Chapter six examines how ridesharing companies confronted public safety concerns that became inseparable from their business models. As platforms scaled rapidly, traditional regulatory categories failed to address insurance coverage, background checks, and accountability.

The chapter traces how firms developed comprehensive safety frameworks that included standardized insurance rules, continuous monitoring, and public reporting. These systems were not voluntary add-ons. They were necessary to sustain operations across jurisdictions with conflicting expectations.

The case study shows how companies engaged in rule formation through consultation with insurers, regulators, and advocates. Executive decision-making was disciplined through disclosure of safety data. Monitoring systems tracked incidents and enabled adjustment.

The chapter demonstrates how these private governance systems later shaped public law. States adopted insurance frameworks and reporting requirements modeled on corporate practices.

This chapter illustrates corporate ordering at work in a domain where business viability and public safety could not be separated. It shows both the potential and limits of private governance and highlights the conditions under which corporate ordering can support legitimate regulatory outcomes.

When companies like Uber and TaskRabbit appeared in Silicon Valley, there was a collective media swoon over these new app-based service-delivery corporations and their products. Pundits and journalists made it seem like these companies were ushering in not only an inevitable future, but a desirable one. Their content helped convince the public and regulators that these businesses were different from existing corporations – that they were startups with innovative technology platforms designed to disrupt established firms by efficiently connecting consumers to independent, empowered gig workers. Those in the media normalized and at times generated this rhetoric and framing, which was then taken up by politicians, amplified by academics, and finally enshrined in laws that legalized the business models of these companies. The positive, uncritical coverage prevailed for years and helped pave the way for a handful of companies that represent a tiny fraction of the economy to have an outsized impact on law, mainstream corporate practices, and the way we think about work. The force that powered the swoon was a relatively new and journalistically problematic trend in media: “tech” reporting.

This chapter first provides a framework for understanding recent local government approaches to aligning Uber and Lyft operations with urban transportation policy goals—including improving street safety, improving transportation access, and reducing greenhouse gas emissions. Many of these approaches to setting policy and designing streets are not regulatory per se, though they can and have been used as de facto regulatory strategies. This “implicit” regulatory approach has arisen in part because most local governments in the U.S. lack the formal authority to regulate Uber and Lyft. Furthermore, most local governments also lack the data necessary to develop and/or enforce appropriate regulations of the app-enabled for-hire vehicle industry.

The chapter continues with a case study of how the San Francisco County Transportation Authority, in partnership with researchers at Northeastern University, developed a creative and partnership-driven approach to policy-making in the face of a severe data deficit. Agency staff and University researchers scraped data from the Uber and Lyft application programming interfaces and used those data to better understand how people move in San Francisco County. This work demonstrates the importance of innovative, goal-oriented problem-solving approaches to inform the regulation of increasingly complex city streets.