Behavior As A Modality: A Framework To Enable Automated Persuasion
Exploring the Intersection of Communication Theory, Behavioral Science, and Artificial Intelligence
Abstract
Communication, as a system of messages, symbols, and cultural exchanges, is ubiquitous across all species. Scholars have argued that communication represents one of the most transformative evolutionary transitions in life's history, alongside pivotal developments like chromosomal mechanisms, eukaryotic formation, sexual reproduction, and multicellular life.
We currently stand at the cusp of a fourth phase in communication studies, precipitated not by political upheaval or mechanical innovation, but by the unprecedented accumulation of digital content and behavioral data. This data now serves as the foundation for developing large language and diffusion models, which hold transformative potential for behavioral scientific inquiry.
This thesis explores behavioral sciences' enduring mission—first articulated by Aristotle 2,500 years ago—of identifying and leveraging persuasive mechanisms. The field has traditionally bifurcated into two epistemological approaches: explanation and prediction. While behavioral scientists have historically sought explanations that provide interpretable causal mechanisms, the emergence of extensive digital behavioral repositories has shifted focus towards more robust predictive methodologies.
Key Themes
Seven Modalities of Communication
Communication is composed of seven interconnected modalities: communicator, message, channel, time of receipt, receiver, time of behavior, and receiver's behavior. This framework provides a comprehensive understanding of how information flows and influences behavior.
Two Cultures of Behavioral Sciences
The field has traditionally divided into explanation-focused approaches (seeking interpretable causal mechanisms) and prediction-focused approaches (leveraging large-scale data for accurate forecasting).
Digital Age Transformation
The digital age provides unprecedented access to behavioral data, enabling new approaches to understanding and optimizing human behavior through large-scale modeling and machine learning.
Behavior Optimization
The ultimate goal is controlling and optimizing behavior by strategically managing all aspects of the communication process - from selecting the right message and channel to targeting specific audiences.
Behavior Explanation
Understanding the causal mechanisms behind human behavior through interpretable frameworks and theoretical models that provide insights into why people act in certain ways.
Behavior Prediction
Leveraging large-scale data and machine learning approaches to accurately forecast human behavior patterns and outcomes across various contexts and platforms.
Large Individual and Societal Behavior Models
Developing comprehensive models that can understand behavior at both individual and societal scales, similar to how Large Language Models revolutionized natural language processing.
Future Directions
Infinite Personalization
Enabling personalized communication between any communicator and receiver, with AI producing performant content tailored to individual preferences and contexts.
Digital Humans & Societies
Creating sophisticated simulations of human populations that can serve as testing grounds for social interventions, policy proposals, and communication strategies.
AI Persuasion Measurement
Developing rigorous methods for studying, measuring, and monitoring the persuasive capabilities of AI models to ensure responsible deployment.
Automated Behavior Explanation
Bridging the gap between prediction and explanation by developing scalable methods that provide both high predictive power and interpretable mechanisms.
Rethinking Free Will
Investigating the degree to which human actions are governed by free will versus being determined by past experiences, environmental context, and external influences.
"We're actually much better at planning the flight path of an interplanetary rocket (rocket science) than we are at managing the economy, merging two corporations, or even predicting how many copies of a book will sell (behavior prediction). So why is it that rocket science seems hard, whereas problems having to do with people - which arguably are much harder - seem like they ought to be just a matter of common sense (easily predictable)?"
— Duncan J. Watts
"Nothing in Nature is random (unpredictable). A thing appears random only through the incompleteness of our knowledge (ignorance)."
— Baruch Spinoza