Querying with Conflicts of Interest

Conflicts of interest often arise between data sources and their users regarding how the users’ information needs should be interpreted by the data source. For example, an online product search might be biased towards presenting certain products higher in its list of results to improve its revenue, which may not follow the user’s desired ranking expressed in their query. The research community has proposed schemes for data sources to implement to ensure unbiased results. However, data sources usually have little or no incentive to implement these measures, e.g., their biases often increase their profits. Thus, we propose a novel framework for querying in settings where the data source has incentives to return biased answers intentionally due to the conflict of interest between the user and the data source. We propose efficient algorithms that reformulate input queries to increase the amount of relevant information in the returned results over biased data sources. We also propose methods to detect biased information in the results of a query efficiently