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

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

2025/4/7
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David Cox: 我将 AI 应用于行为科学领域，通过分析环境数据和行为数据来理解人类行为，并帮助人们做出更好的决策。这包括利用强化学习来预测个体行为，并通过调整奖励来引导其行为改变，最终目标是培养内在的奖励机制。在临床环境中，我们可以利用无监督机器学习识别患者群体，并利用监督学习优化临床干预策略，帮助医疗专业人员做出更优的决策，减少医疗错误。此外，我们还可以利用 AI 分析个体的语言和表达方式，从而理解其视角和认知框架，并提供不同的视角和干预策略。在教育领域，我们可以利用无监督机器学习识别学生的学习类型，并提供个性化的学习资源，以提高学生的学习效率和成功率。总而言之，AI 的应用远不止 LLM 热潮，它在各个领域都有着广泛的应用前景，尤其是在需要理解和干预人类行为的领域。 Demetrios: (This participant's core argument is implicitly present through the conversation but not explicitly stated as a single, coherent argument.) The conversation largely focuses on understanding the challenges and opportunities of applying AI to understand and influence human behavior. Demetrios acts as a facilitator, prompting David Cox to elaborate on his work and its implications. The discussion highlights the need for more data and better ways to collect and analyze it to build effective AI-driven solutions for improving health and education. The ethical implications of using AI to predict and influence behavior are also touched upon, underscoring the importance of responsible development and deployment.

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David Cox, with expertise spanning bioethics, behavioral analysis, and data science, discusses his work on using AI to understand and improve human behavior. He focuses on applying reinforcement learning principles to analyze behavioral patterns and design interventions that promote healthier choices. Data acquisition from wearables and other sources presents a challenge.
  • AI is applied to behavioral ecology in humans
  • Analysis of antecedent-behavior-consequence chains to predict behavior
  • Challenges in data acquisition for real-world behavior analysis

Shownotes Transcript

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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