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One of the biggest problems in the data economy is that individuals and communities that produce the data which fuels the economy are unable to draw sufficient value from their own resources, labour, and identity. Instead, they are trapped in inconvenient and often exploitative relationships with technology platforms and the government. Individuals and communities are often forced to part with personal data which is sold and traded for the financial benefit of a few. 

Community control through data stewards

This growing commodification of data and related exploitation by tech platforms has given rise to new data intermediaries that are working on two foundational premises. First, it is imperative to think individuals and communities have rights over the value generated by data. Second, people need to be empowered to control their data better so that they can benefit from data value. Based on these assertions, several businesses that create the infrastructure for people to control, manage and monetise their personal data have popped up. These are intermediaries between data collectors, the user, and data buyers. Enterprises such as Digi.me play this intermediary role and make it possible for users to aggregate their data from different sources and share data with businesses and governments in return for better services, more convenience, personalised experiences and monetisation. Similarly, Datacoup allows individuals, based on personal preferences and a blockchain-enabled app, to earn cash, discounts, and cryptocurrency in exchange for their data. Streamr, an ecosystem enabler, helps enterprises create data unions that allow people to anonymise, pool and share their data in return for periodic payouts. These intermediaries, or data stewards, are able to return value back to the users, and make data more accessible for use by businesses, governments for both public and private value creation. Data value is distilled to financial returns as other values from data – personal, public – are hard to quantify. 

The social value of data, and incentives to monetise it

The frameworks of data ownership and monetisation that anchor this approach need further thinking. The question of data value is especially complex as data holds an element of social value, where individual data can be used to understand the behaviours of groups and vice versa. Further, value cannot be distilled solely into monetary value as done by many of the models – the value may be public, community-centred, or personal, and adding commercials to it might lead to perverse incentives for both the users who may forgo their data rights in turn for money, and for intermediaries who will be able to side-step user and community interests to further their own, for a small price. There is a related, and valid concern that vulnerable groups may be more willing to share their data given the monetary benefits, and compromise their privacy in an already exploitative data economy. Given that data value is entirely subjective, it is also likely that the information of certain groups and individuals is likely to be compensated for more than others such individuals or communities more likely to spend on e-commerce platforms. Given these complications, it is naive to assume that especially individuals but also groups, have the space to make rational, privacy-preserving decisions with regard to their data. It is also unfair to burden users with these decisions, as data should be viewed through the prism of rights and not compensation. 

This is not to say that data intermediaries are not required – they are especially important to give greater agency to individuals and communities and ensure that the rights of privacy and data protection are safeguarded. The role of the intermediary, however, cannot be limited to merely facilitate data access in return for monetisation and must be focused on collective bargaining and negotiating on data rights. Data intermediaries must provide alternative governance mechanisms that allow users greater decision-making on how their data is being used, and for what purposes, they should ensure greater transparency and accountability, and not just serve as a technical gateway for the further commodification of personal data. 

Need for sustainability, scale, and the role of membership

There are, however, certain concerns about the sustainability of data intermediaries that seek to empower individuals and communities, as data monetisation can be an effective mechanism to fund the efforts of an intermediary. This opens up a critical question on ethical revenue models of data intermediaries and how governance mechanisms can be structured to always be anchored in data rights. In an ideal scenario, and this is possible over the next 5-8 years, data intermediaries are entirely driven by membership where users, recognising the benefits of an intermediary’s services, pay a membership fee and in return receive assistance and advisory services on navigating the data economy better. Data cooperatives like Driver’s Seat, MiData are especially primed for this model. In this scenario, in the case of monetisation, the intermediary will not be a part of the transaction and be able to negotiate in the users’ best interests. However, scale is critical for membership-based models to be viable, which is currently a struggle. The role of intermediaries is still fairly new, and their contribution is not well-understood, therefore, in the short term, intermediaries may have to go down the monetisation route to sustain their functioning. However, all data related transactions must be transparent to and approved by the members/user. Mechanisms for granular consent, accountability, data minimisation etc must exist such that user well-being is prioritised irrespective of the value of transactions. Further, the role of the intermediaries must be redefined to ensure that safeguarding user interests is made a primary purpose and not just data commercialisation. 

Conclusion

Fundamentally, in the current debates, data empowerment is wrongly equated with data monetisation, to give people the power over their data cannot mean to give them the infrastructure to sell their data. Data empowerment means methods of actualising data rights, exercising greater agency, ensure transparency and accountability, and making sure that user data is not being extracted for the profits of a few while exploiting and manipulating user behaviour. The monetisation of data can be a part of this journey to data rights, a way to ensure the sustainability of models that help challenge and renegotiate power dynamics in the data economy but it cannot be an end in itself.