What is Public Transport Enshittification? Mobility in the Age of Internet and AI
Updated: 3 hours ago
If you're a commuter in Metro Manila, you'll realize that our mobility crisis extends beyond damaged roads, vehicle congestion, and waiting on hot or flooded curbs. It's now also about algorithms. Over the years, you may have noticed the absurdly rising costs of using app-based services for your regular trips, whether it's from home to work, home to school, home to the provincial bus station, home to the airport, and more.
Across the globe, journalist Cory Doctorow’s concept of “enshittification” explains how digital platforms systematically decay. They start by luring users with cheap, subsidized services. Once users and businesses or gig economy workers are locked in, the platform pivots, squeezing both sides to maximize shareholder profit.
While this model began in software, its real-world consequences are devastating when applied to transport. In the Philippines, we are witnessing the enshittification of transit, where digital platforms collide with underfunded public infrastructure and services.
The textbook example began a decade ago. Tech giants like Uber entered the local market backed by venture capital, offering heavily subsidized, affordable rides. This artificial affordability diverted middle-class commuters away from buses and public utility vehilces/jeepneys. When Uber exited Southeast Asia, it handed its fans to Grab, cementing a virtual monopoly.
Other players like JoyRide, Angkas, InDrive, and GSM Taxi, among others, initially positioned themselves as cheaper, pro-worker alternatives. Yet, they too are bound by the same corporate lifecycle, gradually tightening the algorithmic squeeze on commuters and app-based workers alike.
With Artificial Intelligence--the we-are-putting-the-algorithms-on-steroids-so-try-to-catch-up disruptive technology--we should expect more, well, disruptions. In non-ridehailing businesses, platforms and companies are adding "AI" in their brand to help solve the same wicked problem of urban congestion and road safety through "integrated planning" or "predictive traffic management system".
We wish them success in accomplishing these goals, or those of their clients.
But when applied to mass transit, a scenario we must avoid, 'AI-driven efficiency' could become an excuse for more tech solutions that shift public/government and private investment away from reliable and safe public transport. Instead, we are distracted by another app-based solution or expensive digital infrastructure claiming to help 'solve traffic' (again).
This creates a dangerous operational feedback loop for transit. As commuters are forced (or influenced by algorithms) onto more private modes, traditional mass transit--our jeeps, buses, and trains--loses ridership and political priority. Instead of investing heavily in high-capacity, high-frequency, worker-owned and worker-led public transport, cities can't wait to post on social media about the "launch" of this or that transport network service.
Ultimately, the enshittification of our public transport sector is a symptom of a society trying to outsource its way out of public responsibility. Relegating mobility to private or semi-private modes is like encouraging private school enrollment rather than funding accessible public schools and capacitating our teachers and non-teaching/admin personnel. In this age, innovations must be used to support public transport and empower the its workers.
