Remember Erin Brockovich? She was the legal clerk who took on the mighty Pacific Gas & Electricity company, claiming they’d contaminated the drinking water in her hometown of Hinkley, California.

The case was settled in 1996 for $333 million, then the largest-ever settlement paid in a direct-action lawsuit in United States history.

Julia Roberts went on to play Brockovich in the Oscar-nominated movie of the same name. 

Such David-and-Goliath legal battles make for a great Hollywood blockbuster because they’re few and far between. At least they were in the 1990s, when the worldwide web was still in diapers.

But today, artificial intelligence (AI) can uncover an alarming number of similar injustices that would never otherwise see the light of day.

AI is trawling the impossibly vast Internet, putting together the pieces of what could be the next big legal case.

It sifts through unimaginable amounts of publicly available online data from news outlets, governmental studies, academia, social media, consumer complaints, administrative documents and companies’ financial filings.

And it identifies potential cases involving faulty products, polluting factories, dangerous car components, breaches of privacy, underperforming pension funds, hazardous medicines – anything that could lead to a mass or class action suit (mass actions have many plaintiffs, while one plaintiff represents a larger group in a class action).

The aim is to help get justice for groups of wronged individuals who may not even realize they’re part of a wider problem. And to provide top-tier legal companies with the makings of an “impactful” case that will earn them money and boost their profile.

Darrow, a legal-tech startup founded in Israel four years ago, is a major player in bringing the benefits of AI to litigators. 

Finds cases, predicts outcome

Darrow doesn’t just find cases (though that’s no small task). It also predicts the likelihood of success and the financial value, based on historical data. 

And it will – again utilizing AI – locate the hundreds or thousands of potential plaintiffs required for a mass or class action.

“We know how to really focus a campaign and reach, say, the 4,000 people who may have been harmed,” says Gila Hayat, a former software developer who became cofounder and chief technology officer at Darrow.  

“We’re mostly focused on class and mass actions, so we know how to target them better.”

It’s a far cry from law firm’s flashing signs along US highways asking “Did you get hurt by anything ever?”

“The attorney’s task is to represent such groups and bring actions to court, but the core skill that is missing is the ability to detect the next case,” says Hayat.

Those cases lie below the surface. Replicating what AI does – poring over millions of documents and making the necessary connections – would require a vast army of people, at an impossible price.

Old-time lawyers would wait for a knock on the door. Today they need to be ahead of the curve, using AI to fit together the pieces of a vast and otherwise unfathomable jigsaw puzzle in support of clients.

Needles in a haystack

Darrow has 110 people working at its Tel Aviv headquarters (mostly in research and development) and at its New York offices, and has attracted $59 million in funding. 

“Our product is a system that monitors a huge amount of data that is publicly available, looking for needles in a huge haystack of data,” says Hayat.

So how often do they find a needle (or as they call it, a successful detection) I ask, expecting a show of fingers. 

“A thousand times a day,” she answers matter-of-factly.

“It’s very hard to understand how many infringements happen that we’re not aware of. It takes expertise and oftentimes a machine to compile all those sources together and see the bigger picture.”

Darrow’s legal analysts narrow down the many thousands of potential cases to the several hundred a year that end up being passed on to law firms with a proven track record in the relevant area of law, either for a per-case fee or as part of an ongoing partnership.

The lawyers get “the full story,” says Hayat. It’s not a “cold lead” with a vague chance of success. It’s a very solid prospect that has already been rigorously tested. 

Last year, Darrow’s cases generated $10 billion of a gross litigation value (GLV) – that’s the value of damages achieved through litigation. 

Changing corporate behavior

The cases Darrow is seeking out are impactful, says Hayat, because the aim is not simply a financial win for the plaintiffs. It’s to change corporate behavior and avoid future wrongdoing.

She can’t name specific cases but says underperforming pension plans are a good example of the wrongdoing the company’s AI picks up.   

“US employee pension plans sometimes invest in vehicles that are not the best in class. The ability to find those underperforming funds that consistently underperform requires ingesting — and I’m not kidding — millions of financial documents tracking those funds’ performance for a really long time, and finding anomalies. They had all the data to change course, but were negligent, careless around retirees’ money.”

No more grunt work

Darrow has direct rivals in every aspect of its business, but Hayat says no other company offers the same breadth. Many focus on improving efficiency – allowing law firms to draft faster, write faster, file faster and manage clients faster.

“But efficiency is not the way to grow your business,” she says. “We’re talking about growth through AI. Assuming you have capacity, instead of taking two cases a year, you now have the ability to take 20. What are the remaining 18 cases that you would take be like? And this is where we come into play. 

“We’re saying, you are going to work on the cases that you want. You’re not going to have to do that amount of grunt work maybe ever again, so what are you going to do with all that free time?”

Lawyers are keen to represent big groups of clients in cases that make a splash and make them cash. At the same time, fragmented groups of people with a common grievance get the legal representation they’d otherwise miss out on.

Named in homage to famed 19th century American lawyer Clarence Darrow, the company’s longer-term plan is to identify new, more diverse and more groundbreaking cases – beyond mass and class actions – and to expand from the US to Europe and elsewhere.

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