| | 19CIOReviewSEPTEMBER 2020Law: In some other fields, technology developers have been able to fully understand certain services that humans previously provided and replace those services with AI. In law, however, there are professional restrictions in the U.S. that prohibit non-lawyers (or even lawyer employees of any company or firm that is not 100 percent lawyer-owned) from providing legal advice. Although some have argued that those restrictions are anti-competitive, and should be relaxed or eliminated, the truth is that legal services do tend to be complicated and it is difficult for non-lawyers to develop and apply the technology without a lot of help from practicing lawyers. A case in point is TAR. Despite being the biggest AI success in law to date, it may also be the biggest disappointment--even today, more than a decade after the first TAR programs were developed, most litigation document review is still manual. One reason is the lack of an easy and universally-applicable or accepted workflow for using TAR. Consequently, some companies that have tried to use it have found that, with the concomitant protocols, negotiations with opposing parties, and potential need for judicial oversight, trying to use TAR in place of human review can end up being more expensive than traditional key word filtering and human review. No company should ever try to apply TAR in place of human review without the close involvement of lawyers who are knowledgeable about TAR. A Brighter Future for AI and the Law?Despite the above impediments to large-scale adoption of AI in the legal industry, we foresee a brighter future. A number of law firms and in-house legal departments are now teaming with software developers and vendors to find new ways to use technology to deliver legal services better and less expensively. A handful of law firms have even launched technology subsidiaries devoted to developing technology tools for the provision of better and/or less expensive legal services. One example is Gravity Stack, Reed Smith's technology subsidiary, and their partnerships with Heretik and LegalSifter to expedite contract review and analysis employing AI. Other examples include programs that can help budget, optimize and report on litigation document review, analyze and provide initial advice in regard to data breaches, assist with due diligence project management, and even programs that can anonymize or pseudonymize documents to assist with GDPR compliance or other protection or redaction of confidential data. While not all of these tools utilize machine learning, each of them leverage technology to reduce time, reduce costs, and enhance quality of the legal services provided.Based on the above developments, and continuing advances in the science and technology of AI, you can expect that the next decade will be far more exciting and transformative than the last decade has been with regard to the growing development and adoption of AI for legal applications. David R. Cohen
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