Director, Learning Design & Development| PMIAsheville, 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?
Jason DeonarainSenior Manager, Agile Transformation| Northwell HealthFarmingdale, NY, United States
I like to treat outputs from AI models as a foundation on which I build on. Ensuring that foundation is solid requires two important things:
1. Ensure that your prompts are specific, add details relevant to the case, and that you avoid being vague or not providing context.
2. Check the output; always proof the output to make sure it makes sense- even if it is cited. Saving Changes...
Jane MartelSenior Project Manager| Arapahoe Library DistrictCo, United States
To ensure the results I receive are accurate, relevant, and aligned with my original goals, I read the output carefully and check the cited references. Saving Changes...
Anand RajakumarOperation Manager| Mouser ElectronicsVijayapura, KA, India
The productivity of artificial intelligence may boost our workplaces, which will benefit people by enabling them to do more work. As the future of AI replaces tedious or dangerous tasks, the human workforce is liberated to focus on tasks for which they are more equipped, such as those requiring creativity and empathy. Saving Changes...
a) use RTF method to prompt correctly so that the role is known , Tasks defined and Format is clear.
b) use CREATE method to prompt so that character is defined, request is proper, examples are in place, adjustment is tuned, types and evaluation are also prompted Saving Changes...
Results from prompt inputs must be carefully curated, moderated and iterated by the PM. Additional sanity checks by SMEs in some instances might be very useful. Saving Changes...
Daniela ZuppichinDirector de Proyectos, Agile Trainer| SiPro360 Project ConsultingCiudad Autonoma de Buenos Aires, Argentina
El desarrollo de sistemas de IA exitosos requiere la colaboración de equipos multidisciplinarios que incluyan científicos de datos, ingenieros de software, expertos en el dominio y otros profesionales. Esta colaboración garantiza que se aborden todos los aspectos del desarrollo y despliegue de la IA, desde la conceptualización hasta la implementación.
Garantizar la precisión y relevancia de los resultados de un sistema de IA es un proceso complejo que requiere un enfoque integral. Al seguir las mejores prácticas, las organizaciones pueden aumentar la confianza en sus sistemas de IA y aprovechar al máximo su potencial.
Saving Changes...
Abhishek GuptaConsultant| TeleperformanceDelhi, DL, India
To ensure AI-generated results are accurate, relevant, and aligned with your goals, start by clearly defining your objectives. Craft precise and detailed prompts to guide the AI in providing focused responses. Review the results carefully and refine your prompts as needed to improve accuracy. Always cross-check AI outputs against reliable sources to validate their correctness, especially for critical tasks. Be aware of AI's limitations, as it can produce errors or biased outputs, so human oversight is essential. Lastly, document your inputs and outputs to maintain consistency and track improvements over time. Saving Changes...
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