The climate change narrative has always seemed to me to be contrived. The idea that life changing pronouncements could be made, about a topic as complex as Earth’s climate, because a small group of people agreed that “the science” was settled.This narrative triggered countries to spend trillions, to pass intrusive laws and regulations, and to stifle any alternative scientific evidence.
Michael Crichton’s lecture “Aliens Cause Global Warming” given on January 17, 2003 at Caltech is very enlightening. Download Crichton’s lecture here
Michael Crichton, MD, argues that climate change discussions rely too heavily on consensus, models, and fear-based messaging, while downplaying uncertainty, historical variability, and the essential role of scientific dissent.
Crichton brilliantly points out the absurdity of the Climate Change central tools―climate computer models.
Stepping back, I have to say the arrogance of the model-makers is breathtaking. There have been, in every century, scientists who say they know it all. Since climate may be a chaotic system—no one is sure—these predictions are inherently doubtful, to be polite. But more to the point, even if the models get the science spot-on, they can never get the sociology. To predict anything about the world a hundred years from now is simply absurd. Look: If I was selling stock in a company that I told you would be profitable in 2100, would you buy it? Or would you think the idea was so crazy that it must be a scam?
Let’s think back to people in 1900 in, say, New York. If they worried about people in 2000, what would they worry about? Probably: Where would people get enough horses? And what would they do about all the horseshit? Horse pollution was bad in 1900, think how much worse it would be a century later, with so many more people riding horses?
But of course, within a few years, nobody rode horses except for sport. And in 2000, France was getting 80% its power from an energy source that was unknown in 1900. Germany, Switzerland, Belgium and Japan were getting more than 30% from this source, unknown in 1900. Remember, people in 1900 didn’t know what an atom was. They didn’t know its structure. They also didn’t know what a radio was, or an airport, or a movie, or a television, or a computer, or a cell phone, or a jet, an antibiotic, a rocket, a satellite, an MRI, ICU, IUD, IBM, IRA, ERA, EEG, EPA, IRS, DOD, PCP, HTML, internet, interferon, instant replay, remote sensing, remote control, speed dialing, gene therapy, gene splicing, genes, spot welding, heat-seeking, bipolar, prozac, leotards, lap dancing, email, tape recorder, CDs, airbags, plastic explosive, plastic, robots, cars, liposuction, transduction, superconduction, dish antennas, step aerobics, smoothies, twelve-step, ultrasound, nylon, rayon, teflon, fiber optics, carpal tunnel, laser surgery, laparoscopy, corneal transplant, kidney transplant, AIDS. None of this would have meant anything to a person in the year 1900. They wouldn’t know what you are talking about.
Now. You tell me you can predict the world of 2100. Tell me it’s even worth thinking about. Our models just carry the present into the future. They’re bound to be wrong. Everybody who gives a moment’s thought knows it.
Among Crichton’s many observations these are the ones which resonated with my perception of the climate change claims and my experience as an engineer.
1. Climate Science and “Consensus”
Crichton argues that invoking consensus is a political tactic, not a scientific one. In the climate context, he maintains that claims such as “the science is settled” are used to shut down debate rather than advance understanding. He stresses that science progresses through testing, skepticism, and falsification, not majority agreement.
His key claim is that when policymakers or advocates emphasize consensus, it signals uncertainty rather than strength, because solid science does not require rhetorical reinforcement.
2. Climate Models and Uncertainty
Crichton focuses heavily on climate models, arguing that they are often misunderstood or oversold:
• Climate models are not predictive in the way weather forecasts are, but instead depend on assumptions, parameter tuning, and incomplete data.
• He emphasizes that many climatic variables (cloud behaviour, ocean circulation, feedback loops) were poorly constrained at the time.
• According to Crichton, models can produce authoritative-looking outputs that mask large uncertainties, which are then presented to the public as firm conclusions.
He warns against confusing model scenarios with empirical evidence.
3. Historical Climate Variability
Crichton points out that Earth’s climate has always changed, often dramatically, long before industrialization. He references:
• Medieval Warm Period
• Little Ice Age
• Earlier warming and cooling cycles
His argument is not that human influence is impossible, but that natural variability complicates attribution, and that public discussions often minimize this complexity.
4. Media, Politics, and Fear Amplification
A major theme is that climate change discourse is driven by institutions—media, governments, NGOs—that benefit from fear narratives:
• Apocalyptic framing attracts funding, attention, and political leverage.
• Worst-case scenarios receive disproportionate coverage.
• Dissenting scientists are often labeled as unethical or corrupt rather than debated on evidence.
Crichton draws parallels to earlier scientific scares (e.g., nuclear winter) that were later walked back quietly.
5. Science vs. Policy
Crichton makes a sharp distinction between science and policy advocacy:
• Science asks what is happening and why.
• Policy asks what should we do.
He argues that climate discussions often collapse this boundary, presenting policy preferences (carbon limits, energy choices) as if they were scientific conclusions.
6. Core Climate Message of the Lecture
Crichton’s central climate-related warning is:
When science becomes intertwined with political goals, it risks losing its corrective mechanisms—skepticism, openness, and error correction.
He does not claim climate change is a hoax, but rather that:
• The certainty communicated to the public exceeds the certainty justified by the data (as of 2003).
• Suppressing dissent harms science itself.
• Good intentions do not protect science from institutional bias.
