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Malta’s Hidden Boss: The AI Controlling Your Ride Drivers

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Angelo Dalli

In today’s gig economy, hundreds of people work for app ride platforms like Bolt, Uber and eCabs, often drawn to Malta by the promise of flexible hours and the allure of being their own boss. But in reality, many drivers are finding that the true boss of their workday isn’t human—it’s an algorithm.

Artificial intelligence (AI) systems run these platforms, making key decisions about which rides drivers are assigned, how much they’re paid, and even how their performance is evaluated. While passengers enjoy the ease and convenience of hailing a ride with a few taps on their phone, drivers are subject to the decisions of an AI that’s largely invisible yet all-powerful. This raises critical questions about fairness, transparency, and the ethics of allowing algorithms to control people’s livelihoods.

The Algorithm at the Wheel

Every time a passenger requests a ride through an app, they trigger a complex AI system designed to optimize the entire process. The algorithm instantly analyzes a wealth of data—how many drivers are nearby, what traffic looks like, the destination, and even the weather. Within seconds, it matches the passenger with the driver it deems most suitable. This decision is not made by a human dispatcher but by a set of invisible rules designed to maximize efficiency.

For the driver, this means they don’t have much say in the matter. Unlike a taxi driver who might choose their passengers, app drivers are at the mercy of the algorithm. The system tells them when to go, where to go, and even how to get there. The promise of freedom that initially attracts many to gig work quickly fades as they realize that their workday is dictated by an AI that they neither see nor understand.



Surge Pricing: Earnings at the Whim of AI

Surge pricing—where fares increase during periods of high demand—is one of the most well-known features of ride-hailing platforms. It’s designed to balance supply and demand by incentivizing more drivers to go online when there are more passengers requesting rides. But while surge pricing may make economic sense from the platform’s perspective, for drivers, it introduces a level of unpredictability that can make earnings difficult to plan.

Many drivers report feeling like they’re chasing after elusive peak times, often driving around in search of these surge zones or waiting for the app to notify them of higher prices. In these moments, their income is at the mercy of the algorithm, which raises and lowers prices based on a set of rules they cannot control. What may seem like a lucrative business model for the platforms can leave drivers feeling powerless over their financial stability.

The Weight of Ratings

Passenger ratings are another tool the algorithm uses to manage drivers. After each ride, passengers are asked to rate their driver on a scale of one to five stars. A driver’s overall rating is more than just a number—it can determine whether they continue to receive ride requests. Drivers with consistently low ratings might see fewer ride offers or be deactivated from the platform entirely. This places tremendous pressure on drivers to maintain high ratings at all times, even when situations beyond their control, such as bad traffic or a difficult passenger, might lead to a lower score.

But the algorithm doesn’t stop at ratings. It tracks every part of a driver’s performance, from how quickly they accept rides to how efficiently they navigate routes. The platform’s AI collects all this data and uses it to make decisions about the driver’s future opportunities. While passengers may assume they’re interacting with an independent driver, what’s really happening is a silent, algorithmic evaluation process in the background. Drivers, meanwhile, are constantly being judged by a system that’s invisible to them and impossible to reason with.

The Ethical Dilemma of the AI Boss

The rise of AI-driven management raises significant ethical concerns. The algorithm may be efficient, but is it fair? Most drivers don’t fully understand how the system works. They don’t know why they’re assigned certain rides, why their earnings fluctuate, or how their ratings affect their opportunities. The lack of transparency leaves drivers feeling frustrated, and many argue that they’re not truly independent contractors if an algorithm controls so much of their work. The lack of transparency may also leave customers feeling frustrated, as prices may rise inexplicably due to minute variances in supply and demand.

This is where the concept of Explainable AI comes in. If AI systems were more transparent, drivers would have a better understanding of how decisions are being made. For instance, they could know why certain rides were assigned or why surge pricing is applied in specific areas. Such transparency could also help drivers challenge unfair decisions, like a sudden drop in their rating or unexplained shifts in their pay. Customers can also get better insight as to why they are being charged more than usual.

But transparency isn’t the only ethical issue. There’s also the question of accountability. If an algorithm makes a mistake—say, it unfairly penalizes a driver based on a misunderstanding of their behavior—who is responsible? Currently, there’s little recourse for drivers to appeal these decisions. They’re left at the mercy of a system that is often opaque and difficult to challenge. In a traditional workplace, a worker could speak to a manager or file a formal complaint. With AI, these human processes are removed, leaving drivers in a precarious position.

Then there’s the issue of bias. AI systems are not neutral. They learn from data, and if that data is biased, the algorithm can reinforce existing inequalities. For instance, if the system prioritizes wealthier areas or drivers from certain backgrounds, it could unfairly disadvantage others. While AI promises efficiency, it also has the potential to perpetuate discrimination, often in ways that are hard to detect.

The Future of Work Under AI

As ride platforms continue to grow, the role of AI in managing gig workers will only increase. We’re already seeing more sophisticated algorithms that track driver behavior, predict passenger demand, and adjust pricing on the fly. And with the looming possibility of autonomous vehicles, the role of human drivers could one day be eliminated altogether, replaced by a fully automated fleet.

But even before that happens, the relationship between workers and AI will become a central issue in the future of work. For drivers, understanding how the algorithm works—and having the power to contest its decisions—will be key to ensuring fairness in the gig economy. Without more transparency and accountability, the AI systems managing these workers could create new forms of exploitation, where the people doing the work are powerless to control their own destiny.

As AI continues to evolve, the question remains: Can we balance the efficiency of these systems with the ethical need to ensure fairness and respect for the human workers they control? For app ride drivers, the AI boss is already here. The challenge now is making sure that it’s a fair one.

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