About 20% of the U.S. unemployed population has been out of the labor force for more than 6 months. The rise of the gig economy has changed the landscape of nontraditional employment opportunities for these predominantly low-skilled long-term unemployed workers. This particular type of on-demand work can be used to fill unemployment gaps and offers little to no training costs and flexible hours. Therefore, we explore whether driving as a form of gig work helps to mitigate the negative effects of long-term unemployment for low-skilled job seekers with employment gaps, and how employers evaluate workers who have held non-traditional jobs. Using a correspondence audit study with 1006 job applications, we evaluated whether a set of resumes "enhanced" with experience driving for a real-time ridesharing service received more callbacks than baseline resumes with an employment gap. We found no evidence that driving as a form of gig work increased the callback rates of applicants. In fact, we observed that in comparison to men, the callback rates for women slightly declined. Our study suggests that driving 'gigs' might not be a substitute for traditional employment on resumes for low-skilled workers. We contribute a call to CSCW to investigate methods that help to understand why real-time ridesharing services do not substitute for traditional jobs in bridging employment gaps and solutions on how to overcome it. Finally, we reflect on our use of audit studies in the new digital era and present potential CSCW and HCI contributions using this method.

Real-time ridesharing services (e.g., Uber and Lyft) are often touted as sharing-economy leaders and dramatically lower the cost of transportation. However, how to make these services work better among low-income and transportation-scarce households, how these individuals experience these services, and whether they encounter barriers in enlisting these services is unknown. To address these questions, we onboarded 13 low-income individuals living in transportation-scarce environments to Uber as passengers. Our participants found these services to be reliable and benefited from rich social interactions with drivers; however, barriers such as cost, limited payment methods, and low digital literacy can make such services infeasible. We contribute platform designs that could lead to increased digital literacy and application transparency. To be more inclusive and to reach critical mass, we suggest that these companies foster belief in commons and community trust by coordinating with local businesses in low-resource areas with lower digital literacy.