The real danger of algorithms isn't their ability to personalize offers based on taste. The harm occurs when they identify and exploit consumers' lack of information or cognitive biases, leading to manipulative sales of subpar products. This is a modern, scalable form of deception.
While seemingly beneficial, algorithms that perfectly cater to existing preferences (e.g., in music or news) can trap users in narrow cultural silos. This "calcification" of taste prevents personal development and creates a balkanized cultural landscape, hindering shared experience and discovery.
Contrary to the common view, algorithms charging different prices based on a consumer's wealth can be beneficial for market efficiency. The real harm occurs when algorithms exploit a lack of information or behavioral biases, not simply when they adjust prices based on a person's ability to pay.
Current regulatory focus on privacy misses the core issue of algorithmic harm. A more effective future approach is to establish a "right to algorithmic transparency," compelling companies like Amazon to publicly disclose how their recommendation and pricing algorithms operate.