Data intermediaries represent a new policy lever to navigate the challenges of the growing data ecosystem.
Everyone is familiar with the paradigm of going online and clicking on terms and conditions they don’t understand (or take time to read). No one
knows (nor follows) what happens to their data.
This status quo creates a reliance on companies to be responsible but can lead to mistrust in the data
ecosystem as a whole. Further, mistrust between people and technology becomes amplified the
more complex the data ecosystem becomes over time. Where once people had screens to navigate,
new ambient data collection methods with their many benefits create nervousness and resignation
when people don’t have the full picture. In some cases, individuals may opt out of interacting with technologies that would be of huge benefit to their
lives. But what if it were possible to outsource these decision points to a trusted agent acting on an
individual’s or even a group’s behalf?
Now that screenless technology is a part of everyday life, there is an opportunity to rethink the human–
technology interaction paradigm and reposition the debate to focus on roles and responsibilities beyond the person. How can the use of data
intermediaries help people navigate technologies and data ecosystem models without losing sight of
what it means to be human, in terms of agency and expectations? How can people think beyond that
given that, as they move towards the complexity of screenless metaverse issues, their understanding of
“humanness” is transforming? Data intermediaries– especially digital agents – represent a new policy
lever through and around which individuals can potentially navigate the challenges of the growing
data ecosystem. This report seeks to shed light on an alternative method of mediated human–technology interaction whereby data appears to
travel seamlessly from people to technology in a human-centric and, crucially, trusted manner. By
communicating shared incentives, establishing reputation or receiving third-party verification, as
well as having assurance structures to mitigate risk to both the intermediary and the rights holders, data intermediaries can increase trust between people and the technology they interact with.
This report explores the opportunities and risks of data intermediaries and, specifically, third-party digital
agents. From data trusts to trusted digital agency, the report paints a picture of a world that is more
empathetic to people and to companies, providing greater certainty for data sharing as a foundation for
innovation through the introduction of a trusted third party. Crucially, it suggests levers of action for both the public and private sector to ensure a futureproof digital policy environment that allows for the seamless and trusted movement of data between people and the technology that serves them.
Our days are filled with myriad discrete data collection moments. Even when we have genuine intent to affirmatively consent to each moment of data collection, it is practically impossible to do so: No individual has the time to provide affirmative consent on a near constant basis. This reality arguably undermines our individual agency.”
2 The world is experiencing something of a mistrust pandemic when it comes to people’s engagement with the data ecosystem. This global “trust gap” or “trust deficit” is a barrier to economic growth, digital innovation and social cohesion. The technology ecosystem is ultimately powered by the collection, sharing and processing of data, often personal in nature. Data sharing is a driver of innovation in technology and of the digitization of mature economic models. But trust between parties who seek to share or exchange data is not a default state; it is something that needs to be earned or built, often as a result of great effort over time. This includes building trust between people and technology. It is all the more important when considering that people share data every time they interact with the technologies in their lives. As Bill McDermott, former Chief Executive Officer of SAP, has noted: “When trust is there, we can take giant strides, turning our greatest challenges into our biggest opportunities. When it’s not, the needle gets stuck. Small hurdles become insurmountable. Division overwhelms unity.”3 As defined by Russell Hardin,4 trust is a belief that an actor will perform a specific action within a specific context, whereas trustworthiness is a property of an actor. The goal of data intermediaries and the infrastructure that supports them is to enable data rights holders to trust trustworthy data intermediaries. That is not to say that without trust and trustworthiness there is no sharing of data; but with trust and trustworthiness there will be greater participation and in turn an increase in the volume and indeed the veracity of data made available as a result.