Welcome back to The Effective Problemsolver and our special 5-part series on the fentanyl crisis. Today we’re on Step 3: uncovering the feedback loops that make complex problems like this so hard to solve.
Thanks for all the great feedback on this series over the past few weeks. I’ve loved hearing what resonated, what you’d like more of, and even where I could improve. If you ever have ideas, questions, or requests, just hit reply—I always appreciate it.
While this series uses the fentanyl crisis as a case study, the process we’re exploring can be applied to any complex issue—homelessness, climate change, youth mental health, you name it.
So even if fentanyl isn’t your focus, I think you’ll still find something valuable here.
Stick with us—it’s going to be worth it.
AI is already transforming the private sector. We’re testing how it might do the same for solving social problems—faster, deeper, smarter.
Where We’ve Been So Far
- Part 1: First-order causes – the direct drivers of the problem
- Part 2: Second-order causes – the underlying forces influencing those drivers
But a list of causes, even layered ones, doesn’t capture how real-world problems behave.
That’s because complex problems are systems, and systems are shaped by feedback loops—where causes influence each other in repeating patterns, sometimes worsening the problem, sometimes stabilizing it.
Why This Step Matters
Here’s today’s big idea:
The relationships between causes often matter more than the causes themselves.
That’s the power of feedback loops. They help us understand not just what’s happening, but why it keeps happening—or even accelerates.
Let’s look at how they work.
Understanding Feedback Loops (with Real-Life Examples)
There are two main types of feedback loops in systems thinking:
Reinforcing Loops (They escalate the problem)
These loops amplify a situation over time. Once started, they tend to grow stronger—like vicious cycles.
Everyday example:
Think about credit card debt.
Interest builds on your balance → You can’t pay it off → The balance grows → Interest grows faster → and so on.
Fentanyl example:
Loop: Fentanyl Potency & Addiction Acceleration
Stronger fentanyl → Users build tolerance → Require higher doses → Dealers respond with stronger supply → Potency increases again.
This is one reason the drug keeps getting deadlier. Each loop reinforces the next.
Balancing Loops (They counter or slow the problem)
These loops stabilize a situation. They push back against change and can help restore balance.
Everyday example:
Your body temperature. When it rises, you sweat to cool down. When it drops, you shiver to warm up. Your system self-corrects.
Fentanyl example:
Loop: Naloxone & Overdose Prevention
More naloxone is available → More overdoses reversed → More people survive → More chances to seek treatment → Fewer deaths.
Unfortunately, in the current system, this loop isn’t strong enough to counteract the reinforcing loops. But identifying it points us toward leverage.
Step-by-Step: How to Use ChatGPT to Uncover Feedback Loops
Now let’s get practical. Here’s how you can use ChatGPT to do this kind of analysis on any issue.
Step 1: List Your First- and Second-Order Causes
Start with the causes you’ve already identified. If you haven’t done this yet, go back to Parts 1 and 2 of the series.
Step 2: Prompt ChatGPT to Explore Feedback Loops
Use a prompt like:
“Looking at this list of first- and second-order causes of [insert issue], what reinforcing or balancing feedback loops might exist between them? Identify at least one reinforcing loop that makes the problem worse, and one balancing loop that stabilizes or reduces the problem. Describe the causal relationships clearly.”
You can also try:
“Are there any vicious cycles or self-reinforcing dynamics in these causes?”
“Which relationships among these causes might create stability or resistance to change?”
These prompts encourage ChatGPT to simulate systems thinking. You can refine them by adding detail from your own work or local context.
Bonus: Use ChatGPT to Get Critical
Once you’ve identified a loop, test its logic. Push back.
“What are alternative explanations for this pattern?”
This helps you surface assumptions, strengthen your thinking, and avoid being misled by plausible-but-incomplete answers.
Coming Up Next
In Part 4, we’ll explore leverage points—places in the system where small, strategic interventions could unlock big change.
See you in two weeks.
