a difference.
Pao, a Harvard-educated attorney, isn’t talking about a dream team of highly skilled lawyers here. She’s talking about discovery.
For example, I didn’t have time to go through all my emails to figure out which ones to give Kleiner, so during the discovery process we gave them practically everything, some 700,000 emails — most of which we could have legally withheld. Kleiner meanwhile handed over just 5,000 emails, claiming they didn’t have the resources to search for anything other than emails that we specifically requested. They did have the resources to pick over my emails, though — I heard they hired a team in India to read and sort through every single one.
That resource disparity, Pao says, had a significant impact on the trial. Kleiner’s work “would show,” Pao writes.
During depositions, they brought up everything from my nanny’s contract to an exercise I’d done in therapy where I listed resentments. Emails to friends, emails to my husband, emails to other family members, even emails to my lawyers.
A Better Way to Do Discovery
Pao’s story is a telling illustration of the outsized role the discovery process plays in modern litigation and how the burdens of eDiscovery can shape the outcome of a case. There are parties, like Pao, who don’t have the resources to conduct a brute-force, eyes-on review of hundreds of thousands of individual documents, or to bring on third-party vendors who can charge $250 a gigabyte for data ingestion and penny-per-page Bates stamping. There are parties, too, like Kleiner, who find themselves buried under a mountain of ESI, the “give them everything and let them try to sort it out” approach to production.
There are, however, alternatives to this process. Discovery Automation, powerfully simple software that leverages the advantages of the cloud, can help level the field and democratize eDiscovery. Potentially privileged documents can be identified automatically. There’s no need to review every single document—an incredibly burdensome approach to discovery, even when conducted via an offshore document review center—when powerful culling tools can help you narrow down your documents almost instantly. Intelligent, flexible searches can help you separate the wheat from the chaff.
With such technology, discovery is no longer a question of how many dollars you can throw at your eDiscovery vendor or the amount of hours you can devote to an in-house team doing manual review.
Who’s to say if such technology would have changed the outcome of Pao’s case? After all, discovery automation can’t change the facts of a case—but it can make those facts easier to find, reducing the burdens and imbalances of discovery in the process. That, indeed, is what ending eDiscovery is all about.