Artificial Intelligence in Behavioral Science: Understanding Human Behavior Through Data and Design

Explore how AI enhances behavioral science by analyzing human data, predicting actions, and designing better user experiences and decision-making strategies.
Duration: 1 Day
Hours: 75 Minutes
Training Level: All Levels
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Contact Support for Group Offers
Batch Two
Thursday, January 22, 2026
12:00 PM - 01:15 PM (Eastern Time)
Batch Three
Thursday, February 19, 2026
12:00 PM - 01:15 PM (Eastern Time)
Batch Four
Tuesday, March 24, 2026
12:00 PM - 01:15 PM (Eastern Time)
Live Session
Single Attendee
$149.00 $249.00
Live Session
Recorded
Single Attendee
$199.00 $332.00
6 month Access for Recorded
Live+Recorded
Single Attendee
$249.00 $416.00
6 month Access for Recorded

About the Course:

Artificial Intelligence (AI) is redefining how behavioral scientists understand, predict, and influence human behavior. This 75-minute session explores the intersection of data science, psychology, and machine learning, showing how AI tools can uncover hidden behavioral patterns, enhance experimental design, and improve decision-making at scale.

Participants will also learn to apply the S-T-E-A-R Mind Framework (Situation–Thought–Emotion–Action–Result) to self-coaching and critical thinking. This reflective practice helps professionals 'clean the mind' in the AI era, reducing bias, improving judgment, and maintaining ethical awareness amid automation.

The webinar examines real-world use cases, from mental health support to marketing, policy, and organizational behavior, and provides frameworks for responsible AI implementation that respect human agency.

Course Objectives:

  • The objective of this course is to equip participants with a comprehensive understanding of how Artificial Intelligence (AI) is transforming behavioral science and human decision-making. Through this 75-minute session, participants will learn to apply data-driven insights and the S-T-E-A-R Mind Framework (Situation–Thought–Emotion–Action–Result) to analyze, predict, and ethically influence human behavior. The course aims to enhance participants’ ability to integrate AI tools into behavioral research and practice, promoting ethical awareness, reducing bias, and fostering responsible innovation across domains such as mental health, marketing, policy, and organizational behavior.

Who is the Target Audience?

  • Behavioral scientists, psychologists, data analysts, organizational development professionals, learning designers, and leaders interested in the ethical and practical applications of AI to human behavior research and practice.

Basic Knowledge:

  • Familiarity with basic behavioral science concepts (motivation, cognition, or decision-making) and general awareness of data or AI terminology. No technical background required.

Curriculum
Total Duration: 75 Minutes
Introduction: The Convergence of AI and Behavioral Science
How Machine Learning and Behavioral Models Inform One Another
Emerging Interdisciplinary Research Trends
Core AI Concepts for Behavioral Professionals
Overview of Supervised and Unsupervised Learning
Predictive Analytics, Natural Language Processing, and Affective Computing
Understanding Data-Driven Bias and Interpretability
Behavioral Data in the Age of AI
New Forms of Behavioral Data (Digital Traces, Sentiment, Micro-Expressions)
Ethical Use of Human Data and Privacy Considerations
The S-T-E-A-R Mind Framework: Self-Coaching for the AI Era
Situation–Thought–Emotion–Action–Result Model Explained
How Cognitive Hygiene Reduces Bias in Behavioral Interpretation
Applying S-T-E-A-R for Emotional Regulation and Ethical Decision-Making
Applications in Practice
AI in Behavioral Health and Therapy
AI in Consumer Behavior and Nudging Design
AI for Social Good: Public Policy, Education, and Workplace Engagement
Ethics, Bias, and Human-Centered Design
Responsible AI Frameworks for Behavioral Professionals
Aligning AI Outcomes With Human Values and Fairness Principles
The Future of AI-Augmented Behavioral Science
Hybrid Intelligence: Humans + Machines in Understanding People
Implications for Leadership, Policy, and Organizational Design
Closing Reflection
Using the S-T-E-A-R Model for Ongoing Ethical Reflection
Key Takeaways and Questions for Continued Learning