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.
Artificial Intelligence
0 Hour
75 Minutes
Description
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.
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 Understanding
Familiarity with basic behavioral science concepts (motivation, cognition, or decision-making) and general awareness of data or AI terminology. No technical background required.
Course Content
No sessions available.
Simpliv LLC 39658 Mission Boulevard, Fremont, CA 94539, USA
Artificial Intelligence in Behavioral Science: Understanding Human Behavior Through Data and Design
Session 1: Introduction: The Convergence of AI and Behavioral Science
No lectures available
Session 2: How Machine Learning and Behavioral Models Inform One Another
No lectures available
Session 3: Emerging Interdisciplinary Research Trends
No lectures available
Session 4: Core AI Concepts for Behavioral Professionals
No lectures available
Session 5: Overview of Supervised and Unsupervised Learning
No lectures available
Session 6: Predictive Analytics, Natural Language Processing, and Affective Computing
No lectures available
Session 7: Understanding Data-Driven Bias and Interpretability
No lectures available
Session 8: Behavioral Data in the Age of AI
No lectures available
Session 9: New Forms of Behavioral Data (Digital Traces, Sentiment, Micro-Expressions)
No lectures available
Session 10: Ethical Use of Human Data and Privacy Considerations
No lectures available
Session 11: The S-T-E-A-R Mind Framework: Self-Coaching for the AI Era
No lectures available
Session 12: Situation–Thought–Emotion–Action–Result Model Explained
No lectures available
Session 13: How Cognitive Hygiene Reduces Bias in Behavioral Interpretation
No lectures available
Session 14: Applying S-T-E-A-R for Emotional Regulation and Ethical Decision-Making
No lectures available
Session 15: Applications in Practice
No lectures available
Session 16: AI in Behavioral Health and Therapy
No lectures available
Session 17: AI in Consumer Behavior and Nudging Design
No lectures available
Session 18: AI for Social Good: Public Policy, Education, and Workplace Engagement
No lectures available
Session 19: Ethics, Bias, and Human-Centered Design
No lectures available
Session 20: Responsible AI Frameworks for Behavioral Professionals
No lectures available
Session 21: Aligning AI Outcomes with Human Values and Fairness Principles
No lectures available
Session 22: The Future of AI-Augmented Behavioral Science
No lectures available
Session 23: Hybrid Intelligence: Humans + Machines in Understanding People
No lectures available
Session 24: Implications for Leadership, Policy, and Organizational Design
No lectures available
Session 25: Closing Reflection
No lectures available
Session 26: Using the S-T-E-A-R Model for Ongoing Ethical Reflection
No lectures available
Session 27: Key Takeaways and Questions for Continued Learning
