The “Flying Car Fallacy” and Why It’s Wrong


Where is my flying car? Popular science cover.

Where is my flying car? Popular science cover.

One of my least favorite responses to hear when talking with someone about the future is what I call the “flying car fallacy”. While the precise phrasing differs from person to person, the most general form looks something like: ‘They promised us flying cars’ or ‘Where are our flying cars?’. The implication, of course, is that any form of techno-optimism or forecasting should be regarded with extreme skepticism due to the failure of flying car predictions to come true.


Honestly? The concept that you should regard what people tell you about the future with skepticism isn’t a bad one. However, while it’s not a precise corollary, I think Scott Alexander’s Innoculation Effect comes into play here. Because there’s this very basic, obviously failed prediction about the future, people applying the fallacy are able to dismiss all other predictions as wishful thinking or, if proven correct, lucky guesses. And as someone who likes to think that he can make useful predictions about technologies, that’s hardly ideal.


While the correct usage parameters for technological forecasting and trend tracking aren’t 100% established (and I hope to get a better handle on those exact things in this blog), there’s a large amount of data that shows that there is -SOME- predictive value. I think it’s worth it, from a professional or even just hobbyist perspective, to examine this misconception and take it apart. So, what powers the flying car fallacy?


“They promised flying cars. There are no flying cars.” Perhaps a bit more verbose than the normal phrasing, but it serves my needs. I’m perfectly comfortable admitting that I’m deconstructing a particular phrasing of this claim that I myself constructed, but I feel the above version adequately represents the concepts and thoughts typically being expressed.


To examine this more closely, it needs to be decomposed. Let’s look at the first sentence: “They promised flying cars.” This is more interesting than it might appear at first glance. There’s a lot of meaning contained in the three concepts in this sentence. First, “they” implies some form of authority or expert. Honestly, while I can find plenty of general references to a ‘they’ or ‘scientists’ or ‘futurists’ discussing flying cars, most of these references fail to cite a specific source. Other controversial topics in futurism (such as AI) often have specific names claiming specific dates, a much more falsifiable claim.


An article on Livescience discusses broken science promises, flying cars among them, and mentions Popular Mechanics and Popular Science. Further investigation reveals that discussion of personalized flying transportation (and railway cars, something that did in some ways come true) go all the way back to the 1930s and 1940s. But still…these were popular magazines. By those years, they had already transitioned into appealing to the public mind and eye as opposed to serious, calm discussion.


This isn’t to say that experts haven’t forecast flying cars–but that allows us to take a look at the second word in the first phrase, “promised”. What does “promised” mean? Well, it might be semantics, but to my mind that means that people are taking a personal guarantee that flying cars will exist rather than a prediction, projection, or forecast. Forecasters who “promise” something about the future are generally not experts but popularizers–experts will generally couch statements carefully.


What does Google say? Well, if you search explicitly for the string “promised flying cars”, it returns about 239k results. If you search explicitly for the string “predicted flying cars”, it returns only 19.5k results. Other configurations return even less. Because it’s a personal guarantee, a promise, people feel betrayed. And that betrayal sticks in people’s minds as a failure for an interesting future to come about, disregarding all the other things that HAVE happened. Things that have happened become natural–things that don’t happen are failures.


Finally, the term “flying cars” itself is a bit of a misnomer–or at the very least unspecific, and looking at exactly what it means lets us address whether or not flying cars ‘exist’ or not. The off the cuff thought is simply a car that is unconstrained by the rules of the two dimensional road. If you think about it a bit more, you conceive of one of two things. The unrealistic/idealistic version is trivially having access to flight to ease up traffic without requiring building additional expensive infrastructure. The more realistic/pragmatic example, however, is a car that also works as a plane, and is subject to all the restrictions that entails (something that has been shown in prototype multiple times, with the most recent being the Parajet Skyrunner, which works off a parachute and a very light body, and the Terrafugia Transition, which is more technically a roadable airplane).



Why Didn’t They Happen?

Okay, so we’ve established that actually using the flying car fallacy generally has to do with a failure to live up to a flight of fantasy that appealed to the imaginations of readers and fans of technologies, rather than a serious, pragmatic estimation of the future. But why DIDN’T they happen? Well, to go over it very briefly (as there are more issues holding back flying cars than can possibly be dealt with in a competent manner here, but they have been discussed in depth elsewhere, we’ll keep it brief):

  • Safety: Three dimensions and velocities make things much more dangerous, meaning that there will necessarily be quite a bit tighter…
  • Regulation: Pilot’s licenses are more difficult to get, violations would be punished more harshly, variations would take longer to be approved.
  • Cost to consumer: Flight takes more fuel than driving, not to mention the fact that the additional engineering required would mean that vehicles would be drastically more expensive–in turn, leading to the fact that a comparatively small portion of the population would use the needed infrastructure. Speaking of…
  • Cost of infrastructure: New structures to support new dimensions of travel, new ways to deal with cars taking off and landing, etc. As mentioned above, this would be required for a comparatively small portion of the population, unlike roads which (with the exception of some private toll roads) are used by both expensive and economic cars.

Arguing Against It

To argue against the flying car fallacy, you need to clearly delineate between different types of technological predictions (or promises). Making sure that wild unsupported flights of fancy aren’t put forward as representative of your beliefs is ideal. In fact, one of the major things you should take away from this is that you SHOULDN’T let your hopes rise when someone claims something about the future, but can’t present rigorous evidence as to why or how it will happen. The next blog post will go into how to counter poorly framed techno-optimism and promises.


Citing the lack of flying cars isn’t the only pithy response people make in response to positive predictions about the future, but it is most certainly a common one. However, it’s founded on a bitterness on the lack of follow through from visionaries more than any widespread failure on the part of people who make rigorous evaluations of future possibilities. I am in no way trying to say that people should by default accept optimistic predictions about the future, any more than they should reflexively dismiss them.


In the end, if someone wants to believe that a failure of techno-optimism to bring about their hopes means that all forecasts fail, you can’t convince them otherwise. The best thing you can do is try to show them amazing things that WERE predicted ahead of time.


Thanks to Paul Bragulla for Proofreading and Discussion

Status Quo Fallacy

It’s almost inevitable that if you openly speculate about new technologies that have any impact on society that change the status quo, you’ll be met with a pithy response of ‘Previous technologies didn’t change (Relevant aspect of society), what makes you think this one will?’ It might not always be phrased that way, but it’s certainly a common sentiment that I expect many readers will have heard.

Of course, this pops up most commonly when you’re discussing automation. As an example, if you discuss the displacement of workers in various industry segments and skill levels, you’ll be met with responses ranging from ‘technology opens up more new jobs than it replaces’ to ‘the luddites originally complained about being put out of work too’. Incidentally, for that last example–turns out many luddites WERE put out of work. That’s not to say I agree with them-history bore out that mechanization of industry improved the lot of the working class in Britain tremendously…but wage suppression still hurt in the short term.

One of the easiest ways to model the future is to assume something won’t change. This isn’t accurate, but it’s easy. People like thinking that what they are familiar with will always be around. Sometimes it’s selective–people will isolate one or two issues they have with the current dynamic of society and humanity, and look at how they  might be affected by technology, but assume the context is the same.

More often, they might pick one or two coming technologies and see how they cause a systematic impact, but not take into account momentum of existing social structures and whatever underlying human motivations cause them (unless the technology is one that directly alters the human condition, such as various neuroprosthetics or nootropics). This is particularly common, and problematic, with people whose futurism is driven by a particular political ideology they wish to see come to pass (or not come to pass, depending on if they are seeking utopia or avoiding dystopia).

The pithy way to phrase this belief, what I call the ‘Status Quo Fallacy’, might be the statement that “Quantitative change will not lead to qualitative change”. Can we argue this point? Is it possible to point to any sort of historical popular statements or predictions that stated that quantitative change wouldn’t lead to qualitative change?

Conveniently, yes! Professor Donald Simanek of Lockhaven University of Pennsylvania has conveniently collated a list of some of the best overly negative/pessimistic quotes about the future of science and technology throughout history, as well as a few overly optimistic ones (which we will revisit in a later article).

I strongly advise reading it yourself for some degree of amusement, especially one of the earliest quotes:

I also lay aside all ideas of any new works or engines of war, the invention of which long-ago reached its limit, and in which I see no hope for further improvement…- Sextus Julius Frontinus, governor of Britania, 84 C.E.

Regardless of ancient humor, there are some more relevant quotes. As the topic of this blog concerns science and technology, and as I’d like to avoid stepping into politics and theology, I’ll disregard those quotes. Furthermore, I think the point is best illustrated in a case where a technology had already been demonstrated as achievable and practical, if not quite ready for mass production. The final requirement is that the quote comes from someone with a degree of authority on the topic or at the very least understanding–luckily, nearly all of the quotes fulfill that requirement.

What does that leave us? Erasmus Wilson claimed that the electric light would not surface again after the Paris Exhibition closed. Lord Kelvin, a mathemetician and physicist, claimed that radio had no future outright. The inventor of the vacuum tube, Lee DeForest, said television had no future. Even the head of 20th Century Fox, who had made his fortune on the movie boom, claimed that television would never gain market share. These are all from the telecom industry, as they in many ways are the predecessor of today’s computer and data industries.

What’s the commonality between these? Individuals who knew systems intricately, who helped develop them or had helped develop their predecessor, were blinded by the status quo. When you are living in a system and much of your life revolves around that system, you either don’t want it to change or you can’t let yourself expect that it will change.

Does this still apply today? Absolutely. People have continued to make predictions, especially about computers. But every time they can’t show, quantitatively or qualitatively, why their prediction holds true for the future instead of simply being a hold-over from the past, you have to treat it with immense skepticism.

This is not to say all negative predictions should be ignored, however. Many have completely valid reasons, and should be used to construct a rigorous model of the future.

In further articles in this series, I hope to examine precisely when various failed predictions about technology came true, and see if there is any sort of consistency between when something was getting enough attention to make a bold statement about it, and how long it took to come true. I will also discuss the value of tempering enthusiasm (lowering the ceiling as opposed to raising the floor, so to speak), and being able to differentiate between different types of failures in technological development.

Technology Tracking Methods Part 1: The Problem

This is less an informative lecture than some thoughts on a problem that I run into.

Technology foraging, technology tracking, whatever you want to call it–is hard.

To keep abreast of all the technologies that I feel are necessary, I have to read approximately 50 RSS feeds a day, and sort through the content by hand. I had previously attempted to put together a system that automatically sorted articles by subject and importance, but it didn’t work out so well (this is part of the driving purpose behind a project I’d like to unveil to the public sometime shortly). This means that I have to go through about ~300 articles a day and manually tag/sort them, as well as decide how important they are.

Furthermore, I’m only gleaming the tips of the iceberg–there’s thousands of industry specific scientific articles that I’m missing, not to mention the wealth of information hidden in areas like patents and scientific journals. There’s an incredibly amount of data, and I’m missing huge amounts of it. To adequately track technology, I need to be able to render down all that data into something human readable or searchable.

Is it so surprising, then, that most people (even ones that see the development of technology as critical to their profession) can’t keep up with technology? I have to specifically set aside time to do it and it can get wearying even for me. It doesn’t scale, either. There’s no real way to add more to my tracking abilities as they stand right now without a linear increase in time spent. This means that further tools are needed.

These tools are being worked on right now, and I hope to implement the first step soon, which I’ll discuss briefly in the next blog post. I hope to share parts of my process as I develop them so that others are either inspired to take up the tools I provide, or build their own. The problem is currently poorly served.


This blog falls out of my experiences looking at emerging technologies and forecasting in the last few years of my life.

I spent late 2012 through early 2014 as one of the founders of a consulting start-up called ‘Prokalkeo’. Prokalkeo’s goal was to help companies plan a strategy for emerging technology. It didn’t quite go that way-we ended up primarily doing market research. Our website is still up, if you want to investigate, and you might see some of the inspiration for this blog there.

I started Prokalkeo because I cared about the subject. Unfortunately, scrambling for clients doesn’t leave you a lot of time (or energy) for a deep investigation into a subject. While we knew our stuff, we weren’t able to push the boundaries back as much as we would have liked, let alone formalize it into any sort of framework.

That’s in the past, now–I’m employed elsewhere in a job that I love, and that allows me to have the energy to pursue outside interests. I’ve wanted to do something like Stratexist for a while.

The blog is titled Stratexist for a couple reasons–I hope to become a master strategist of technology, and I want to prove to myself and the world that viable, rigorous methods to plan a strategy of technology exist.

Please watch this space for updates. Unlike some blogs, I’m not going into this knowing what the outcome is going to be. This will be a place of reviewing existing papers and content and making them more well known, but also hopefully pushing back the boundaries of forecasting. Content will range from operations research, to math, to economics, to simple heuristic business decision making.