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Why Great AI Starts With People, Not Data: Lessons From GenAI In Project Management

Dec 18, 2024 - forbes.com
The article emphasizes the importance of human expertise over large datasets in developing effective AI systems, particularly in the context of project management. While traditional AI development often relies on vast amounts of data, the author argues that the nuanced judgment and insights of experienced professionals are crucial for creating AI that delivers real-world value. Techniques like few-shot learning, which use a small number of high-quality examples from experts, can help AI models better understand complex decision-making processes and provide more context-sensitive guidance.

The author highlights that AI's true power lies in mimicking the thought processes of seasoned professionals, capturing their tacit knowledge and judgment. This human-centered approach to AI development offers several advantages, such as providing context-rich explanations, replicating sophisticated judgment calls, and achieving efficient training with less data. Ultimately, the article suggests that the real potential of AI is unlocked by learning from human expertise, which can lead to smarter, more intuitive AI systems that support complex problem-solving and decision-making.

Key takeaways:

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  • Human expertise is crucial for developing AI systems that deliver practical, real-world value, especially in fields like project management.
  • Few-shot learning, which uses a small number of high-quality examples from experts, can be more effective than training AI on vast datasets.
  • AI systems that incorporate insights from experienced professionals can better mimic the thought processes and judgment of those experts.
  • Starting AI development with human expertise rather than massive datasets can lead to more context-sensitive and efficient AI solutions.
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