DeepAI AI Chat
Log In Sign Up

Towards Data Auctions with Externalities

by   Anish Agarwal, et al.

The design of data markets has gained in importance as firms increasingly use predictions from machine learning models to make their operations more effective, yet need to externally acquire the necessary training data to fit such models. A property of such markets that has been given limited consideration thus far is the externality faced by a firm when data is allocated to other, competing firms. Addressing this is likely necessary for progress towards the practical implementation of such markets. In this work, we consider the case with n competing firms and a monopolistic data seller. We demonstrate that modeling the utility of firms solely through the increase in prediction accuracy experienced reduces the complex, combinatorial problem of allocating and pricing multiple data sets to an auction of a single digital (freely replicable) good. Crucially, this is what enables us to model the negative externalities experienced by a firm resulting from other firms' allocations. We obtain forms of the welfare-maximizing and revenue-maximizing auctions for such settings. We highlight how the form of the firms' private information – whether they know the externalities they exert on others or that others exert on them – affects the structure of the optimal mechanisms. We find that in all cases, the optimal allocation rules turn out to be single thresholds (one per firm), in which the seller allocates all information or none of it to a firm. We note the framework and results introduced hold more broadly for the auction of digital goods with externalities.


page 1

page 2

page 3

page 4


Revenue Maximizing Markets for Zero-Day Exploits

Markets for zero-day exploits (software vulnerabilities unknown to the v...

Learning Optimal Deterministic Auctions with Correlated Valuation Distributions

In mechanism design, it is challenging to design the optimal auction wit...

Double Auctions with Two-sided Bandit Feedback

Double Auction enables decentralized transfer of goods between multiple ...

Neural Auctions Compromise Bidder Information

Single-shot auctions are commonly used as a means to sell goods, for exa...

On Approximate Welfare- and Revenue-Maximizing Equilibria for Size-Interchangeable Bidders

In a Walrasian equilibrium (WE), all bidders are envy-free (EF), meaning...

Differentiable Economics for Randomized Affine Maximizer Auctions

A recent approach to automated mechanism design, differentiable economic...

Selling Information in Competitive Environments

We consider a setting where data buyers compete in a game of incomplete ...