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Issue #1 | Summer 2022

Data Pools

Data pools are datasets that are either self-generated by AI or come from internal or external sources. A distinction is made between open and closed data pools. In the case of open data pools, several compa- nies share access to the data after agreeing on specific framework conditions regarding the use and customization of the pool. Closed data pools are data sets to which only one company has access. These data pools are advantageous in that companies don’t have to share competitive advantages as- sociated with certain data with their competitors.

From the perspective of economic sustainability, closed data pools are a delicate issue. They lead to so- called lock-in effects – which means that users are bound to a specific product or its provider in ways that make it difficult for them to switch to other products or providers due to unavoidable barriers such as high switching costs. They can also result in increased market concentration and even monopolies. The innovative strength of the market suffers as a result, and market diversity is severely constrained as single, large companies disproportionately benefit from AI. At the same time, though, closed data pools and thecompetitive advantages they provide incentivize companies to engage in practices that distort competition when obtaining data.