Exploring Agent-Based Modeling for Complex Policy Challenges with Sherwin Brown

In this episode of The Flux, hosted by John Cordier, CEO of Epistemix, we hear from Timothy Clancy, a researcher from the University of Maryland's START program. Recorded at the Complex Social Systems Society of the Americas Conference in Santa Fe, New Mexico, Clancy shares insights from his career, which spans government work and applied studies on national security. They discuss the evolution of modeling in policy-making, the challenges of visualizing complex data, and the importance of building trust with policy-makers. Clancy emphasizes the need for simplicity in communication, the enduring nature of integrating soft skills with technical models, and the crucial role of understanding organizational dynamics to drive impactful decisions. The conversation also touches on specific models he has worked on, including those related to countering ISIS and studying violence and instability, illustrating the importance of robust, scenario-driven simulations in informing policy.00:00 Introduction to The Flux00:47 Meet Timothy Clancy01:03 Timothy's Background and Work01:45 Challenges in Policy Making with Data02:58 Visualization and Communication in Modeling05:29 Timothy's Career Shift and Focus07:00 Emerging State Actor Model12:40 Modeling Sentiment and Radicalization20:35 Counterfactuals and Policy Making23:08 Navigating Policy Making Institutions31:41 Conference Insights and Conclusion

In this episode of The Flux, host John Cordier, CEO at Epistemix, interviews Sherwin Brown from MITRE. Sherwin shares his journey into agent-based modeling, starting from his background in health management and policy. He discusses the role of data science and analytics in solving complex problems, such as monitoring the impact of the Affordable Care Act and tackling issues like homelessness and opioid overdoses. Sherwin emphasizes the importance of visual storytelling in agent-based modeling and its potential to support decision-making in policy contexts. The episode also highlights the importance of community and curiosity in the field of agent-based modeling.00:00 Introduction to The Flux Podcast00:45 Meet Sherwin Brown from MITRE00:59 Sherwin's Journey into Agent-Based Modeling01:59 Affordable Care Act and Data Science Competitions02:21 Exploring Natural Language Processing04:04 Agent-Based Modeling in Policy Making05:54 Complex Relationship Between Homelessness and Opioid Overdoses07:04 Complex Social Systems Society Conference08:05 Future of Agent-Based Modeling09:11 Advice for Students Interested in Agent-Based Modeling10:17 Closing Remarks

In this episode of 'The Flux,' we dive deep into data-driven decision making with Bill Rand from NC State University. Join us as Bill discusses his work in agent-based modeling, social media misinformation, and various innovative projects. Discover how agent-based modeling can provide insights into human behavior, business analytics, and even intergenerational trauma. Learn how different modeling approaches can help forecast outcomes, refine decision-making processes, and provide better policy and business strategies. Perfect for anyone interested in AI, data science, and the social sciences.00:00 Introduction to the Flux Podcast00:20 Meet Bill Rand: Data-Driven Decision Making02:42 Applications of Agent-Based Modeling31:21 What the Flux Moment32:02 Reflections and Methodological Insights

In this episode of The Flux, join Dave Freed, Senior Director at Ansys, as he delves into the transformative world of computer simulations. With a rich history from Exa Corporation to OnScale and Ansys, Dave explores the evolution and future of simulations, highlighting their pivotal role in automotive, aerospace, and nuclear engineering. Discover how simulations have advanced to replace costly physical testing, improve accuracy, and prevent errors. Learn about intriguing real-world applications, the integration of AI in automating complex tasks, and the surge of simulation in life sciences. Dave also shares personal experiences and acknowledges mentors who've shaped his illustrious career.00:00 Introduction to The Flux Podcast00:19 Meet Dave Freed: CTO and Simulation Expert00:41 Dave's Career Journey in Simulation11:59 The Value of Simulation22:18 Simulation Accessibility and User Experience31:49 Future of Simulation and AI Integration

In this episode of The Flux, host John Cordier interviews Matt Madden, Director of the BYU Marketing Lab, about his work in making complex statistics and marketing analytics accessible. Madden discusses the lab's unique approach, which allows students to apply their skills in real-world consulting projects. They delve into key topics like market research techniques such as conjoint analysis, which helps students and clients understand consumer behavior more accurately than traditional surveys.Madden shares his journey from math education to statistics and ultimately to marketing, providing insights into how data can guide consumer insights while acknowledging its limitations. He highlights the challenges of relying solely on past data, emphasizing the need for creativity and risk-taking in decision-making. They also discuss integrating newer technologies, like AI and machine learning, into marketing analytics, exploring both the opportunities and concerns associated with increased data availability. Madden further addresses the importance of qualitative data, its challenges, and the evolving nature of market research.The episode closes with advice for students entering the marketing field, focusing on the importance of resilience, saying "no" to prevent burnout and the necessity of balancing data-driven decisions with human creativity and empathy.This episode is a must-listen for marketers, data enthusiasts, and business professionals seeking to harness data analytics while maintaining a consumer-focused, ethical approach.00:00 Introduction to The Flux00:45 Meet Matt Madden: BYU Marketing Lab Director01:03 The BYU Marketing Lab: Real Consulting Experience02:08 Conjoint Analysis: A Market Research Technique05:59 From Math Education to Marketing Analytics07:32 Predictive Modeling in Healthcare11:14 The Future of Marketing Analytics13:39 Challenges in Data Privacy and Forecasting20:02 Entrepreneurship and Qualitative Data at Scale24:18 Industry's Overexposure to Surveys24:44 Consumer Feedback Fatigue25:32 A Rare Example of Effective Feedback27:04 The Importance of Data in Business Decisions27:58 Challenges for Small Businesses in Using Data30:30 Disaster Recovery in Data Analytics32:59 The Future of Modeling and Machine Learning35:33 Advancements in User Interface and Visualization37:28 The Evolution of Programming Languages41:19 Advice for Graduating Students

In this episode of The Flux, host John Cordier sits down with Don Burke, co-founder of Epistemix and a trailblazing epidemiologist, to explore the fascinating intersection of infectious disease research, artificial intelligence, and agent-based modeling (ABM). Burke shares his journey from a traditional career in infectious disease research to becoming a passionate advocate for modeling and simulation, offering a behind-the-scenes look at his groundbreaking work with HIV, vaccines, and global disease prevention.Burke recounts his early days in the military, developing vaccines for tropical diseases and his epiphany when he first encountered genetic algorithms and artificial intelligence. This moment sparked a shift in his approach to public health, leading him to apply simulation methods to complex biological and social systems, ultimately culminating in his co-founding of Epistemix. He discusses his pivotal role in creating agent-based models for predicting disease outbreaks like smallpox, avian flu, and most recently, COVID-19, illustrating the power of simulation in making better decisions in public health.Beyond infectious disease, Burke reflects on the future of modeling, emphasizing its potential to not only tackle epidemics but also simulate human behavior, social contagions, and decision-making processes—showing how these tools are critical for addressing broader societal challenges. Throughout, Burke conveys his belief that interdisciplinary collaboration and data-driven insights are essential for solving today’s most pressing global issues.This episode offers an in-depth, accessible exploration of how AI, computational social science, and agent-based modeling are shaping the future of public health and decision-making across industries.Timestamps:00:00 Introduction to the Flux Podcast00:19 Meet Don Berg: From Infectious Disease Physician to Modeler00:30 Early Career and Vaccine Development01:47 HIV Research and Genetic Algorithms04:29 The Epiphany: Modeling Viral Evolution06:52 Transition to Johns Hopkins and Building Modeling Skills08:16 9/11 and the Rise of Biodefense Modeling12:42 The MIDAS Program and Agent-Based Modeling20:23 Expanding Agent-Based Modeling Beyond Infectious Diseases26:43 The Campfire Concept: Collaborative Modeling30:12 Lessons from DA Henderson and Smallpox Eradication32:49 Reflections on a Career in Modeling and Simulation34:49 The Future of Modeling and Simulation39:11 Current Projects and Historical Insights

In this episode of The Flux, John Cordier interviews Rob Axtell fromGeorge Mason University, where he leads the largest graduate programin agent-based modeling (ABM) globally. Axtell shares his journey intocomplex systems modeling and how the field has evolved since the1990s. He explains how George Mason’s Ph.D. program inComputational Social Science is shaping the next generation of expertswho go on to roles in government, research, and the private sector.They discuss the power of agent-based models to simulate real-worlddynamics, from consumer behavior to macroeconomics, highlighting theincreasing availability of data and computing power that allows ABM tocompete with traditional models used by institutions like central banks.Axtell emphasizes the need for more empirical grounding in ABM andthe potential to build large-scale, highly detailed models, including theexciting possibility of simulating entire economies.Axtell also touches on the importance of modeling social complexity atthe individual level, the challenges of past limitations in data, and theunique potential of ABM to provide a more accurate picture of systemslike financial markets.For those new to the field, Axtell offers practical advice on gettingstarted, emphasizing the value of tools like NetLogo as a gateway toABM. Whether you're a student, researcher, or data enthusiast, thisepisode provides a deep dive into the cutting-edge applications of ABMand its future impact.00:00 Welcome to The Flux Podcast00:18 Meet Rob Axtell: Expert in Agent-Based Simulation01:07 Overview of George Mason's Computational Social Science Program01:45 Career Paths for Graduates03:34 Rob Axtell Journey into Agent-Based Modeling05:58 The Evolution and Impact of Agent-Based Models08:37 Applications and Future of Agent-Based Modeling11:35 Challenges and Opportunities in Agent-Based Modeling14:06 The Importance of High-Fidelity Models16:31 Policy Implications and Real-World Applications29:41 Technical Advances and Future Directions36:44 Advice for Aspiring Agent-Based Modelers39:09 Conclusion and Final Thoughts

In The Intersection of Science Fiction and Reality episode of The Flux podcast, host John Cordier engages in a conversation with Sam Arbesman, Scientist-in-Residence at Lux Capital and Research Fellow at the Long Now Foundation. They explore how science fiction, video games, and computational social science intersect to influence real-world innovations.Harbisman shares how early experiences like playing SimCity and reading Isaac Asimov's Foundation Trilogy sparked his interest in complexity science and computational modeling. They discuss the concept of psychohistory from Foundation, and how it inspired modern computational social science to analyze societal behaviors on a large scale.They also touch on how venture capital plays a role in transforming science fiction ideas into reality, with Lux Capital supporting innovations that blur the lines between science fact and fiction. Arbesman reflects on the increasing complexity of technological systems, emphasizing how understanding these systems requires new tools and thinking, akin to studying biological systems.Ultimately, this episode highlights the value of scenario planning, counterfactuals, and complexity science in decision-making and innovation, making a compelling case for the importance of these methodologies in navigating an uncertain future.Timestamps:00:00 Introduction00:16 Meet Sam Arbesman01:00 Sam's Journey into Complex Systems01:34 The Influence of SimCity and Science Fiction03:03 The Foundation Trilogy and Psychohistory07:01 Science Fiction's Real-World Impact13:08 The Role of Venture Capital in Innovation14:19 The Future of Deep Tech and Emerging Technologies19:12 The Importance of Counterfactuals and Scenario Planning30:20 Encouraging Complexity Science Education35:44 The Future of Simulation and Computational Science

In this episode of The Flux, John Cordier interviews Matt Kohler, Applied Complexity Scientist at MITRE and President of the Computational Social Science Society of the Americas, about the transformative power of agent-based modeling (ABM). Kohler explains how ABM simulates complex human systems and helps decision-makers understand the ripple effects of their choices. From anthropology to economics, Kohler shares examples of how ABM is helping scientists and leaders explore new insights.As technological advancements in data, hardware, and software drive ABM to new heights, Kohler discusses its expanding role in solving real-world challenges, from traffic modeling to financial crises. With its potential to revolutionize industries by providing a clearer view of how complex systems evolve, ABM is poised to become an indispensable tool for policy-makers, researchers, and organizations.This episode is for anyone interested in the intersection of complexity science and decision-making, and how ABM is shaping the future of predictive modeling.Timestamps:01:00 Matt Kohler's Flux Moment03:17 Agent-Based Modeling Insights05:13 Applications and Future of Agent-Based Modeling08:56 Challenges and Successes in Agent-Based Modeling23:41 Economic Theories and Agent-Based Modeling26:58 Getting Started with Agent-Based Modeling29:10 Future of Computational Social Science

In the inaugural episode of The Flux, John Cordier, CEO of Epistemix, interviews Josh Epstein, Director of the Agent-Based Modeling Lab at NYU and a prominent figure at the Santa Fe Institute. The discussion revolves around the potential and progress of agent-based modeling (ABM), particularly in public health, economics, and beyond.Epstein shares insights into how ABM creates simulations of artificial societies to generate real-world patterns like epidemics or wealth distributions. He highlights the generative explanatory standard, which uses individual agent behaviors to explain macroscopic phenomena, contrasting it with traditional models that assume rational actors. Epstein introduces Agent Zero, a framework offering an alternative to the rational actor model by incorporating emotional, cognitive, and social elements into agent behavior. His work emphasizes the need for cognitively plausible agents in simulations, moving beyond simplified assumptions in fields like epidemiology and economics.This episode underscores the transformative potential of ABM in areas such as public policy, disease modeling, and economic forecasting, stressing the importance of integrating human behavior into models to improve decision-making. Epstein envisions ABM becoming a core tool in tackling complex, real-world problems, with the field poised for continued growth as computational power advances.Timestamps00:00 Introduction to The Flux Podcast00:23 Meet Josh Epstein: Pioneer in Agent-Based Modeling02:32 Exploring Agent-Based Models04:59 Generative Social Science and Agent Zero07:31 Inverse Generative Social Science15:58 Behavioral Dynamics in Epidemiology19:00 Leadership and Decision Making in Modeling19:33 Future of Agent-Based Modeling20:35 Global Adoption of Agent-Based Models22:34 Visualization and Pandemic Modeling33:46 Why Model?37:34 Optimism for the Future