The author emphasizes that human involvement is necessary at every stage of the innovation process, from ensuring the accuracy of data fed into AI systems, to making decisions based on AI findings, to adjusting governance models as situations change. While this may not yield the fastest results, the author argues that it leads to greater quality and more meaningful innovation.
Key takeaways:
- People drive more creative ideation than AI, as they can refine AI-generated suggestions and ideas, and know when an idea could be cultivated into something great.
- Humans are necessary to scrutinize AI suggestions, ensuring the data going into AI systems is accurate and combing through suggestions for potential bias.
- Human diligence is required for governance in innovation, as people can add nuance that AI systems can't offer and can adapt governance models based on changing situations.
- People bring empathy to innovation, understanding customer challenges and emotions, which AI systems can't comprehend.