University of Michigan

Rethink How You Decide with AI

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University of Michigan

Rethink How You Decide with AI

Tina Lasisi

Instructor: Tina Lasisi

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Gain insight into a topic and learn the fundamentals.
Beginner level

Recommended experience

5 hours to complete
Flexible schedule
Learn at your own pace
Gain insight into a topic and learn the fundamentals.
Beginner level

Recommended experience

5 hours to complete
Flexible schedule
Learn at your own pace

What you'll learn

  • Develop decision-making strategies with AI that highlight both the visible and invisible choices.

  • Create prompts to allocate time, money, and energy more effectively across priorities.

  • Build a personal decision-making system using AI that adjusts to your life as it changes.

  • Use AI to explore ideas, challenge your reasoning, and recognize limitations.

Details to know

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Recently updated!

June 2026

Assessments

3 assignments

Taught in English

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This course is part of the Applied AI: Data Analysis, Workflows, and Decisions Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
  • Learn new concepts from industry experts
  • Gain a foundational understanding of a subject or tool
  • Develop job-relevant skills with hands-on projects
  • Earn a shareable career certificate

There are 3 modules in this course

In this module, you will uncover the full range of decisions you are already making in your life domains, including habitual and default choices you have never examined. You’ll learn to distinguish between a single choice and a coherent strategy, map their real constraints (time, money, energy, competing commitments), and use GenAI to surface blind spots. To conclude the module, you will draft a first version of a north star document.

What's included

1 video5 readings1 assignment1 discussion prompt

In this module, you will explore configuration reasoning: mapping multiple ways of arranging your choices under real constraints and comparing trade-offs between them. You will examine three payoff structures (gradient, threshold, plateau) as evaluation lenses and use GenAI to expand the configuration space and stress-test your preferred arrangement. This module emphasizes that configurations involve multiple resource types (time, money, energy, attention) and that the goal is experimentation, not theoretical optimization.

What's included

1 video2 readings1 assignment1 discussion prompt

In this module, you will pull together everything from Modules 1 and 2 to examine where your approach has broken down or could break down, and adjust your system accordingly. You will learn to diagnose breakdown patterns (overcommitment, decision fatigue, drift), design personal triggers and rhythms for strategic thinking, and revise your north star document using GenAI as a calibration partner. The module emphasizes that strategy is a practice, not a product.

What's included

1 video5 readings1 assignment1 discussion prompt

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Instructor

Tina Lasisi
University of Michigan
1 Course5,005 learners

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