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Drivers on food delivery platforms often run a loss on low-paying orders. In response, workers on DoorDash started a campaign, #DeclineNow, to purposefully decline orders below a certain pay threshold. For each declined order, the platform…
Although freelancing work has grown substantially in recent years, in part facilitated by a number of online labor marketplaces, (e.g., Guru, Freelancer, Amazon Mechanical Turk), traditional forms of "in-sourcing" work continue being the…
This paper explores the economic interactions within modern crowdsourcing markets. In these markets, employers issue requests for tasks, platforms facilitate the recruitment of crowd workers, and workers complete tasks for monetary rewards.…
Crowdsourcing has become an important tool to collect data for various artificial intelligence applications and auction can be an effective way to allocate work and determine reward in a crowdsourcing platform. In this paper, we focus on…
Crowdsourcing is a form of "peer production" in which work traditionally performed by an employee is outsourced to an "undefined, generally large group of people in the form of an open call." We present a model of workers supplying labor to…
Digital workers on crowdsourcing platforms (e.g., Amazon Mechanical Turk, Appen, Clickworker, Prolific) play a crucial role in training and improving AI systems, yet they often face low pay, unfair conditions, and a lack of recognition for…
The rapid growth of the digital platform economy is transforming labor markets, offering new employment opportunities with promises of flexibility and accessibility. However, these benefits often come at the expense of increased economic…
We consider job scheduling settings, with multiple machines, where jobs arrive online and choose a machine selfishly so as to minimize their cost. Our objective is the classic makespan minimization objective, which corresponds to the…
Combinatorial Auctions are a central problem in Algorithmic Mechanism Design: pricing and allocating goods to buyers with complex preferences in order to maximize some desired objective (e.g., social welfare, revenue, or profit). The…
Gig economy consists of two market groups connected via an intermediary. Popular examples are rideshares where passengers and drivers are mediated via platforms such as Uber and Lyft. In a duopoly market, the platforms must compete to…
Crowdsourced on-demand services offer benefits such as reduced costs, faster service fulfillment times, greater adaptability, and contributions to sustainable urban transportation in on-demand delivery contexts. However, the success of an…
Ride-sourcing platforms such as Uber and Lyft are prime examples of the gig economy, recruiting drivers as independent contractors, thereby avoiding legal and fiscal obligations. Although platforms offer flexibility in choosing work shifts…
Generative AI has the potential to transform how firms produce output. Yet, credible evidence on how AI is actually substituting for human labor remains limited. In this paper, we study firm-level substitution between contracted online…
Crowdsourcing provides a popular paradigm for data collection at scale. We study the problem of selecting subsets of workers from a given worker pool to maximize the accuracy under a budget constraint. One natural question is whether we…
We study the problem of collaborative machine learning markets where multiple parties can achieve improved performance on their machine learning tasks by combining their training data. We discuss desired properties for these machine…
The problem of pricing the cloud has attracted much recent attention due to the widespread use of cloud computing and cloud services. From a theoretical perspective, several mechanisms that provide strong efficiency or fairness guarantees…
We initiate a principled study of algorithmic collective action on digital platforms that deploy machine learning algorithms. We propose a simple theoretical model of a collective interacting with a firm's learning algorithm. The collective…
We study online resource allocation in a cloud computing platform, through a posted pricing mechanism: The cloud provider publishes a unit price for each resource type, which may vary over time; upon arrival at the cloud system, a cloud…
While microtask crowdsourcing provides a new way to solve large volumes of small tasks at a much lower price compared with traditional in-house solutions, it suffers from quality problems due to the lack of incentives. On the other hand,…
In this paper, we propose three generic models of capacitated coverage and, more generally, submodular maximization to study task-worker assignment problems that arise in a wide range of gig economy platforms. Our models incorporate the…