Dickerson: How I learned to stop worrying and love artificial intelligence

  • Print
Listen to this story

Subscriber Benefit

As a subscriber you can listen to articles at work, in the car, or while you work out. Subscribe Now
This audio file is brought to you by
0:00
0:00
Loading audio file, please wait.
  • 0.25
  • 0.50
  • 0.75
  • 1.00
  • 1.25
  • 1.50
  • 1.75
  • 2.00

The recent advances in generative artificial intelligence are undeniably the latest cause célèbre in the legal industry. Many have prophesied AI’s impending disruption of white-collar work for years now. The legal industry has remained largely static amid these predictions. However, AI is a uniquely powerful technology that may affect the legal industry in ways that previous technological developments have not. Predicting the future is difficult, but history is a useful teacher. This article explores the ways in which the history of legal technology can inform expectations for AI’s impact and how ultimately it will destabilize the legal industry, regardless of its effect on the labor force.

It’s not news to anyone that the legal industry is notoriously slow to adopt new technology compared to its corporate counterparts. In fact, it was only in 2012 that the American Bar Association adopted Rule 1.1 of its Model Rules of Professional Conduct. In response to the proliferation of technology in communications, research and e-filing, the ABA declared that “a lawyer should keep abreast of changes in the law and its practice, including the benefits and risks associated with relevant technology.” Some lawyers may have been slow to implement new technology in their legal practices, but it’s a useful reminder that we are ethically obligated to stay informed.

The technological developments preceding the adoption of Rule 1.1 were important but had a relatively benign impact on the labor force. The first notable development in legal tech came in the 1950s with the use of the dictation machine. This invention didn’t supplant the need for legal assistants; it simply enabled practitioners to operate more efficiently by creating space for support staff to work on other matters, and attorneys could work independently of their assistants. Generative AI has already proven useful for matters such as drafting routine documents and correspondence, but it has not threatened legal support staff or attorney jobs due to the necessity of a human to interpret and revise documents or communicate with clients about complex issues.

The next development in legal tech, and certainly the most profound, came with the advent of personal computers, word processors and legal research databases. Lexis’ 1973 UBIQ terminal sparked one of the greatest efficiency gains in recent memory through online legal research. The increasing power of personal computers to handle specialized legal applications and proliferation of word processors supercharged law firms’ ability to take on work. In turn, lawyers were increasingly enabled to allocate their time to other client matters, administrative tasks and business development. Again, these inventions didn’t replace librarians, support staff or attorneys; they just created more sophisticated ways for legal professionals to do their jobs with greater efficiency and in higher volumes. And with that came an expansion in the legal labor force, as upgrades and tech support became a necessity in the modern law practice.

After legal research systems, communication took off. Fax machines, low-cost printing, intra-office email and email to users outside an organization increased the speed at which information and documents were shared. The progress of the internet and instantaneous communication helped revolutionize law firm marketing, and competition became fierce. The current iterations of AI programs have become quite good at accessing or receiving information and summarizing it in concise ways. However, we shouldn’t expect AI to drastically reduce the number of legal professionals yet. Humans are hiring humans, and they are the ones generating and directing the ideas through various communications. AI can develop clever written content, but firms are not rushing to fire their marketing directors or website vendors, as human attention is still needed to direct and inform marketing and client communication efforts.

More recently, however, technology has affected the legal labor force on the margins. The development of computer-based case management systems, cloud-based applications and specialized software have revolutionized case management, time and billing, docketing, and specialized tools for areas such as real estate and IP. These inventions may have reduced the need for legal support staff in organizing large swaths of documents, but it has created additional roles for understanding, operating and troubleshooting these systems. AI has already begun the task of automating back-office functions such as client chatbots, opening new matters, clearing conflicts and paying expenses. From an economist’s perspective, the recent development in technology has certainly increased efficiencies in the workplace, but it has not sparked the productivity revolution as predicted.

Those bullish on AI’s capacity to disrupt the legal industry may argue that we’ve barely scratched the surface of the technology’s abilities. MIT professor David Autor, an expert on labor economics and technological change, has elegantly observed that, “Before, progress was linear and predictable. You figured out the steps and the computer followed them. It followed the procedure; it didn’t learn and it didn’t improvise. … ChatGPT and the like do improvise, promising to destabilize a lot of white-collar work, regardless of whether they eliminate jobs or not.” Indeed, many believe it could revolutionize our industry by competently engaging in document analysis, contract review, legal research and even drafting legal documents, regardless of its impact on the labor force.

But this shouldn’t be cause for alarm. While AI is improving its capabilities with low-level document analysis, it cannot yet perform the critical functions that paralegals and attorneys are specifically hired to perform. AI cannot assess the quality of caselaw, access historical documents, discern between what’s real and what’s been created out of nothing. It’s just a tool, only as good as its user. It creates content out of what is already out there, with no authority, no understanding, no ability to correct itself and no way to identify novel ideas.

If history teaches us anything, it’s that there will always be luddites. As legal commentator Alex Su has observed, it’s safe to predict that our corporate clients will be quicker to adapt the technology than us; smaller law firms will be able to experiment with AI more quickly than BigLaw; and BigLaw may embrace early but will be slow to streamline AI across all offices. Someone to watch in this space is Faegre Drinker Biddle & Reath LLP. The firm took an early stance on AI and is working on programs to help clients navigate the emerging regulatory frameworks and automate aspects of M&A due diligence. Westlaw’s Precision Legal Research and Lexis + AI are also developments that will serve as early indicators of how AI will be used in legal practice.

However, if there’s anything history can teach us, it is that sometimes we need to resign ourselves to the unknown unknowns. AI is a uniquely powerful technology, and alarmism aside, it will profoundly impact the legal industry. This underscores the sage wisdom that adaptability is more important than predictability, and those legal practitioners that learn to hone the power of AI will have a competitive edge in the ever-changing marketplace and development of the law.•

__________

Conner Dickerson is a member of Cohen & Malad LLP’s Business Services, Real Estate, and Business Litigation practice group. Opinions expressed are those of the author.

Please enable JavaScript to view this content.

{{ articles_remaining }}
Free {{ article_text }} Remaining
{{ articles_remaining }}
Free {{ article_text }} Remaining Article limit resets on
{{ count_down }}