Tag Archives: Legal Education

Incorporating AI Tools Into Your Legal Practice

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Image Generated by ChatGPT

I published Advice for Incorporating AI Tools Into Your Legal Practice along with Celia Bigoness and Robert MacKenzie in the National Law Review. It reads,

We have been speaking with many lawyers and law students about using generative artificial intelligence (AI) tools in their legal practice. We are struck by the fact that many of them have not been experimenting much, if at all, with the tools that are available to them – although many acknowledge that their clients are increasingly integrating generative AI into their businesses. We have been integrating a lot of these tools into our own professional lives, and here are some tips to help lawyers and law students get comfortable with AI tools that can help them, in big ways and small, with their job.

Put it on Your Home Screen

Put your preferred AI app (ChatGPT, Claude, etc.) onto your phone’s home screen and be sure to allow it to access your phone’s microphone. You will be surprised by how often you get the urge to ask the app slightly complex questions that a basic web search would not answer. (Hat tip to one of our kids for this idea.)

Start with the Familiar

Trusting the output of an AI tool without having the ability to verify its accuracy is okay if you are choosing a movie to stream tonight. It is not okay if you are using it to provide legal advice to a client. To get comfortable with AI tools, start using it for tasks that you have experience executing and reviewing. One simple way to start: explain a familiar task to the AI tool and ask it for guidance on how you can use it to complete the task.

As you use AI tools in newer areas, you want to review the cited sources in the AI output to confirm that you agree with the AI model’s interpretation of them. Sometimes they are plain wrong, sometimes the AI model misinterprets the cited documents, and sometimes those documents are out-of-date.

When the stakes are greater than your personal entertainment, you need to do a lot of due diligence before you adopt an AI tool’s findings.

Use Multiple Tools

Different AI models are built on different training documents and have different algorithms that they apply to those documents. There is nothing more edifying than running the same queries through a few general AI models and a few specialized ones (like those geared to lawyers, in particular). You will see a range of answers, from non-answers to highly specialized and accurate ones. You will start to become a more sophisticated consumer of the different models, understanding each of their strengths and limitations.

Tell It Your Needs

Most AI tools will tailor their responses to your preferences. In some cases, we created a prompt to instruct the AI tool that responses should be of the type that a lawyer would like to receive—providing sources, explaining its analytical steps, and what it did and did not consider. The AI tool responded that it would be precise, answer “above a lay level,” and “be candid about uncertainty.” This has improved its answers and had the side effect of reducing sycophantic language (“That is a very good question!”).

Use it for Your Pain Points

We all have some routine tasks that we find irritating. They are usually the ones we procrastinate on. For some, it is preparing slide decks. For others, it is drafting certain kinds of emails (unpaid bills, anyone?). Just getting a first draft from the AI tool often helps you to finish the work up. But for some tasks, like preparing presentation slide decks, you can save hours and hours of your time.

We have experimented with both general AI tools and those that specialize in slide deck preparation. They have pros and cons, but are generally very helpful. In all these cases, the AI tool’s time savings are in large part due to the fact that the AI tool is optimizing a task that you are capable of doing yourself. You are able to quickly verify and edit the output.

However, if you were asking the tool to analyze a topic with which you are unfamiliar, or perform a task that you’ve never done before—if you’re learning from scratch—you will still need to go through the painstaking process of checking sources and confirming output.

Play in Vaults

One game-changing use of AI tools is to upload documents to a secure location in the cloud (sometimes referred to as a “vault”) and hone the tool’s focus on only those documents. A transactional lawyer can upload hundreds of documents and quickly identify commonly appearing terms for comparison or inconsistencies among them. A litigator can upload thousands of pages of litigation documents and create a draft chronology of events. Again, the output cannot be taken at face value due to the functional limitations of these tools, but it can provide an extraordinary first draft that can then be verified and edited to the form you prefer. This can be a game-changing use of AI for lawyers, as long as you have verified the vault’s security in advance.

Use it as a Second Set of Eyes

This is a great and scalable tip for those who are skeptical of AI tools. After you have completed a written task, ask an AI tool to critique for clarity, coherence, and accuracy. Even an experienced attorney will get at least a couple of suggestions that will ring true. And of course, you can reject all of the suggestions that you disagree with. This is a great way to see if an AI tool can provide you with real value with very little investment of your time.

Along the same lines, for more advanced experimentation, you can use the AI tool to issue spot and offer counterarguments to your work to complement your own analysis. Again, this is very low stakes because you can reject anything you find wrong-headed or irrelevant. Of course, you need to be careful about sharing privileged information (see vault security above).

Preserve Confidentiality

We have spent more time than many of you would like looking at the Terms of Use of the AI tools we have used. Except for certain tools that are developed for legal work in particular, we believe that the attorney-client privilege can be compromised when using many AI tools because of how the tools use your input information.

We have had students and clients who wanted to use AI transcription tools to compile meeting notes. We have advised them that confidential information can be compromised by such tools and that we do not use them in our practice, at least at this time.

If you begin to use a tool with client-identifying information, be sure to confirm that you are complying with your professional responsibilities to preserve client confidences.

Don’t get Lazy!

We all read the headlines about lawyers who use AI to draft legal documents and do not check to confirm that the work product is correct. Those lawyers rightfully face professional discipline and reputational consequences. We can all say that we would never do that, but a new term has arisen to describe an unthinking reliance on AI: “cognitive offloading.” This offloading occurs when we reduce our own deep research and thinking because of an unhealthy reliance on AI tools.

Every time we complete a substantive task with AI, we need to ask if we have thought through the task as fully as we would have if we did it without the tool. If the answer is no, we need to dig into it again. Cognitive offloading is a particular concern for law students and younger generations of lawyers, who have grown up with technology and tend to be more comfortable using AI tools – and therefore more susceptible to this unthinking reliance.

Conclusion

From our discussions with lawyers in private practice, it is clear that AI tools are being used in the ways we have mentioned above. No doubt, more specialized tools are in development. It’s clear that AI will transform the practice of law in the coming years. Those who are new to AI can use these pointers to begin exploring how AI works. We think they can amplify their effectiveness to the benefit of their clients and themselves, so long as the risks that AI tools pose are thoughtfully addressed.

 

Integrating AI Tools Into Law School Teaching

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Robert MacKenzie and I have an article in Bloomberg Law, Law Schools Should Teach How to Integrate AI Tools Into Practice. It reads,

Now that artificial intelligence tools for lawyers are widely available, we decided to integrate them for a semester in our Entrepreneurship Clinic. We have some important takeaways for legal education in general and the transactional practice of law in particular.

First, employers and educators need to account for law students who already are using AI tools in their legal work and guide new lawyers about how to use such tools appropriately.

Second, different AI products lead to wildly different results. Just demonstrating this to law students is very valuable, as it dispels the notion that AI responses can replace their independent judgment.

Third, AI’s greatest value may be in refining legal judgment for lawyers in ways that can help new and experienced lawyers alike.

Legal AI Prep

As we were planning our syllabus over the summer, we provided formal training in AI tools designed for lawyers. A librarian provided us an overview of products from Bloomberg Law, Lexis, and Westlaw early in the semester.

Before the training, we asked students how they were using AI in the legal work. Their responses ranged from “not at all” to “I start all of my case law research on ChatGPT.”

We were confident that our students would be better off operating somewhere between those extremes. Over the semester, we demonstrated how AI could enhance the speed and quality of legal work, as well as the dangers of outsourcing research and judgment to an AI tool.

AI Tool Differences

Perhaps the training’s most valuable takeaway was that each tool had access to different databases of materials and had different constraints. We designed simulations that required groups of students to complete the same transactional tasks (drafting, researching, benchmarking market terms, and crafting effective client emails) using various AI tools.

In one exercise, students acted as counsel to a small business owner. The “client” emailed them asking about standard-form contracts relevant to their industry and what pricing mechanics such contracts use.

For the research stage of the task, all teams located a standard-form construction contract, but only half of them found the industry-accepted standard form that we contemplated. The others located this form later by modifying their search approach. This helped to demonstrate some limitations of AI tools.

For the client communication stage, some teams failed to answer the “client’s” questions. This isn’t something the AI tool could address on its own, and it reminded students to constantly refocus on the big picture in addition to individual tasks.

We found that AI tools built on widely available AI platforms such as ChatGPT produced the most responsive outputs and were most forgiving of haphazard prompting. But certain specialized legal AI tools often failed to answer the prompt.

This is a double-edged sword. Although the generally available tools were more likely to generate an answer, they also were more prone to providing unreliable outputs. By contrast, the specialized tools hallucinated much less frequently but regularly stopped short of fulfilling a request if it required work beyond their guardrails.

Delegating Work

Our final takeaway was that AI was surprisingly good at issue-spotting and double-checking a lawyer’s work product. These uses can help both new and experienced lawyers.

We used the idea of delegation to make this point to our students. AI is fast, adaptable, and always available, so it’s a great resource. But you should only delegate work to it when you can verify its output.

In one exercise, students had to issue-spot risks and approaches after a “client” described a business opportunity. Students brainstormed in small groups. There was a lot of overlap, but some groups thought of items that others had not. We added the items to a collective list, relying on our years of practice to guide the students through gaps that remained.

Once we had a strong collective list of items, a team asked an AI product to issue-spot the same scenario. It generated most of the items in our list, some that weren’t relevant, and—most importantly—a couple that no one had raised.

This was a valuable lesson: AI had something to add to our analysis, but we had to exercise independent judgment to determine whether its contributions merited further thought.

Important Takeaways

We asked students for feedback on our use of AI throughout the semester. The most valuable feedback was that they wanted to develop their own legal judgment and learn how and why certain tasks are completed before relying on AI.

This echoes the transition from book-based legal research to electronic legal research. There was some value in searching the law reports in the library, but electronic legal research won out because it was so much more efficient. Yet even with this enhanced efficiency, a responsible lawyer must understand how to build a strong research plan and actually read the cases they cite.

In the clinic, our goal is student learning. It was for this reason that we liked to deploy the AI tools at the end of our exercises: You do the work and then interrogate it with the AI tools of your choice.

Such an approach ensures law students get the benefit of struggling through first repetitions of new tasks while allowing them to generate superior work product with fewer drafts. This process requires discipline. Legal education and legal employers need to clarify the line between AI as a tool versus AI as a crutch.

We learned a lot about how AI tools can help law students develop into good lawyers. As those tools are integrated into legal practice, lawyers of all experience levels should take a self-conscious approach to using them.

The Changing Architecture of Real Estate Law Education

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Washburn Professor Andrea J. Boyack

The Association of American Law School Section on Real Estate Transactions and the Section on Academic Support are doing a call for Statements of Interest for those interested in presenting at an AALS panel meeting in January of next year. Panelists should be prepared to answer some or all of the following questions:

What real property law courses should law schools be teaching?

Who should be teaching these courses?

How should the courses be taught?

The Section on Real Estate Transactions and the Section on Academic Support seek to explore these questions and related issues at their joint online session during the 2021 AALS Annual Meeting, The Changing Architecture of Approaches to Legal Education: Real Estate Transactions as a Case Study.

Members of the legal academic community are invited to submit statements of interest in joining the panel of presenters who will discuss the following in the context of real property law and related courses (mortgage finance, securitization, commercial leasing, housing law, real estate development, etc.):

  • Law schools’ curricular choices
  • Course content and design
  • Teaching and pedagogy application.

As explained more in the “Background” section below, the Sections are specifically looking to highlight issues related to course offerings, curricular design, and teaching methodologies that can better prepare students for modern practice and ensure student achievement of course objectives. Statements of interest (including a description/summary of your proposed presentation) should be emailed to Andrea Boyack at andrea.boyack@washburn.edu by September 17, 2020.

There is no formal paper requirement associated with participation on the panel.

**Note that the AALS Annual Meeting in January 2021 will be held in a completely digital format, and individual registration fees will not be charged for participation in/attendance at the Annual Meeting.**

Background/Program Overview:

In the past decade, legal education has experienced a number of body blows from which it still struggles to recover. In 2007, Educating Lawyers: Preparation for the Profession of Law (more commonly known as the “Carnegie Report”) criticized the academy for insufficiently preparing students for legal practice. In the aftermath of the 2008 Financial Crisis and global recession, many attorneys (especially from Big Law) were laid off and new graduates faced fewer and fewer job prospects. Mainstream and social media spotlighted lawyer and law student discontent, worries about sustainability of legal careers and the high cost of legal education, schools skewing data to try to game US News rankings, and the growing number of for-profit institutions. Law firms and their clients started exhibiting an increasing hesitancy with respect to hiring and training inexperienced attorneys. Law school admission rates tumbled as college graduates changed their opinions about the value of a legal education, as the ABA began making new demands of law schools pertaining to skills training and assessments. The practice of law, in the meantime, has changed dramatically, with automation, internet resources, and contract attorneys (or non-attorneys) taking the place performing tasks lawyers once controlled. Furthermore, schools have struggled to adapt to different expectations of the Millennial and Gen-Z generations of law students. Then, in March 2020, legal academia and law practice suddenly shifted to operating (temporarily?), primarily in the digital/virtual realm. The world has changed over the past 15 years, the practice of law has changed, and law schools struggle to adapt quickly enough to stay relevant and valuable.

The evolving demands and expectations for law schools are not just issues to be addressed by deans and administrators. Nor can the task of preparing new lawyers be allocated exclusively to clinicians and adjunct instructors of specialized “skills” classes. Doctrinal professors may want to also change their approach in the classroom in response to new industry demands for practice competencies and evolving attorney roles in an ever-changing marketplace, but have our pedagogical approaches adequately adapted to this new world? And how has law schools’ increasing reliance on adjunct professors impacted the students’ experience and preparation for the bar and beyond? In short: In what ways do we need to rethink what we teach and how we teach it in order to remain optimally relevant to tomorrow’s lawyers.

Eligibility:

Per AALS rules, faculty at fee-paid law schools, foreign faculty, adjunct and visiting faculty (without a full-time position at an AALS member law school), graduate students, fellows, and non-law school faculty are not eligible to submit a statement of interest.