Articles Posted in Artificial Intelligence

In a recent blog post Ron Friedmann responded to a question posed in a legal technology publication:

“‘How do you envision the legal team of the future changing?’ The thesis of my answer: multidisciplinary teams ….

” … The complexity of the modern world makes many problems multifaceted. How many ‘legal problems’ are really business problems with a legal element?  Clients need lawyers to team with other professionals – and treat them as peers – for the best solution.

“A story from early in my legal market career illustrates the point. I had just arrived at a large firm to run practice support. A partner who knew I had a quant background asked me to help on a competition matter. A regional office of a regulator questioned our client’s action. It worried that many consumers would be adversely affected by a mistake it had made. I ran a simple time-series regression on the number of claimants to date. It showed a quickly diminishing curve. That is, a reasonable projection showed few new complaints would be filed. That one graph got the regulator to back off. That was a simple stats answer, not a legal’ answer.”

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The legal industry has been slow to embrace artificial intelligence (AI)*. But other industries and professions are not waiting to deliver AI’s enhanced precision and cost efficiencies.

How high do the stakes have to be before law begins to catch up with medicine?

On April 11, 2018 the U.S. Food and Drug Administration announced that it would, “permit marketing of the first medical device to use artificial intelligence to detect greater than mild level of eye disease retinopathy in adults who have diabetes”.

According to the U.S. FDA, the device: “Provides a screening decision without the need for a physician to also interpret the image or results, which makes it usable by health care providers who may not normally be involved in eye care.”

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In this blog I describe how to use effective management and liability prevention to control corporate legal costs. This calls for a certain amount of detail.

But in providing that detail I want to be sure not to lose sight of what this blog and my law practice are all about. Simply this:

When a company’s management is unhappy with the job their lawyers are doing, I help its owners or executives to put something better in place to achieve their business goals.

Company owners and executives need to take charge of legal and regulatory affairs in order to control legal costs, prevent liability, and otherwise cope with the legal and regulatory system’s increasing demands upon business. 

Because their lawyers won’t do it for them. 

Consider last week’s diagnosis (here and here) from Ken Grady — one of the legal industry’s leading visionaries: 


“Today, we talk about the legal industry going through a transformation. We point to new providers, the use of new tools such as project management, and the miracle of artificial intelligence and what it can and will do.

“But, if we look carefully at the legal industry, we can see that not much has changed from 100 years ago even with these tweaks ….”

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Take-away #3:

  • AI won’t replace a lawyer’s judgment.
  • AI will drive labor-saving technology to perform law’s “manual” tasks.

Jeffrey Carr put this best:

Jeff Carr is that rare general counsel who reduced total legal costs and proactively headed off liability before it arose — instead of the steady, single digit increases in legal budgets that are the norm. 

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Take-away #2 :

The applications of artificial intelligence to legal industry tasks is robust in three areas where the relevant data is publicly available.   

In Part I of this series I wrote that the use of artificial intelligence (AI) to predict outcomes in civil litigation isn’t happening any time soon because the necessary data is held mostly in fragmented silos. The relevant data is available from proprietary sources only — you need a law firm’s or company’s permission to access it — and you’re unlikely to get it.

In this Part II I turn to applications for AI to tasks where the relevant data is publicly available.

These applications are further along in development. They’re not yet the subject of widespread adoption (see my post on slow adoption of legal technology).

Legal Research:

Case law, statutes, and regulations are all publicly available. So a handful of tech firms are already applying AI to legal research.

Getting the most widespread attention in this group is Ross Intelligence,

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Application of artificial intelligence (AI) to business law is the subject of much hope and some hype among legal tech promoters, a handful of forward-thinking law professors, alternative legal services providers — and their avid followers in the legal media.

Which brings me to the other (much larger) group — law firm lawyers who base their livelihoods on billable hours and pursuit of associate leverage — and in-house lawyers who pretty much take their professional cues (they’d contend vociferously that this isn’t the case) from what their counterparts in outside law firms do.

Among this group the application of AI to business law meets with one of two responses:

  1. Harrumphing skepticism, or
  2. Damn-with-faint-praise — “we’ll look at this — later”.

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A new app from Silicon Valley highlights a legal industry that resists innovation to the point of self-parody.

Zero, a 2015 start-up headquartered in Los Gatos, California, now enlists artificial intelligence in the retrograde practice of lawyers billing by the hour:

“ … Today, lawyers work everywhere and anywhere, on mobile devices, and until now, that time has been fiendishly hard to capture. It was typically just written off. Not anymore …

“ … The result? Time that used to be lost is now captured, and billable. A typical attorney using Zero recovers between half an hour and an hour per day. Multiply that by your hourly rate. Now multiply it by 20 billable days in the month. Zero delivers ROI on the first day you use it – and keeps on delivering, day after day.”

In light of the severe and volatile legal and regulatory demands on business in 2018 — this is kind of like MIT or Cal Tech studying laser power — to deploy in buggy whips.

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