Project Management

Please login or join to subscribe to this thread

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

linkedin twitter facebook   Artificial Intelligence  
avatar
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?

Sort By:
< 1 ... 59 60 61 62 63 64 65 66 67 68 69 ... 191 >
avatar
Alvin Guillermo Rodriguez Arguello Project Manager| INFRASTRUCTURE, TECHNOLOGY & OPERATIONS Nindiri, Masaya, Nicaragua
To ensure AI-generated results are accurate, relevant, and aligned with your goals, clearly define your objective, refine queries as needed, and verify information from reliable sources. Be aware of AI limitations, provide context for better accuracy, and check for biases or ethical concerns. Always review and validate outputs before implementation to ensure quality and relevance.
avatar
Anonymous
Making sure the AI is getting accurate data based on the data or the lenses you are working on. AI needs to be trained just like a puppy, making sure it knows you to give you the best outcome.
avatar
Rahul Rathore Technical Professional| KBR Inc. Unnao, Uttar Pradesh, India
1. Reliable, structured and clean data,
2. Clear requirements about task,
3. Metrics,
4. Lesson learned
avatar
Ravi Shanker Program Manager| TTEC digital Hyderabad, TG, India
ok
avatar
Alexandre Fodor São Paulo, São Paulo, Brazil
Hi Sarah,
One best practice is being as more clear as you can to get better answers from AI systems. Once you receive an answer you have to check whether this make sense or not.
avatar
Luis Ricardo Valdivia Pinto Senior Programs and Projects Manager. PMP®| Consulting Santiago, Rm, Chile
In my opinion and based on what I reviewed in the PMI course "Talking to AI: Prompt Engineering for Project Managers", some of the best practices to ensure that the LLM responses we are using are accurate, relevant, and aligned with our original objectives are: Request and validate the sources used by the AI, ideally use the CREATE formula to create the prompt for the AI, perform iterative prompt refinements, provide detailed examples that clarify what we expect as a response and that the requirement described in the prompt is as specific as possible.

Best regards,

Luis Valdivia
To achieve high accuracy, relevance, and purpose in AI-generated results, we need to: clearly define objectives, refine questions as needed, and verify information from reliable sources. Understand the limitations of AI, provide additional context to enhance accuracy, and be mindful of biases or ethical issues. Always review and confirm results before use to ensure quality and suitability.

Be clear and specific in your prompts/queries. Provide context and details about what exactly you're looking for.



Review outputs critically. Don't assume everything is accurate - fact-check key claims or information.



Ask follow-up questions to clarify or expand on responses.



Compare outputs across multiple queries or AI systems when possible.



Provide feedback if you notice errors or misalignments, so the system can potentially improve.



Be aware of the AI's limitations and potential biases. Know what types of tasks it's suited for.



Frame queries to align with your specific goals and use case.



Break complex tasks into smaller, more manageable queries.



Iterate and refine your prompts based on initial outputs.



Combine AI outputs with human expertise and judgment, rather than relying solely on the AI.



Stay up-to-date on the capabilities and limitations of the specific AI system you're using.



Document your process and results to track effectiveness over time.



The key is to view AI as a tool to augment human intelligence, not replace it entirely. Maintaining a critical and iterative approach will help ensure you get the most accurate and relevant results.

avatar
Divine Ningue Arpellet Global Manager, Finance Operations| Ceridian Minneapolis, Mn, United States
For accuracy purposes, definitely impose literature sources to be cited.
avatar
Roseanne Laudisio Bethpage, Ny, United States

When using AI in at work it’s important to protect sensitive data like personal information (PII), health records (PHI), financial details, and company secrets (Intellectual Property). This includes uploading documents that contain key information that the model needs or examples to help train it.

If you are not sure if your company is using an AI model or AI technology that guarantees data privacy, you must clean or anonymize the information before using it. This reduces the risk of privacy breaches and keeps your company compliant with data protection policies and regulations. When in doubt, check your company policy or reach out to someone in your organization (e.g., CIO, CISO, Legal Team, HR) who can guide you if you’re unsure how to handle sensitive data or have questions on how to use AI technology within your organization.

< 1 ... 59 60 61 62 63 64 65 66 67 68 69 ... 191 >

Please login or join to reply

Content ID:
ADVERTISEMENTS

"It's no coincidence that in no known language does the phrase "As pretty as an airport" appear."

- Douglas Adams

ADVERTISEMENT

Sponsors