Lawrence Rowland discusses the potential of ChatGPT and GPT in project management. He explains the differences between ChatGPT and GPT, highlighting the benefits of ChatGPT+ and the GPT Builder. Lawrence emphasises the importance of early adoption and experimentation with GPTs, as well as the need for entry-level tools to encourage wider adoption. He explores the role of GPTs in enhancing communication and information flow in project teams, and the potential for GPTs to disrupt and expedite various aspects of project management. Lawrence also discusses the upcoming ChatGPT Store and the possibilities of sharing and testing GPT use cases. He encourages project professionals to embrace the creativity and imagination enabled by GPTs and emphasises the importance of learning and exploring the capabilities of these models. The conversation explores the democratisation of projects and the changing role of project managers in the context of AI implementation. It discusses the flywheel effect of AI implementation and the potential impact on project success rates. The conversation also touches on ethics, education, alignment, and control issues related to AI. It highlights the importance of transparency and accuracy in AI projects and the need for ongoing discussions in society. The conversation concludes with a discussion on the future modes of AI interaction and their impact on the physical world.
Takeaways
- ChatGPT and GPT offer low-code or no-code environments for project professionals to experiment and apply AI in their work.
- Early adoption of GPTs can help address resource scarcity and skill set challenges in project management.
- GPTs have the potential to enhance communication and information flow in project teams, enabling faster decision-making and problem-solving.
- The upcoming ChatGPT Store will provide a platform for sharing and accessing public GPTs, fostering collaboration and innovation in project management.
- Project professionals should start with the hardest questions when using GPTs and be open to exploring the capabilities and limitations of these models. AI implementation is increasing the democratisation of projects, allowing a broader range of people to run projects at different scales.
- The role of project managers is changing as AI takes on more implementation tasks, requiring project managers to focus on decision-making and conflict resolution.
- The flywheel effect of AI implementation leads to more data on project success and failure, improving the overall success rate of projects done through AI.
- Ethical considerations and education are important factors to address in the context of AI implementation.
- Transparency and accuracy in AI projects are crucial, and different approaches to AI centralization and decentralisation may impact these factors.
- Ongoing discussions and societal awareness are necessary to navigate the impact of AI on businesses and society.
- Future modes of AI interaction, such as video integration and task-based models, will further impact project management and the physical w
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