Freelancing platforms have gained tremendous popularity, connecting millions of employers and freelancers worldwide. We examine whether profile pictures on such platforms may facilitate hiring biases based on appearance-based perceptions of a freelancer's fit for the job (e.g., whether the applicant looks like a programmer). We collect data from Freelancer.com for all jobs posted between January-June 2018 that ended in a contract, resulting in 79,038 jobs with 2,462,043 applications from 220,385 freelancers. Leveraging computer vision techniques, we find that freelancers with pictures perceived as high fit (or who ''look the part'') are more likely to be hired. More importantly, we show that such a bias goes above and beyond known prejudice variables such as demographics and attractiveness. Interestingly, we discover that ''looking the part'' complements rather than substitutes online reputation. We further conduct two experiments to explore the underlying mechanisms behind these findings. We find that when the reputation system is extremely positive, as in most freelancing platforms, employers use profile pictures as tiebreakers to choose among similar applicants. We also show that freelancers, especially those who ''do not look the part,'' may mitigate such biases by strategically selecting backgrounds and accessories in their profile pictures to enhance their chances of being hired.
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