Not even three months old and ChatGPT has disrupted multiple industries across the globe, including legal operations. The craziest part is that ChatGPT is still growing and maturing. In time, as it gets fed more data, more opportunities for leveraging this powerful tool should unlock themselves.
What Is ChatGPT?
Developed by OpenAI, ChatGPT is an interactive language model that produces human-like text in response to prompts. OpenAI used the GPT-3 language model as the foundation for ChatGPT.
GPT-3 is arguably the more powerful model of the two, but ChatGPT is more user-friendly and intuitive, in part because additional data was used to train and adjust the latter for a chat application.
ChatGPT is just one outcome of adjusting GPT-3.
GPT-3 was trained using a huge amount of text from various sources such as books, articles, websites, and social media posts. Consequently, it can generate text in a wide array of styles and genres.
However, it can easily be modified for a specific purpose, as OpenAI did with ChatGPT. All it takes is enough examples of a certain type of text to retarget GPT-3 for one’s own purposes.
There are two primary approaches to retraining GPT-3: fine-tuning and feeding.
Fine-tuning vs feeding
To fine-tune GPT-3, several hundred samples of possible prompts and expected outputs are needed. The more samples there are, the more reliable GPT-3 will be at providing the expected output.
In contrast, feeding is more of a quick-and-dirty method. It’s possible to repurpose GPT-3 with just a few samples of work, but the reliability and predictability of results are significantly lower.
When feeding GPT-3, you first provide the model with a couple of samples. The model will process the samples, look for patterns, and then complete your request based on the information you provided.
It’s faster and not as resource-intensive, but as can be expected, the smaller body of evidence will lead to mixed results. In real-world terms, the return of fine-tuning versus feeding is like a Michelin-star chef versus a home cook.
ChatGPT in Legal Ops
ChatGPT unlocks several possible opportunities for legal operations. Strategic, meaningful implementation of the model could enable legal ops to speed up and scale their contracting processes.
Here are a few major use cases. This list, however, is just the tip of the iceberg:
One drawback of ChatGPT and GPT-3 is that they are limited in terms of the amount of text they can generate. Also, the longer the prompt, the less reliable the result will be.
Consequently, these models aren’t well-suited to drafting an entire contract. However, they are perfect for drafting individual clauses in accordance with specific instructions.
This allows legal teams to quickly create error-free clauses in moments. All lawyers will need to do is indicate the requirements and check the end result.
For better or worse, legal jargon is dense and difficult to work through. This, in turn, causes bottlenecks and snags in workflows. It also results in a greater work burden for legal as non-legal teams constantly turn to lawyers for explanations.
ChatGPT can simplify legalese so that non-lawyers are able to understand the contents of any legal document. This both speeds up workflows while freeing legal ops from constant questions.
Another minor limitation is that ChatGPT contains data only up to 2021. This means that as far as ChatGPT is concerned, everything that happened in 2022 “never happened”.
This isn’t a dealbreaker. ChatGPT can be successfully leveraged even if it doesn’t contain all data. It just requires a bit of quality control to guarantee that facts and data are correct.
Still, ChatGPT and GPT-3 can both be used to speed up the search of legal documents. Whether it’s locating simple names or conducting a full-text search, the model can be deployed to cut down on time spent on tedious searches. This enables legal to spend more time on analysis and less on discovery.
If you’re not convinced by ChatGPT’s ability to browse documents, then consider that Microsoft announced that it’s planning to use ChatGPT to power its Teams and Bing platforms.
GPT-3 Features in ContractWorks
ContractWorks is the first contract management solution to offer a fully functional contracting solution that allows legal teams to capitalize on GPT-3’s capabilities. Not a prototype, not a beta, but rather a complete product.
ContractWorks currently enables two contracting features that are built using GPT-3: Clause Creator and Simplify.
Clause Creator can be found during the contract redlining stage. Simply add any requirements that the clause should include and indicate the target length. After generating the clause, you can review the language and make any edits before inserting it into the contract.
Here’s a sample of what Clause Creator can produce:
Prompt: Generate a non-compete for 90 days for both parties after the contract ends.
Output: Both parties agree not to compete with each other for a period of 90 days after the contract ends.
Clause Creator empowers legal and non-legal units to handle contracts faster and draft clauses more efficiently as clauses can be created and negotiated in seconds, instead of days.
The second feature that uses GPT-3 is Simplify, which does exactly as the name suggests – it simplifies language.
To use Simplify, select the text you want to “translate” into simple words. GPT-3 will process the text and produce an easier version that you can copy and send to anyone.
With Simplify, complex legalese transforms into simple English in moments. Here’s a sample of Simplify in action:
Legalese: Mutual Obligations. Each party discloses its Confidential Information to the other under this agreement. “Discloser” will mean the party disclosing Confidential Information and “Recipient” will mean the party receiving Confidential Information from Discloser. Each of the parties is a discloser in respect of Confidential Information owned by such party.
Simple English: Each party will disclose its confidential information to the other party. The party that discloses the information is the discloser and the party that receives the information is the recipient.
Simplify provides non-legal teams the freedom to focus on the meaning and contents of contracts while liberating legal ops from always fielding every single question. With Simplify, legal can merely point non-legal to Simplify for basic explanations
Tips for Leveraging ChatGPT
Although ChatGPT has already made a massive splash on current practices, it’s not infallible. Here are some tactics that will help you benefit from implementing the current iteration of ChatGPT:
● If the answer you receive is irrelevant, reword your prompt so that it’s simpler and more specific.
● If the answer you receive continues to be irrelevant, select data to fine-tune GPT-3 or completely rethink the wording of your prompt.
● Don’t use ChatGPT to draft large amounts of text.
● Use keywords to help the model ensure the answer is relevant.
● Keep in mind that ChatGPT contains data up to 2021, not later.
These tips will help you successfully integrate ChatGPT and GPT-3 to accomplish your contracting needs while mitigating any potential downsides of ChatGPT.
For savvy, digitally literate lawyers, ChatGPT has the potential to completely reshape the way they go about their daily work. However, in its current form, ChatGPT is better suited as a highly intelligent legal assistant who is capable of accomplishing menial, less interesting tasks.
If you want to find out more about how ContractWorks can help you incorporate ChatGPT and GPT-3 into your contracting workflows, book a demo with our team.
For more information about how in-house legal teams can use GPT-3 in contracting, and how to train this technology to produce high-quality content, download our free guide, How to Train GPT-3 AI to Become Your Legal Assistant.
Some of this content was previously published on the ContractWorks blog.