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When using AI systems, what are some best practices for ensuring the results you receive are accurate, relevant, and aligned with your original goals?

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Sarah Philbrick
PMI Team Member
Director, Learning Design & Development| PMI Asheville, NC, United States

Validating and checking outputs is critical when working with AI systems like Generative AI. Such validation approaches may include establishing clear criteria, implementing strong testing protocols, and continuous refinement.

In your experience with AI, what are some best practices for ensuring the results you receive are accurate, relevant, and aligned with your original goals?
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Nicole Miller Broken Arrow, Oklahoma, United States
Early on using AI in my projects, I have to admit that I was quite naive. I didn't validate the output and took it as truth. I was unaware of how to validate, using the various techniques explained during this course.
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Mikaella Darum Operations Effectiveness Manager and Change Manager| RELX Reed Elsevier (Philippines) Quezon City, Philippines
It all starts with the objectives and key results for the process or a product being supported. Common performance indicators include accuracy or how close the output is to an expert's, and response time which is how quick it is able to generate an output. Focusing on the bigger value or outcomes are the revenue generated from offering an AI solution to customers. Of course, we need to ensure we are compliant by adhering to ethical standards of usage.
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Michael Chin MGA Brooklyn, NY, United States
Validating and checking outputs iteratively with progressively deeper prompt inputs will certainly help here. Choosing the best prompting pattern is important as well as the data iteratively introduced. This is where good quality data through practices such as data labelling and annotation help to 'plug-the-hole' so to speak in addressing hallucinations, poor responses.
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Puja Mehra Sr. Project Manager| ACI Worldwide Princeton Junction, Nj, United States
It is hard to achieve preciseness especially when you are in an industry which restricts you to train AI. However, you could leverage AI by reiterating and redefining your asks closest to what you are looking for.
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Candida Tocci Other Calgary, Alberta, Canada
Know that the best response is not on the first try
Keep asking questions
Look at which formulas to use ex. RTF or CREATE
Ensure you understand your company's/project goals
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Narendrasing Patil Project Manager| TE connectivity India Pvt Ltd Pune, Mh, India
good
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MOHAMED ATTIA new Cairo, C, Egypt
It is very important when dealing with artificial intelligence to take into account the description of the personality, context, task, request, etc., otherwise we will get random results that are likely not the desired answers at all. Also, review it carefully, evaluate it afterwards, and revise it in case of use before publishing it elsewhere.
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Louis Blais Vancouver, British Columbia, Canada
Jun 08, 2024 11:44 AM
Replying to Giorgos Sioutzos
...
Providing the specific context in clear and consise way is essential.
I am a new fan of the "CREATE" model which incorporates Character, Request, Example, etc. into a prompt engineering framework. It really helps to get refined and precise results.
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Tamara Martinez Lake Worth, Fl, United States
Since I am new to this and learning. I think the best thing is reviewing the information and asking for references. You just can't blindly accept the output.
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Anonymous

Clear and Specific Instructions: Clearly state your query or task. The more specific you are, the better the results will be.



Context Matters: Provide as much context as possible. This helps the AI understand the full scope of your request.



Iterative Refinement: Don't hesitate to refine your queries. If the initial response isn't quite right, tweak your question or add more details.



Verify Information: Cross-check the information provided with other reliable sources. AI can sometimes produce incorrect or outdated responses.



Feedback Loop: Provide feedback on the responses. This can help improve the AI's future performance.



Ethical Considerations: Ensure your use of AI aligns with ethical standards and guidelines, respecting privacy, copyright laws, and avoiding harm.
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