The emergence of on-demand superapps has become a game-changer for many Filipinos.
Commuters found a more comfortable way of navigating Philippine cities known for their horrendous traffic and inefficient transportation system.
Customers now enjoy the convenience of having food delivered on-demand.
As business establishments aim to cut costs, drivers and riders found alternatives from the traditional 9-to-5 job.
Digital platforms such as Grab, Angkas, Joyride, and FoodPanda come in to bridge all these needs. But the convenience brought by these apps comes at a cost.
The hype around generative artificial intelligence (AI) is accelerating the adoption of AI tools. As journalists, it is our role to scrutinize the use of such technologies. In the case of AI-driven apps in the Philippines — majority of which are imports — who really benefits, and who bears the risks the most?
Our data-driven investigation, the first of its kind in the country, exposes how technological innovations like ride-hailing and food-delivery applications are supposed to improve people’s lives, but because their advancement has far outpaced existing laws, the touted benefits are unevenly distributed.
In “Grab fares surge under opaque algorithm,” we worked with 20 researchers and spent more than six months examining Grab’s algorithm and how it impacts consumers and drivers. By collecting data from Grab, we discovered that rides for at least 10 routes always included surge charges, the fee added by Grab to get more cars on the road.
Knowing whether GrabCar rides always included surge fees was only the first thing we wanted to find out. We also wanted to check whether the ride-hailing company’s surge pricing model worked as advertised – that it would get more cars on the road. The data we gathered suggested otherwise: customers still had to endure lengthy wait times even when fares were high. This meant that the app’s algorithm was not working as advertised, confirming with robust data the numerous complaints on social media about Grab’s seemingly steep prices.
Beyond the data, we also looked into how Grab was able to dominate the market; how algorithms are regulated; the underlying factors that make navigating Metro Manila so difficult; and, most importantly, what needs to be done.
In “When apps are gamified, workers rarely win,” we then delve into the lives of food-delivery and ride-hailing workers whose daily routine is dictated by an app.
Workplaces are required to secure permits and undergo inspections before they can legally operate. But what if the “workplace” is an app powered by algorithms? Who inspects how it operates? Who evaluates the algorithm and ensures it doesn’t encourage problematic behaviors?
Philippine laws have yet to adequately address issues concerning apps and algorithms, leaving their regulation limited. This gap often burdens Filipino workers who depend on these platforms as their primary source of income. While ride-hailing and food delivery work is branded as “gig work,” the reality is far from the casual nature implied by the term. These so-called gig-economy workers struggle with uncertain pay, indebtedness, and the physical toll of chasing incentives.
