Project Management

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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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Pablo Ignacio Castillejo Program Manager| Cemex Mexico D.F, Df, Mexico
give context as broad as possible and ask for detailed references in data presented in the answer
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Jessica Black None Peterborough, ONTARIO, Canada
It’s smart to start with clear, specific instructions so it knows exactly what you're looking for. Test out a few different prompts if you’re not getting what you need at first, and refine as you go. Always double-check the info for accuracy, and keep an eye out for any biases or assumptions the AI might be making. Lastly, if you’re trying to reach a specific goal, give it feedback or examples and adjust your approach to help the AI stay on track.
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Yang Hock Yong Butterworth, 07, Malaysia
Be specific on the request, provide the example if have and test it see the output is meeting your requirement or not. You can re-post again the question to get the other set of answer.
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Shawn Briscoe Project Delivery and Support Services| OTIF Inc.
Here I should be advised to draw on the Quality Management and Risk management knowledge areas. The requirement is in the sphere of quality assurance. Benchmarks clearly help in defining expectations. If there are accessible industry standards and manufacturers recommendations, best practices or seminal project management references these may be useful also. In the end prompt designers should have some vision of the likely outcome, and set aside time to tweak. We don't want to envision AI as an added layer of effort between requirements and deliverables, but sometimes an openness to this point of view may give the right mindset from which to improve outcomes
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Stephen Marshall Production Manager| ASCD Alexandria, Va, United States
Understanding what you are asking for to achieve optimum results is paramount to receive the best AI feedback possible. Including the different Prompt clarifying strategies will surely bring your request into focus for the AI and allow for the most precise and usable feedback
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RENZO ORBEGOZO MONTOYA PAE Argentina
First of all, we must be clear about what we want. Secondly, the question must consider organizational aspects (external and internal) and the context of the project. The more specific the question, the better.
We must not forget that the IA's response must be reviewed by the Project Manager.
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RENZO ORBEGOZO MONTOYA PAE Argentina
First of all, we must be clear about what we want. Secondly, the question must consider organizational aspects (external and internal) and the context of the project. The more specific the question, the better.
We must not forget that the IA's response must be reviewed by the Project Manager.
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Milankumar Rathod India
Our objective is to receive GenAI response that are accurate, relevant, and aligned with our original goals.

Our query should be very specific and clear. We can provide contextual data and what kind of response we expect from the tool including evaluation criteria.

We can utilize appropriate prompt formula that best suites our requirement. Additionally we can go for refinement of prompt if needed.

This process ensures that the responses generated by the GenAI are closer to our expectations. At the end, we need to verify the responses using our skills.
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Anonymous
Ensuring that the prompt/request is asked in a way that GENAI understands.
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Dulaj M. Perera Sri Lanka
Always to remember output results will based on the quality, accuracy and relevancy of the input provided. Always to monitor and verify the output vs the real life scenario. Also, to consider ethical and fairness of the output.
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