HKUST Business Review

Through this comprehensive analysis, we found that after BCLs were adopted, rideshare-related docket cases declined significantly. In other words, as expected, excluding higher-risk drivers is effective in preventing rideshare-related crimes. But at the same time, we found that property crimes in communities with new BCLs increased by approximately 6%, suggesting that displaced workers were pushed toward other offenses. Digging deeper, we found that not all background check laws had the same effect. In a follow-up analysis, we explored the impact of more and less strict BCLs, and we found that stricter laws— that is, regulations that excluded drivers for non- violent, non-recent offences such as identity theft, fraud, or evading police (even if these convictions were more than five years old)—led to worse outcomes than laws that only targeted recent, violent, or sexual crimes: These stricter BCLs did not reduce rideshare crimes any more than the less-strict laws did, but they significantly increased property crime rates. This analysis demonstrates that in addition to the direct social and financial harm they cause to people with criminal records, strict BCLs often increase overall crime rates without even improving outcomes for the passengers these laws are designed to protect. So, what will it take to effectively protect customers’ safety without excluding good workers and unintentionally increasing crime rates? Three Theories of Criminal Activity Designing better interventions starts with understanding why people commit crime. Criminology theory points to a range of drivers: First, Routine Activity Theory suggests that crime occurs when a potential offender is motivated, encounters a suitable target of crime, and that target is insufficiently protected. In other words, crime happens when a person’s routine activities enable and incentivize it. Next, Labeling Theory argues that stigmatizing people as “criminals” can reinforce cycles of exclusion and recidivism. Whether that’s a government regulation that forces people to disclose their criminal past or a voluntary organizational policy or social norm, the stigma of being labeled as a criminal can make repeat offenses all the more likely. And finally, Rational Choice Theory posits that people weigh the benefits and costs of crime versus legal work, and when legal options come up short (or feel altogether inaccessible), crime becomes the rational choice. Taken together, these theories shed light on why indiscriminate background checks may inadvertently fuel more crime than they prevent—and what other approaches might be more effective. Effective Deterrence Takes More Than Background Checks Specifically, these theories and our own research inform several strategies that platforms, communities, and governments can use to deter crime and protect communities (without some of the unintended consequences of BCLs). 1. Platforms Can Leverage Technology to Deter Crime For platforms, there are a range of tools that can help ensure passenger safety without excessively excluding drivers. For example, innovations such as license plate verification (in-app notifications reminding riders to check their car’s license plate before entry), real-time ride tracking (the ability to share trip status with trusted contacts), emergency button integration (instant 911 access with location data), and unusual stop detection (AI alerts for suspicious detours) all help boost rider safety without restricting drivers. Indeed, our study showed that when Uber rolled out these features, crime rates fell by up to 30%—a much larger effect than BCLs alone. Figure 2. Impact of In-App Panic Button Launch on Incident Reports New laws mandating background checks even for gig workers threaten to erode this vital benefit of the gig economy. Launch of panic button (Uber) in five States Insight 46 HKUST Business Review