Introduction to Enshittification
Enshittification, a term coined by Cory Doctorow, describes the inevitable decline in quality of two-sided online products and services over time. This phenomenon is characterized by three distinct stages: being good to users, exploiting user dependence to benefit business customers, and finally, squeezing both users and businesses to extract maximum profit, leading to a terrible service for everyone.
Stage 1: Good to Users
In the initial stage, platforms attract users with great features, locking them in. This is evident in the early days of social media platforms and dating apps, where the primary focus was on providing a seamless and enjoyable user experience.
Stage 2: Good to Businesses
As platforms grow in popularity, they start to exploit user dependence to benefit business customers. This is achieved through the introduction of ads, fees, and other revenue-generating strategies. While this stage may seem beneficial for businesses, it marks the beginning of the end for users.
Stage 3: Good to Shareholders/Platform
The final stage is where platforms prioritize their shareholders’ interests over users and businesses. This leads to a decline in service quality, as companies focus on extracting maximum profit. The consequences of enshittification can be seen in the examples of Google Search, Facebook, and other platforms that have prioritized profit over user experience.
The Enshittification of AI
As AI technology advances, it’s essential to consider whether it will follow the same path as other digital platforms. According to Cory Doctorow, the enshittification of AI is a predictable decline that sets in as digital platforms and services go from dazzling to dreadful. The signs of enshittification are already visible in AI-powered platforms, with the introduction of ads and price hikes.
Practical Takeaways
To avoid the pitfalls of enshittification, it’s crucial for companies to prioritize user experience and transparency. This can be achieved by implementing fair pricing models, providing clear guidelines on data usage, and ensuring that AI-powered services are designed with users’ best interests in mind.