AI Today Podcast: Lessons Learned from AI Project Management: Interview with Jonelle Martinez
Oct 14, 2023
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Jonelle Martinez, an expert in AI project management, shares insights on the challenges and consequences of AI projects, including the importance of skills, clean data, and resources. They discuss the future of AI and its application to organizations, highlighting potential benefits and expressing concerns about ethics and data privacy. They also talk about promoting feedback, project management resources, and more AI content on the podcast.
AI has positive implications in education and government sectors, but cultural issues and process changes need to be addressed for successful adoption.
Managing AI projects requires addressing challenges related to data quality and quantity and having the right resources and skills, while following structured approaches like the Cognitive Project Management for AI (CPMI) methodology.
Deep dives
The Future of AI and its Application to Organizations
The interviewee discusses her perspective on the future of AI and its application to organizations. She believes that AI has positive implications, especially in education and government sectors. However, she highlights the importance of addressing cultural issues and process changes surrounding the adoption of AI. Additionally, she emphasizes the need for ethical handling and interpretation of AI systems, raising concerns about data and privacy. Overall, she sees AI as a tool that can benefit society if proper controls and ethics are implemented.
Challenges in Managing AI Projects and the Role of CPMI Methodology
The interviewee shares insights into managing AI projects and highlights challenges faced in doing so. These include issues related to data quality and quantity, as well as the necessity of having the right resources and skills, such as data scientists and data engineers. She also discusses the importance of following a structured approach like the Cognitive Project Management for AI (CPMI) methodology, which integrates CRISPM with modern agile techniques. The interviewer acknowledges these challenges and emphasizes the significance of learning from failures and adopting a growth mentality.
The Role of Data Literacy and Trustworthiness of AI Systems
The interviewee reflects on the significance of data literacy in the modern world, drawing a parallel to the historical importance of learning how to read with the advent of the printing press. She underscores the notion that everyone needs to be data literate to succeed in this data-driven age. The interviewee also addresses the issue of trustworthiness in AI systems, expressing the need to understand how such systems work to alleviate fear and identify potential bias or problems. She stresses the importance of clean data, ethics, and privacy in shaping the future of AI.
Companies of all sizes in just about every single industry are looking to see how Artificial Intelligence (AI), machine learning (ML), and cognitive technology projects can be used. They want to see how AI can provide a competitive edge, provide efficiencies, and improve ROI in today’s competitive landscape. As a result, this creates tremendous opportunity for people looking to manage these types of projects.