
Explore how social proof and social norms shape decision making, including how visible others' actions, in-group influence, and positive framing guide behavior, with examples like friends' voting status.
Explore how behavioral science informs AI-driven predictive analytics by linking interventions and stimuli to human behavior. See how behavioral economics and social psychology shed light on biases and decision making.
Learn how small changes in choice architecture act as nudges to influence decisions without restricting freedom, using social proof and commitment bias in smartphone apps that enable social sharing.
Demonstrates that teaching assistant robots can match human teachers in precision education, using AI, big data, learning alerts, and randomized controlled trials.
Explore how six behavioral disorders—self-control, limited attention and cognitive ability, loss aversion, default bias, social preference, and biased beliefs—shape human behavior and inform nudges to improve outcomes.
Explore how limited attention and cognitive ability shape choices, illustrated by Netflix's ai-driven recommendations and nudges. Discuss the paradox of choice and satisficing versus perfectionism in decision making.
Examine loss aversion and the endowment effect shaping risk choices and insurance decisions, showing how the pain of loss outweighs gains and cues influence pricing and promotions.
Explore default bias, the tendency to adopt default behavior, and its links to limited attention and loss aversion. Examine auto-renewals as a default example and messaging strategies to guide decisions.
Explore how social recognition and social preference drive self-image maintenance and conformity to group norms. Analyze Alan's example to see how social preference affects drinking before exams and educational norms.
Explore how biased beliefs shape human behavior, debunk brain 10% myths, and examine four cognitive biases: anchoring, authority bias, confirmation bias, and in-group bias, with ethical implications for AI-driven interventions.
Learn how behavioral economics and psychology guide ethical human interventions, while digital giants use nudges and experiments to ease choices and raise data consent considerations.
Define nudge and explain its theoretical basis in behavioral economics, then distinguish type one and type two nudges through system one and system two, with ethics guiding design.
Choose between type one and type two nudges by applying cognitive load theory; use type one under high cognitive load, and type two to promote lasting habits.
Explore how nudges vary by transparency, with transparent vs non-transparent nudges shaping behavior and ethics; examples include price stickers and colorized stairs, while evidence on effectiveness remains inconclusive.
explore a two-by-two matrix to classify transparent and non-transparent nudges, including type one and type two, and see how educational interventions use cognitive load and reflective versus automatic thinking.
Explore the ethical use of nudges in behavioral interventions, comparing type one and type two nudges, transparency, and effectiveness, with attention to autonomy, education targets, and decision metrics.
This course is conducted in English (with Chinese subtitles 英語發音,中文字幕).
This course introduces you to the science of human behavior, especially the behavioral biases and nudge theory that are essential for precision marketing in business. The course features English pronunciation and Chinese subtitles, and each unit includes a set of multiple-choice questions.
The goal of the course is to cultivate learners who have acquired data-driven decision-making, AI, predictive modeling, and data science skills to combine with behavioral science across disciplines. Through the planning of effective proactive intervention programs, such as "behavioral change technology" and "self-regulation methods," learners can fully demonstrate the behavior science of AI-driven precision decision-making in the digital transformation wave of AI applications (such as precision education and marketing).Unit 1: Introduction to Human Behavioral Science
Unit 1: Introduction to Human Behavioral Science
Unit 2: Obstacles to Human Behavior
Unit3: Nudge Theory
The course is designed for teachers to lead students in understanding and evaluating real-world cases.
Students will be able to design effective and ethical AI precision decision-making intervention plans.
The overall goal of the course:
Students will be able to explain how AI-driven behavior change through precise decision-making can add value to various industries.
Students will be able to design effective and ethical AI precision decision-making intervention plans based on behavioral science.