EMOTION
Give an emotionally framed reason for producing a good output. An example might help clarify what is meant here – watch this video which gives an example in prompt 4 of using emotion to produce a better outcome.
Transcript
Further reading
If you want to read the prompts in order to try it out yourself, please go to a copy of the speed journey poem [Tip: hold Ctrl and click a link to open it in a new tab. (Hide tip)] .
Ok, this one appears to be way out there – appeal to the GenAI’s emotional side? Use emotional blackmail? Didn’t we just say that AIs are not intelligent? Are we suggesting they’re emotional?
Well, no. Definitely not.
What we are seeing is a positive unintended consequence of training the underlying neural network on social media and other ’real-world’ content (instead of, for example, collections of newspaper articles, academic papers and company reports which tend to avoid emotional language). Much of the training material for some LLM models has included emotional language and this appears to have been captured in the neural network. It’s unintended, but it’s useful in prompting for some LLMs.
Law firm Addleshaw Goddard released a report in October 2024 outlining the results of their work to develop and test a robust method of using LLMs to review documents in the context of mergers and acquisitions transactions. They highlighted the importance of accurate, comprehensive prompting to achieve the best results, including the last tip - emotion.
“The process of using well-crafted and intentional prompts to instruct LLMs adds an advantage and improves performance.….. We found that adding urgency or importance to the prompts did slightly increase performance, and this emotive style of prompting is something that we will continue to investigate.”
Prepare a prompt for an LLM
Let’s now put what you have learnt into practice.
Prepare a prompt for an LLM using the PREPARE framework. You want it to produce a presentation outline for a presentation on employment law to either students, advisors or paralegals on the benefits and risks of using GenAI to answer legal questions.
Discussion
Here’s an example using the PREPARE framework – remember, for a real prompt each of the focus areas could be longer: prompts and parts of prompts don’t have to be short.
| PROMPT | Create a presentation outline for the following task: Create a presentation giving the benefits and risks of using GenAI to answer legal questions. |
| ROLE | Act as a knowledgeable lawyer with 2 years’ experience, and an interest in risk management and compliance. |
| EXPLICIT INSTRUCTIONS | The presentation is for either 2nd year law students, paralegals in a small law firm or advisors in a charity that provides legal support to members of the public . It should focus on the benefits and risks of using GenAI for legal queries. Include risks related to the submission of information to the GenAI and mitigations for those risks. Suggest examples for the students, paralegals or advisers to explore in their own time. |
| PARAMETERS | Present the outline in table form, showing headings and sub-heading. Do not use bullet points for this outline. |
| ASK | After you have finished, ask me some follow-up questions so that we can produce a better result. |
| RATE | Provide a confidence score between 1 and 10 for the quality of the outline. Then briefly explain the key reasons for the decision you made so that it can help me improve areas of weakness. |
| EMOTION | The task will help students or paralegals or advisors to understand their work, and I will be assessed on the quality of the presentation, so this is important to me and the students or paralegals or advisors. |
Why don’t you try out your prompt, or the example given above, in an LLM? As an input, you wouldn’t include the keywords, just present the text on the right-hand side of the table in a single prompt.
Further reading
If you are interested, you can find examples of prompting in legal practice in this supplementary course content – Examples of prompting in legal practice.
There are further examples of prompt frameworks in the Further resources section later.
Having considered the way to prompt LLMs with a single prompt, we will now consider another alternative way of instructing an LLM to produce something through conversational prompting.
