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Sikandar Hayat
Islamabad, Pakistan
To ensure accurate, relevant, and goal-aligned results from AI systems, define clear objectives, provide high-quality data, and understand the AI model's strengths and limitations. Regularly monitor and evaluate performance, check for biases, and use an iterative feedback loop for continuous improvement. Prioritize transparency and involve domain experts for validation. Test the AI under various scenarios and adhere to ethical guidelines to ensure the AI's broader impact is positive.
When using AI systems, it's crucial to start by clearly defining your objectives and the specific outcomes you aim to achieve. Regularly validate the AI's outputs against these goals to ensure alignment. Incorporate diverse data sources to enhance the accuracy and relevance of the results, and continuously monitor the AI's performance, making adjustments as necessary. Additionally, involve subject matter experts to review and interpret the AI-generated insights, ensuring they are contextually appropriate and actionable. Lastly, maintain transparency in your AI processes and be prepared to iterate based on feedback and evolving project requirements.
I think practice make perfect, therefore it takes time and effort to develop your ability / skill to effectively use generative aI for PM tasks. the nature of the business may dictate more thorough prompting to get useful information
To ensure AI systems provide accurate, relevant, and goal-aligned results, start by defining clear objectives and using high-quality, relevant data. Continuously monitor AI outputs, maintain human oversight for validation, and implement a feedback loop for system refinement. Be vigilant about potential biases and keep the AI system updated with the latest data and technological advancements.
Matthew Loew
Bonita Springs, FL, USA
I was using AI very generically until now. This is great information which I need to educate myself on. Looking forward to a deeper understanding of this.
accurate inputs means accurate outputs
Anonymous
I would make the prompt / request as specific as possible to narrow the possibility of too vague or broad of output. I would also ask for its sources. Then I would conduct an expert review of the output and review a sample of the references in more detail to confirm the output validity.
Checking reference sources and rephrasing the prompts
Charles Baggett
Charlotte, Nc, USA
Continuous refinement is key. Take the time on the front end to develop a specific initial prompt that has details related to your situation and goals. Using the CREATE method is a great start.
After each of the LLM's outputs, review them carefully and provide additional data and information to refine the outputs you receive. You will likely go back and forth with the LLM several times before you have an acceptable output.
SAMI RIZVI
Bahrain
The best practice would be to evaluate the GenAI response with Subject Matter Expert where you do not have much knowledge and risks are involved to get the outcomes and meet the project's intended Goals.
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"I might repeat to myself, slowly and soothingly, a list of quotations from beautiful minds profound; if I can remember any of the damn things." - Dorothy Parker |
