For years, Uber has invested evenly in AI, now, this technology is widely applied and acts as a vital capillary throughout the business.
While the integration of AI has brought benefits to the platform, it is important to remain vigilant when data privacy and AI bias come into play.
The AI technology behind Uber
The ride-hailing services provider was founded in 2009 and has made multiple investments in AI to power its platform and make it work more efficiently. These include using computer vision to validate the identities of its drivers and intelligent location data to improve the accuracy of vehicle locations on the platform. The company uses its deep learning algorithm, DeepETA, to enhance forecasts of rider demand and predict pick-up and drop-off times based on map data and traffic measurements. It also uses a machine-learning-powered algorithm to calculate the variation of fares and facilitate its surge pricing.
The ride-hailing company also improved its conversational platform to make communication with customers more accessible. This enhancement benefits drivers, who can better focus on driving thanks to hands-free pick-up and one-click chat features.
In the future, Uber Eats plans to roll out 2,000 four-wheel robots in major US cities in 2026 to drop off food orders.
Reflecting on past ethical dangers and anticipating future ones
In 2021, Uber encountered an AI issue when an Uber driver lost his job because the automated face-scanning software failed to recognize him. The driver’s account was suspended after the facial recognition software could not verify his photo, leading to accusations of racist facial verification technology. The Independent Workers’ Union of Great Britain supported the driver and claimed that at least 35 other drivers had seen their registration terminated due to alleged software mistakes since the start of the Covid-19 pandemic. Protesters, including 80 Uber drivers, gathered outside Uber’s London headquarters, expressing concerns about the software’s role in disproportionately terminating drivers of colour.
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By GlobalDataUber uses Microsoft Face API software for driver identification, requiring the regular submission of new photos. The company claims that the software is meant to ensure safety and security but faces criticism for difficulties in accurately recognizing people with darker skin tones. According to Professor Toby Breckon from Durham University, facial recognition software is designed for well-lit photos, leading to better recognition of lighter skin tones even in poorly lit environments. In 2022, the court rejected Uber’s attempt to dismiss a facial recognition discrimination claim.
This episode highlights the potential biases and harms associated with AI algorithms. It serves as a reminder to address and prevent future discrimination in AI systems.
Data privacy implications and Uber
On the horizon, there is a further Uber development that deserves attention. In Q2 2023, Uber filed for a patent on AI technology that, through pre-request matching, would predict customer habits. This would help Uber predict when users need a ride or meal delivered based on motion sensors in the smartphones, app usage, and profile data. This information allows the app to anticipate customer preferences and better match the driver with them, thus personalizing each request.
While this development has the potential to benefit the platform, it also raises concerns about data privacy. The algorithm relies on user profiles, including usage history and location data, which raises several ethical implications. The commercial applications of this technology should not be underestimated, but it is crucial to address privacy concerns, especially in the current context where data privacy is a significant topic of discussion.
