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Over the last semester, I’ve been teaching two classes at Michigan State University College of Law, one called AI and the Law and the other called New Technologies and the Law, and a class at University of Michigan Law School called Legal Technology Literacy and Leadership. All three classes pushed me to keep up-to-date with the nearly-daily developments in AI, ChatGPT, and LLMs. I also did quite a lot of experiments, primarily with ChatGPT, especially GPT-4, and with Notion AI.

I haven’t written or spoken much about it (unless you happen to be an unsuspecting friend of mine who starts asking me about the topic), with the exception of one of my LegalTech Hub law department innovation columns called “Innovation Ideas: Quantity, Quality, and ChatGPT, on The Kennedy-Mighell Report podcast here and there, and a bit on some other podcast interviews I’ve done. I’ve been hesitant to report on some of my learnings publicly until I have a greater degree of comfort (the example in the column) – and things change all the time. I’m still hesitant, but I have something that seems ready now.

Since the semester ended, I’ve done much more experimenting than ever before, primarily in the areas of personal productivity and innovation, but in a broad range of other areas. Unlike many others, I’m not ready to make any big pronouncements, but I’m currently fascinated by the points I run into constraints and what I’m learning there. For example, I tried two experiments this morning that seemed reasonable but were big failures.

The experiments I’m doing fit into my original concept of the Kennedy Idea Propulsion Laboratory, my project to create a think tank and R&D lab focused on legal innovation.

One goal of Kennedy Idea Propulsion Laboratory is to move ideas into productization, especially the productization of services. The first example of a productized service I created is called Legal Innovation as a Service.

I was thinking about how the Legal Innovation as a Service product would be a perfect place to try to incorporate some AI into a productized service. So, I’ve spent some time working on ways I might be able to do that.

I’ve reached the point where I have some approaches that seem complete enough to move out of the lab and start testing with the Legal Innovation as a Service product.

These are limited AI helper tools that are “human (i.e., Dennis) in the middle” approaches. I believe that they can significantly improve quality and enhance the product’s value, while avoiding confidentiality and other risks.

And I’m ready to test them.

What I’ve decided is to start using them with new orders from customers who want to try them. I’ll keep the price of the Legal Innovation as a Service flat fee the same at least through the summer (but possibly through the end of the year.) I want to test these approaches and get some good data about them to evaluate and make improvements to them.

Intrigued? Reach out to me.

My primary focus these days is on transformative innovation for law departments with a mandate to move innovation forward. However, I’ll consider other customers because the same approaches should work elsewhere in the broader legal world.

You can learn more about Legal Innovation as a Service offerings here. I’m excited to find out how these enhancements will work in the real world.

You can schedule a Zoom meeting to talk about Legal Innovation as a Service with me through my Calendly page.

[Originally posted on DennisKennedy.Blog (]

Want to schedule a Zoom call to talk with me about Legal Innovation as a Service, Speaking, or other services? Schedule a Zoom with Dennis via Calendly.

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