IS ALGORITHMIC PRICING ETHICAL?

Algorithmic pricing is defined as using software or AI to set prices based on data such as the demand, the time of day, the weather, inventory, and specific customer browsing. It is important to distinguish the two different types of algorithmic pricing, as they pose different ethical concerns. One of those types is surge or dynamic pricing, which is prices changing for everyone based on real-time demand. The other type is personalized pricing, where different individual customers see different prices based on their browsing history, location, device type, purchase history, and other data. As the consumer, dynamic pricing already feels bad enough on its own, but personalized pricing changes feels like a deeper violation; is it fair to be charged more simply because the algorithm thinks we can or will pay more?

As usual, we will begin with the case FOR algorithmic pricing being ethically defensible. The most common argument is that the prices are simply responding to real supply and demand; without surge pricing when needed, market efficiency goes down. For example, surge pricing incentivized more Uber drivers to drive when riders needed them the most. Another argument is the resource allocation argument, which states that without changing pricing, goods are taken by whoever shows up first rather than who values the product the most; by increasing prices when demand goes up, those who want the product the most are the ones that purchase it, introducing a fairer rationing mechanism into the market. Now, let’s tackle the more interesting part of the case for ethical defensibility: how does this apply to personalized pricing changes? The strongest argument here is that while personalized pricing may charge more to those who can afford it, it also charges less, or even discounts, prices to price-sensitive customers such as students and seniors. 

Now, let’s tackle the argument AGAINST algorithmic pricing being ethically defensible. The first argument is that an individual’s vulnerability is exploited during surge pricing. During emergencies, when demand for basic resources such as water, shelter, and transportation go up, pricing also going up can be extremely unethical, as it results in depriving people of basic necessities needed for survival. An example of this occurring is Uber’s surge pricing during the 2017 London Bridge terror attack, during which fares spiked when everyone tried to flee at once due to high demand. Although Uber later apologized and refunded riders, the damage had already been done since the pricing changes were made by software and AI automatically. Another argument is the discriminatory pricing argument, which is essentially the argument that pricing higher for certain customers based on their browser history and other personal data is unfair and discriminatory. Finally, one last argument is the information asymmetry argument. In personalized algorithmic pricing, the customer does not know what the other person is paying, meaning they don’t know that they could be paying less or more than other customers. Therefore, the consumer’s choice isn’t fully informed and is considered unfair. 

As I leave you with both sides of the argument to think about, here are a few complicating questions to both scenarios. Is the ethical issue about the pricing method itself, or about what data is used to set the price? Should companies be required to disclose when and how algorithmic pricing is being used, and would that make algorithmic pricing ethical since the information asymmetry is resolved?