In 1998, Stanford University students introduced Google as a groundbreaking search engine that transformed how we navigated the web. Its innovative algorithm ranked websites based on the number of inbound links, providing a more effective way to find relevant information compared to existing search engines like AltaVista.
This system of ranking sites via links acted like an automated peer review, enhancing the quality of search results and revolutionizing internet searches for users.
However, despite its initial success, Google faced challenges with its business model. Initially resistant to advertising, it eventually embraced it in 2000. The company’s new model involved collecting and analyzing user data to provide targeted advertising opportunities, marking the beginning of what would later be known as surveillance capitalism.
This approach allowed Google to generate significant revenue by monetizing user behavior, although it set the stage for future issues.
Over time, Google’s model fell victim to “enshittification,” a process where a platform initially offers high-quality services to attract users but gradually shifts focus to profit maximization, often at the expense of user experience.
This phenomenon led to a decline in service quality, but Google maintained its dominance due to its entrenched position and users’ inertia. Despite deteriorating experiences, Google remained the primary search engine globally, with “Googling” becoming synonymous with online searching.
The advent of ChatGPT and similar AI chatbots has begun to disrupt Google’s business model. Unlike traditional search engines that list websites, chatbots provide direct answers, which reduces the need for users to click through search results and exposes them to fewer ads.
This shift could impact Google’s revenue from search ads and change users’ expectations for online information retrieval, challenging Google’s long-standing dominance.
Recently, Google has adjusted its approach to search by focusing on the principles of expertise, authoritativeness, and trustworthiness (EAT) rather than trying to index all available content.
This change reflects a move towards being more selective about what content gets indexed, prioritizing unique and authoritative sources. However, this shift raises questions about Google’s ability to effectively evaluate content quality on a web flooded with AI-generated material, recalling past challenges faced by earlier internet platforms like Yahoo!.