In contemporary service-delivery markets, an often-undisclosed relationship between data and profit stimulates the commodification of employment data. Analysing how such data is used reveals patterns of monetisation through a host of different market purposes – from potentially useful (predicting traffic conditions) to individually worrying (predictive personalisation). Data production and commercialisation imperatives drive digital platforms to extract secondary data while maintaining an information access imbalance between those with big data and data analytics capabilities, and the uninformed data product. This article speculates about regulatory options available for workers on these platform economies. To date, much focus has been dedicated to the possibilities of data regulation and reformulating labour law to address the challenges posed by the gig economy and platform capitalism. We chart an alternative path towards grassroots empowerment of participatory self-regulation, guaranteed through data discovery, AI-assisted information looping and vulnerable stakeholder emancipation. We argue that the essential condition of this self-regulatory frame for its social and market sustainability requires informed engagement by currently disempowered market players, with the consequence of market power dispersal in favour of a more balanced regulatory field. A unique feature of our proposed regulatory framework is the use of AI-assisted information looping to disrupt the current information imperialism of platform operations and their data customers, revealing the forces at work which now undermine worker dignity, and retard work life quality through surveillance.