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AI Used in UCI Law School Tax Courses

University of California-Irvine School of Law has begun to teach budding attorneys how artificial intelligence can help analyze outcomes of thorny tax cases.

Professor Omri Marian told the Business Journal that software from Toronto-based Blue J Legal Inc. slashes the time needed to crunch numbers, an example of how common tasks, even in complex areas, can be automated.

“Something that would’ve taken 8 to 10 hours of work, of client billing, can basically take 20 minutes,” he said.

He is enthusiastic about such products’ efficiencies, but emphasizes AI’s limits to make actual predictions for clients.

As tech’s role in tax practice grows, “most tax advice will be somehow relying” on it—but “under no circumstance” would attorneys offer legal counsel solely “because some software told me.”

Messy Data

Instead, it’s about integrating new modes of machine-based analysis with the law, both in the hands of talented and prepared attorneys.

UCI Law has moved on that motif before.

It has run a tax course built around data analytics software from Irvine-based Alteryx Inc. (NYSE: AYX).

Students get “thousands and thousands of rows of messy data and they’re required to render legal tax advice” based in part on its analysis.

Marian said the law school is “certainly the first and right now I think the only” program using both products. He said one way to offer a unique tax law program is “preparing tax students for what the future may hold.”

This term he’s teaching the first Blue J class with about 25 students, including mid-track law students and those with a J.D.

That’s Accurate

Blue J Legal Chief Executive Benjamin Alarie said software algorithms look at past tax cases to assess the odds of future results. Blue J software might consider, “if something were challenged in court, whether the taxpayer would be successful or not in, say, [t]aking that [tax] deduction.”

Algorithms compare and incorporate tax codes and regulations, court cases, and revenue and private letter rulings, and run it against a client’s situation. Alarie said his software’s part of a tax lawyer’s work is, “more than 90% accurate in predicting the outcome.”

Alarie is a full-time business law professor at the University of Toronto; he was on UCI’s campus last month speaking at a conference on machine learning and tax law practice.

“This is a collaboration,” said Alarie, who launched his firm in 2015.

Blue J customers include law firms, accountancies and government agencies, mostly in Canada, with a growing U.S. presence.

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Kevin Costelloe
Kevin Costelloe
Tech reporter at Orange County Business Journal
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