Atomic Habits by James Clear provides a practical and scientifically-backed guide to forming good habits and breaking bad ones. The book introduces the Four Laws of Behavior Change: make it obvious, make it attractive, make it easy, and make it satisfying. It also emphasizes the importance of small, incremental changes (atomic habits) that compound over time to produce significant results. Clear discusses techniques such as habit stacking, optimizing the environment to support desired habits, and focusing on continuous improvement rather than goal fixation. The book is filled with actionable strategies, real-life examples, and stories from various fields, making it a valuable resource for anyone seeking to improve their habits and achieve personal growth[2][4][5].
In 'Nudge,' Thaler and Sunstein argue that by understanding how people think, we can design 'choice architectures' that nudge people toward better decisions for themselves, their families, and society. The book introduces the concept of 'libertarian paternalism,' where gentle nudges guide people toward beneficial choices without limiting their freedom. It explores various aspects of human decision-making, including the distinction between the 'Automatic System' and the 'Reflective System' of thinking, and provides numerous examples of how nudges can be applied in real-life scenarios to improve outcomes in health, finance, and other areas[1][3][5].
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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