Welcome to Decision Analysis for Wicked Climate Problems!

Lecture 01

September 15, 2025

Why analyze decisions?

How did you make these decisions?

  • Where to go to college?

  • Whether/where to go to graduate school?

  • What car to buy?

  • What house/apartment to buy/rent?

Wicked planning problems

The search for scientific bases for confronting problems of social policy is bound to fail, becuase of the nature of these problems. They are “wicked” problems…

[there are no] “optimal solutions” to social problems unless severe qualifications are imposed first…

— Rittel, H.W.J., Webber, M.M. Dilemmas in a general theory of planning. Policy Sci 4, 155–169 (1973).

The stakes are high for wicked problems

“Every solution to a wicked problem is a ‘one-shot operation’; because there is no opportunity to learn by trial-and-error, every attempt counts significantly” — ibid

Inaction is a decision

What examples can you think of where inaction has negative consequences?

  • Burst pipe
  • Small fire in house
  • Downed electrity line
  • Novel viruses
  • Climate change

Why analyze actions to manage climate risks?

Humans are changing the climate

Figure 2: : Figure SPM.2 in IPCC, 2021: Summary for Policymakers.

This intersects with many dimensions of global change

Many already plan and make decisions to manage their risks

  • International agreements to reduce emissions
  • National investments in decarbonization
  • Large-scale public infrastructure projects
  • Household decisions to relocate or harden
  • And don’t forget: inaction is a decision

Are actors making good decisions? Can they do better?

In this course, you will learn how to:

  1. Frame climate decision problems in a helpful way.
  2. Apply multi-objective robust decision-making frameworks to real-world problems using open source software tools.
  3. Evaluate trade-offs between competing objectives using appropriate quantitative techniques.
  4. Identify actionable insights for addressing problems characterized by deep uncertainties.
  5. Communicate complex technical analyses clearly and effectively.
  6. Develop professional-quality deliverables.

Note

We are studying an approach to how decisions could be made. We are not studying how decisions are made. Closing the gap between these two areas of focus might help make decision analysis more useful. That’s the topic of an upcoming Thayer course!

A few recent examples from our group

Source: Sharon Karr/FEMA

Zarekarizi et al. (2020): How high to elevate a home?

Getting to know each other

Meet your instructor

Figure 4: Dr. Adam Pollack (right), your instructor!
  • I research:
    • Flood-risk management
    • Problems where people don’t agree on success
    • Ways to make decision analysis more useful
  • From Port Washington, NY (via Boston, MA and Centerport, NY)
  • I used to own a popcorn business

Meet each other

  • What is your name?
  • What is your year of study?
  • What decision problem interests you the most?
  • What are you looking to get out of this course?
  • What is one fun fact about you?

Course overview and logistics

Our course is fully online!

Expectations from students

  • come prepared to class (e.g., by carefully reading and synthesizing the reading assignments before class and being ready to present their synthesis in class);
  • actively contribute to the group discussions and activities;
  • submit the assignments on time; and
  • schedule office hours as needed.

Students should expect to spend roughly three times the in-course hours outside the classroom for readings and assignments.

Note

For the training, I also expect you to provide structured feedback at the end of each module on how we can refine the course to make it better for students in the future. In exchange, you will get co-development credit on the final published version of this Fall 25 open-source course.

Assignments and grading

  • Active Participation (10%)
  • Computational Labs (30%)
  • Course Project
    • Progress Reports (20%)
    • Presentation (20%)
    • Report (20%)

There are seven modules in this course

  • “Overview”: Overview of decision analysis for wicked climate problems
  • “Uncertainty”: Uncertainty and Monte Carlo analysis
  • “RDM”: Robust decision-making
  • “Trade-offs”: Multiple objectives and navigating trade-offs
  • “DMDU”: Decision making under deep uncertainty
  • “Gaps”: Gaps between decision analysis and decision support
  • “Projects”: Student project presentations

Class structure

Emulating the 2 Spot (MWF 2:00-2:55pm, No Tu X-hr)

Note

Let’s discuss how we do the labs for this training

Mondays

  • Lecture
  • Take notes and ask questions
  • Slides posted by Sunday night (often earlier)

Wednesdays

  • Serious (but fun!) game or student-led journal club
  • Be prepared to synthesize lessons into your lab report and project update
  • Sometimes we will start longer labs on Wednesday

Fridays

  • Lab
  • Make substantial progress together
  • Lab report due before next lab

Communication

  • Questions during class is best
  • Slack is great - not as good as in class, but still promotes open discussion
  • Office hours are great (including when the issue is urgent and/or private)
  • Email is ok if issue is urgent and/or private and you can’t make office hours

Overall guidelines

  • Collaboration is highly encouraged and a skill we will practice in course, but all work must reflect your own understanding.
    • See GenAI policy on syllabus
    • Always cite external references
  • A rubric will be available for all graded assignments and you can easily find it from the schedule webpage.
  • Assume good faith of others and engage in good faith yourself.

Warning

Decision analysis is values-laden and good decision analysis is explicit about normative assumptions. Please do not outsource the opportunity to learn this vital skill.

Upcoming Schedule

This week

Class

  • Tuesday (No Meeting): computing setup (do on your own if you want to work through labs)
  • Wednesday: lecture on framing a decision analysis
  • Friday (No Meeting): getting comfortable with our computing setup

Assignments

  • Catch up on Readings
  • Project progress report 1
    • What decision problem will you focus on this term?
    • See here for more guidance
    • Due next Friday

Next week

  • Starting Uncertainty module
  • More practice with our computing setup
  • First serious game of the term
  • First lab and lab report of the term