From Shiny to Strategic: The Maturation of AI Across Industries // David Cox // #303

Key takeaways

AI has transitioned from a novelty to a strategic asset in various industries, focusing on ROI and market differentiation.
Understanding behavior from an ecological perspective can significantly enhance how AI applications impact human decision-making.
AI and machine learning offer powerful tools in clinical settings, promoting tailored interventions and improved patient outcomes.
Challenges in data privacy and effective data utilization must be addressed to maximize the benefits of AI in personal and clinical contexts.

Summary

Maturation of AI in Industries

In the podcast, David Cox discusses how the initial excitement surrounding AI, particularly after the release of ChatGPT, has evolved into more strategic considerations for businesses. Originally focused on implementing shiny new technologies, companies are now prioritizing return on investment (ROI) and market differentiation. This shift reflects a more mature understanding of AI’s role in achieving business goals beyond merely following trends.

Behavioral Science Meets AI

David elaborates on his background in behavioral science and how it intertwines with AI developments. He emphasizes the significance of understanding human behavior through an ecological lens, utilizing data from various sources such as wearables and environmental stimuli to aid individuals in making better decisions. This involves analyzing antecedents and consequences of behavior to implement effective interventions, particularly in health.

Innovations in Clinical Settings

The conversation shifts to the application of AI and machine learning in clinical practice. David explains how unsupervised learning can help identify patient cohorts while supervised learning can optimize clinical decision-making. He highlights the potential of AI to analyze behavioral patterns and enhance interventions tailored to individual needs. This demonstrates AI's transformative potential in behavioral health.

Challenges and Future Directions

David identifies significant challenges in collecting and harnessing data effectively for behavioral interventions, particularly in the context of privacy and personal data management. He envisions a future where individuals have access to their own data and how it could be utilized for personal improvement. Furthermore, he discusses the implications of using AI to predict and manage behavior effectively, emphasizing the importance of ethical considerations.

Show notes

From Shiny to Strategic: The Maturation of AI Across Industries // MLOps Podcast #303 with David Cox, VP of Data Science; Assistant Director of Research at RethinkFirst; Institute of Applied Behavioral Science.

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// Abstract

Shiny new objects are made available to artificial intelligence(AI) practitioners daily. For many who are not AI practitioners, the release of ChatGPT in 2022 was their first contact with modern AI technology. This led to a flurry of funding and excitement around how AI might improve their bottom line. Two years on, the novelty of AI has worn off for many companies but remains a strategic initiative. This strategic nuance has led to two patterns that suggest a maturation of the AI conversation across industries. First, conversations seem to be pivoting from "Are we doing [the shiny new thing]" to serious analysis of the ROI from things built. This reframe places less emphasis on simply adopting new technologies for the sake of doing so and more emphasis on the optimal stack to maximize return relative to cost. Second, conversations are shifting to emphasize market differentiation. That is, anyone can build products that wrap around LLMs. In competitive markets, creating products and functionality that all your competitors can also build is a poor business strategy (unless having a particular thing is industry standard). Creating a competitive advantage requires companies to think strategically about their unique data assets and what they can build that their competitors cannot.

// Bio

Dr. David Cox can formally lay claim to being a bioethicist (master's degree), a board-certified behavior analyst at the doctoral level, a behavioral economist (post-doc training), and a full-stack data scientist (post-doc training). He has worked in behavioral health for nearly 20 years as a clinician, academic researcher, scholar, technologist, and all-around behavior science junky. He currently works as the Assistant Director of Research for the Institute of Applied Behavioral Science at Endicott College and the VP of Data Science at RethinkFirst. David also likes to write, having published 60+ peer-reviewed articles, book chapters, and a few books. When he's not doing research or building tools at the intersection of artificial intelligence and behavioral health, he enjoys spending time with his wife and two beagles in and around Jacksonville, FL.

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Timestamps:

[00:00] David's preferred coffee

[00:08] Takeaways

[02:11] AI Beyond LLMs

[06:05] Notifications and Screen Time

[08:35] Exercise and Brain Chemistry

[10:30] Data Privacy and Improvement

[12:14] God Mode Habit Tracker

[13:58] Breaking Habits for Reading

[20:15] Evaluating Lasting Change

[24:23] Phone Free Bedtime Ritual

[29:00] Identity and Habit Formation

[32:05] Voice Memo AI Future

[33:32] Unsupervised Learning in Education

[37:08] Data-Driven Classroom Insights

[40:33] Wrap up