Critical Listening: How to Cut Through the Bullshit on Podcasts and Audiobooks
It has become commonplace for people to do a lot of their learning through audiobooks and podcasts, instead of physical books.
Fast and cheap internet and smartphones have made accessing several-hour-long audio files as simple as a click of a button, and something we can do anywhere — in the gym, in the park, in our cars, and so on.
Over one in five Americans now listen to audiobooks, and the trend towards listening to audiobooks instead of reading physical books is picking up steam, especially amongst people who previously shied away from reading a physical book, opening up a new market for book publishers.
Not only that, but 55% of Americans have listened to podcasts, with 24% of people listening to podcasts at least weekly.
With so many people turning to audio to not only be entertained, but to learn — with shows that run the gamut of personal development through to scientific inquiry such as The Tim Ferriss Show, The Joe Rogan Experience, EconTalk, and The Knowledge Project becoming incredibly popular— it’s important that we listen critically, instead of taking everything we hear on face value.
As with reading, it’s not just the hours we spend listening to audio that matters, but the quality of our attention and our interpretation of what we’re listening to.
In a world where virtually anybody can start a podcast on a shoestring budget, the number of active podcasts hovers around one million, and so, the amount of noise that comes with that — on low budget and big budget podcasts alike— has increased by orders of magnitude.
If you find yourself saying “I heard it on a podcast” as conclusive evidence of something, you’re probably not listening critically.
How to Listen Critically
Below are five things to listen out for when consuming audio. The more you do this, the more it will become second nature, and the more critical listener, and thinker, you will become — a skill you can apply to most aspects of life.
1. Absolute Language
As Nobel Prize-winning physicist Richard P Feynman put it, “You can never be sure you’re right. You can only be sure you’re wrong”.
Science isn’t about proving things true beyond any irrefutable doubt. It is about developing a less wrong or more right view of the world, based on what we know about it. But there are usually far too many variables to control for, and far too many unknown variables, for us to know ‘for sure’ that something is absolutely true.
As a result, most things are gray, not black and white, and almost never one hundred percent conclusive. When people use absolute language, it signals absolute thinking, and the truth is typically sacrificed.
Absolute language to look out for:
- Only — only white people like NASCAR.
- All — all rich people are assholes.
- Never — there will never be another plague.
- Impossible — “That’s impossible”… is what the automotive and aerospace industries told Elon Musk before he successfully built Tesla and SpaceX.
- Always — swans are always white… thought Europeans before they discovered black swans in Australia in the 1700s.
- Must — you must do this, you must do that.
- Everything — “Everything is f*Cked” — is it, really? Everything?
- Need — we don’t need to do, or need to have most things. We might want or prefer, but we rarely need. Usually indicative of lazy rhetoric.
2. Weasel Words
Sometimes people might use weasel words to make a point, without fully committing to the point they’re making.
They might use words such as many, studies show, there is evidence that, often, most, probably, likely, up to, some, or could be.
Personally, I think this is an honest approach to take, and takes account of the fact that most things are inconclusive and based on our understanding of the world today.
But we should be wary of people who use such words but take them to mean something more. For example, someone might say that “many children who play violent videogames have demonstrated violent tendencies”, and act as if violent videogames cause violent behavior.
Anybody who studied relational databases at college knows that, technically speaking, anything more than one can be considered many. As such, the abovementioned statement actually means nothing without further context around how many children were observed, and what percentage of them demonstrated violent tendencies. I
t also says nothing about what other factors might have influenced the violent behaviors amongst the children observed.
When people use anecdotes or stories to make their case, be wary because said case might not be so strong. It might be no different to your mom telling you that “your uncle Frank started a business, and he lost everything!” as a good enough reason to not pursue entrepreneurship.
In fact, best-selling books built around anecdotes — such as Jim Collins’ Good To Great, have been largely debunked in retrospect (many of the high performing companies profiled later fell out of the S&P500).
We can always find isolated examples, incidents, or events to support our case, but what matters is the larger body of evidence from which we draw conclusions. Anecdotes, without studies that back them up, or a very strong pattern or trend that comes up time and time again across thousands of related anecdotes, mean very little.
4. Bullshit Science
One thing many people are susceptible to when listening to podcasts is science-speak. There is a misconception that if one peer-reviewed study came to a conclusion, that it is, therefore, true — but as touched on earlier, this is simply not the case.
As Carl Bergstrom and Jevin D West, authors of the bestselling Calling Bullshit: The Art of Scepticism in a Data-Driven World, put it, “there’s plenty of bullshit in science, some accidental and some deliberate”.
Studies can be performed and hacked in ways that come to confirm a pre-existing belief.
Studies can be sponsored by large organizations to support their own commercial interests (hello big food!).
Peer reviewers don’t look over things with fine-tooth combs.
And often, studies can just be plain wrong, with some disciplines being more susceptible to this than others.
A report penned by Open Science Collaboration in August 2015 found that study replication rates (ability to replicate same conclusions by re-performing previous experiments) for psychology studies ranged from just 23% for social psychology up to about 50% for cognitive psychology. In fact, the replication crisis in the social sciences is a widely accepted fact. And we see similar challenges plaguing economics and medicine.
When it comes to science, as with anecdotal evidence, if a large body of studies, independent of each other, all come to the same or similar conclusions, then we can have more faith in said conclusions being true.
However, for every individual study you find that says one thing, you’re likely to find another that says something different.
Case in point:
Also, if someone appears not to know how the study was performed, but just points out the conclusion, it should raise a red flag.
I could have lumped this in with science, but stats are so widely abused that I felt they deserved their own entry.
You’ve probably heard the saying that ‘87% of statistics are made up’.
It’s probably true. At least I’m 87% sure of it.
You get where I’m going with this.
Unless statistics are substantiated with a little context, you can take them with a grain of salt. Remember, most people that get paid to complete surveys are probably not representative of the actual target population said survey is supposed to tell us something about.
So next time you find yourself listening to a podcast or audiobook, and someone uses absolute language, weasel words, anecdotes, or puts all of their faith in a single scientific study — double-blind and peer-reviewed or not — don’t take it at face value.
Instead, ask yourself why what they say might be wrong, accounting for not just the above, but also the person’s personal motivations and incentives because they may not be aligned with yours.
If we’re going to spend hours consuming digital audio, then let’s listen critically when we do it.
PS. I’m fully aware that I’ve used a number of weasel words in this article (oh the irony!), and given the context in which I’m saying it, I think it made sense to do so. If you're not so sure, refer again to point #1.
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