24% of smartphones shipped globally in Q4 2022 were iPhones; 76% were Android phones. If I want to buy a phone trusted by most buyers, which one should I choose?
Comparison is an important logical tool. It is one of the primary methods of reasoning. But for comparison to work, it must rely on a shared and relevant dimension between the things we compare. Without such a dimension (or when we use an imaginary or distorted dimension), the comparison becomes fake — a very subtle fake that factual data might cleverly mask.
If I want to buy a popular phone, comparing iPhones to Android phones is misleading. iPhone is a complete product — a phone designed and manufactured by Apple. Android, on the other hand, is not a phone at all. It is an operating system — a piece of software embedded in hundreds of different phone models made by dozens of brands. So while the most popular mobile operating system is indeed Android, Apple’s iPhone was the most shipped phone brand in Q4 2022, followed by Samsung phones with 19.4%. If I am looking for the most popular brand, Apple’s is the one I am looking for.
Now, to be honest, even comparing iPhones to Samsung phones (or any other brand, for that matter) is probably not the most reliable comparison if I am looking for my next phone. Each of these companies sells more than one model at any given time, and this fragmentation is obscured when comparing only the brands. Each model has different features, a different design, quality, and, no less importantly, a different price. It might make sense to go for the most popular brand, but if I care about value for money or the features of the product I buy, I will probably want to compare the popularity of actual models.
All these different comparisons can be potentially valid as they are based on actual data. Each can become a false, misleading comparison depending on my needs. When looking for the most popular phone, comparing iPhones to Android phones is meaningless. However, if I am an app developer and I want to know which operating system is the most popular, the same comparison might actually make sense, as all iPhones run the iOS operating system.
That’s precisely what makes False Comparison a subtle fake-creation method: the comparison itself might be genuine or fake; it all depends on the conclusion that follows.
How to Deal With False Comparison
Before dealing with the comparison itself, don’t blindly trust the quoted data. Unless you already trust the source citing the data, double-checking it using other resources (or looking for the origin of the data) is always a good idea. Sometimes, and especially when someone deliberately creates fake content, the data itself will also be manipulated.
Once you are sure the data used for the comparison is reliable, it is time to look at the conclusion of the comparison and consider what dimension it is based upon. Fake conclusions will be based on a new dimension that is not apparent in the data, a dimension not relevant at all to the data, or a dimension that applies to only some of the data. In the example above, the conclusion about smartphone brand or model popularity adds a dimension that applies only to one of the two facts I cited: one of the numbers didn’t apply to a brand or a model.
The best way to deal with a potentially fake comparison is to consider the type of conclusion you aim for and what dimension is required to reach that conclusion. Then, make sure the data presented include that dimension, and if it doesn’t, look for data that does.
Remember: Fake content can be based on actual facts and figures. Reliable data doesn’t mean valid conclusions.
