Dear Waze,
I appreciate how Waze has improved real-time navigation, but it seems to be designed for experienced urban drivers who prioritize speed and can easily handle notifications. This may exclude and endanger those with different driving abilities and priorities. In this email, I outline four key design issues and suggest solutions to make Waze more inclusive. My observations come from personal experience with the platform and relevant academic research.
Firstly, Waze selects the fastest route automatically but doesn’t factor in risks like high crime areas, poorly lit areas, or dangerous road conditions. This has had real consequences, like in 2015, when Regina Murmura was led into a dangerous favela in Brazil and killed by local gang members. Since then, Waze has introduced high-risk area alerts in Brazil and Israel. However, most users still lack this feature, placing vulnerable drivers, such as older adults, new drivers, tourists, gig workers, and women, at higher risk. Winner (1980) argues that technology is not neutral, as its design choices reflect social values and may have political outcomes. Waze’s algorithm appears neutral, but because it prioritizes speed over safety, it favors confident, experienced drivers while putting others at risk. This is not a technical limitation but a design choice that reinforces inequality. To avoid this, Waze should supplement its algorithm with official safety data (e.g., crime reports and lighting conditions) and provide a "Safety first" routing option, guaranteeing that every user has equal access to a safe driving experience.
Secondly, because Waze relies heavily on user reports, it assumes roads without reports are safe. However, this results in a geographical bias because hazard notifications are less frequent in places with fewer active users, such as rural communities, low-income neighborhoods, or roads during off-peak hours. For instance, rural drivers in areas with few Waze users and gig workers driving late at night may miss important hazard alerts, making navigation less reliable and possibly dangerous. Kitchin (2014) critiques the rise of data-driven science. Arguing that big data does not provide an objective reality but an "Oligoptic view," a partial view shaped by who collects data and where. In this case, Waze assumes that missing reports indicate evidence of safety rather than a lack of participation. Kitchin contends that theory should supplement data-driven science to prevent flawed conclusions. Similarly, Waze should not only rely on crowdsourced reports and road traffic data but add official safety data (e.g., police crime reports and municipal road conditions) to ensure that missing data does not create blind spots to navigation safety.
Thirdly, Waze has two main issues when handling hazards: it doesn’t immediately reroute drivers when conditions are risky and depends on user reports rather than accurate weather data. While users can manually report dangers like ice, snow, or flooding, these warnings don't adjust the routes, which puts drivers at risk. This affects everyone in extreme weather conditions, but gig workers and low-income are disproportionately affected since they may not have access to proper winter gear. I experienced this firsthand after a snowstorm in Montreal when I took an Uber; despite dangerous conditions, we were systematically routed onto unplowed streets rather than safer main roads. Morozov (2013) critiques “solutionism,” the tendency of tech companies to define problems too narrowly and neglecting broader complexities. This is exemplified by Waze, which disregards social, economic, and environmental issues in favor of the fastest route. Morozov warns against one-size-fits-all, Western-centered technological solutions that may not apply across all contexts. By supplementing its user reports with real-time weather data and municipal road conditions, Waze would ensure that users are actively relocated when necessary.
Finally, Waze can be more distracting than helpful due to its game-like features and constant notifications. As the app offers leaderboards, points, and badges for reporting risks it incentivizes users to remain engaged even while driving. Furthermore, its pop-up notifications must be manually dismissed, further distracting driving. This design choice unequally affects new drivers, who need to focus on the road; neurodivergent drivers (e.g., ADHD), who may be overwhelmed with many notifications; and older adults, who may struggle to process or remove alerts quickly. Zuboff (2019) critiques surveillance capitalism, arguing that platforms are designed not just to provide services but to profit from behavioral surplus (data beyond what is required to improve services). She argues that digital platforms are not neutral; they shape user behavior to serve corporate interests by manipulating user behavior to maximize engagement. This directly relates to Waze; by transforming a navigation tool into a game, it prioritizes data collection over user safety. Waze should implement a driver mode that restricts intrusive notifications and prioritizes voice-based safety alerts, maintaining the focus on the road rather than on the app.
In conclusion, Waze’s current design is too focused on speed and engagement. It provides incomplete safety data, which leaves vulnerable drivers, gig workers, low-income communities, and those in extreme weather conditions to face unsafe driving conditions. Waze should offer a safety-first routing option, add official data to supplement user reports and reduce nonessential app interactions. These changes will guarantee that navigation remains a tool for safety rather than just efficiency or engagement.
Best Regards,