Across the platform economy and the AI supply chain, workers generate enormous amounts of data simply by doing their jobs.
For ride-hailing drivers and delivery workers, this can include location, performance, ratings, identity verification and other forms of platform-generated data.
For data annotators, AI data workers and content moderators, the relationship can go even further: workers may contribute not only their labour, but aspects of their identities, bodies and environments as data.
Yet workers often have limited visibility into what information is collected about them, how it is used, how long it is retained, who it is shared with, or how it influences the systems that govern their work.
“What becomes possible when workers can see, understand and collectively examine the data systems that shape their working lives?”
Our current Nairobi pilot is helping us explore that question.
DSA is currently working with platform workers in Nairobi, including ride-hailing drivers, delivery riders, content moderators and data annotators/labellers. Through small-group data literacy sessions, community sensitisation, worker conversations and one-to-one guidance on Subject Access Requests (SARs), we are beginning to understand the practical challenges workers face when trying to exercise their data rights.
Data protection laws provide individuals with important rights over their personal information. But understanding those rights, knowing when they apply, identifying where to submit a request and navigating the process can be difficult.
The gap between having data rights in law and being able to exercise those rights in practice.
Digital labour platforms can generate extensive information about workers and their activity. At the same time, workers may know relatively little about what information exists about them, how particular decisions are made, or what role their data plays within automated management systems. Among AI data workers and content moderators, worker conversations have also raised concerns about highly personal forms of data collection.
These accounts help identify questions requiring deeper investigation; individual experiences should not automatically be treated as evidence about an entire company or industry.
A legal right can be difficult to use without accessible information and trusted support. Workers may need help understanding terminology, identifying the relevant organisation, deciding what information to request and understanding the response they eventually receive.
This is why DSA combines data literacy with practical guidance rather than treating awareness alone as the end goal.
A Subject Access Request begins as an individual exercise of a data protection right. But if multiple workers independently encounter similar practices, decisions or barriers, those experiences may begin to reveal broader patterns.
Can individual data rights become a pathway towards collective worker evidence?
Our research agenda is developing directly from the questions emerging through our work with workers.
What personal, behavioural, biometric, location, performance and work-related information is collected or generated during digital work?
How much information can workers realistically obtain about the data held about them, and what happens when they exercise rights such as Subject Access Requests?
What role does worker data play in ratings, account management, performance monitoring, automated decision-making and other systems that affect access to work?
Where do workers encounter difficulties—in awareness, language, technology, processes, institutional responses or understanding the information they eventually receive?
Can individual requests and worker experiences, when shared voluntarily and safely, help identify patterns that would otherwise remain invisible?
Can data protection tools complement existing labour organising, advocacy and accountability strategies rather than remaining purely individual legal rights?
Our emerging model connects three stages of work:
Workers first need to understand what personal data is, how digital systems collect it and what rights may be available to them.
Workers who choose to do so can explore mechanisms such as Subject Access Requests to seek information held about them.
With appropriate consent and safeguards, patterns emerging across individual experiences may help workers and their organisations identify broader questions about platform governance, data practices and digital working conditions.
“The objective is not to collect workers' personal data unnecessarily. It is to explore whether data already generated about workers can help workers better understand and challenge the systems governing their livelihoods.”
DSA's approach to research begins with workers rather than treating them simply as research subjects.
We begin with workers' experiences, questions and concerns.
We provide practical data literacy and guidance for workers who want to exercise their data rights.
We identify recurring questions, barriers and emerging themes while protecting individual privacy.
We examine whether individual experiences point towards wider patterns or research questions that require further investigation.
Where appropriate, learning can be translated into practical resources, research outputs, policy discussions and worker-led advocacy.
“The aim is not research about workers without workers. It is to develop evidence that workers themselves can understand, question and potentially use.”
Areas of ongoing investigation guided by worker discussions and pilot sessions.
Understanding what happens when platform and AI workers attempt to exercise their rights of access to personal information.
Documenting practical obstacles workers encounter before, during and after the SAR process.
Exploring what workers understand about the information collected or generated through platforms and how that information may affect their working lives.
Developing a clearer understanding of worker-reported experiences involving biometric, identity and other highly personal forms of data in AI-related work.
Testing whether independently documented worker experiences can safely contribute to broader evidence about digital labour systems.
Exploring what meaningful transparency, accountability and worker participation in decisions about workplace data could look like in practice.
DSA is an early-stage organisation, and our Nairobi work is an early-stage learning pilot.
We therefore make an important distinction between worker-reported experiences, emerging patterns and verified research findings.
We will not present a small number of worker experiences as representative of an entire workforce or industry.
Instead, our work is designed to identify important questions, document recurring experiences carefully and determine where more systematic investigation is needed.
“Credible research is not about having all the answers at the beginning. It is about asking important questions, building evidence carefully and being transparent about what the evidence can—and cannot—tell us.”
Workers should not have to surrender more personal information in order to challenge excessive data collection.
That principle shapes how DSA approaches research and learning.
Workers should understand why information is being collected and how it may be used.
We should collect only the information genuinely necessary for the purpose of the research.
Identifiable worker information should not be published unnecessarily.
Participation in research or collective evidence-building should be voluntary.
Individual accounts should not automatically be presented as evidence of industry-wide practices.
Wherever possible, research should produce knowledge that workers and worker organisations can actually use.
As our work develops, we aim to translate learning from the Nairobi pilot into accessible evidence and practical knowledge.
Future Research & Learning outputs may include:
Anonymised insights from worker data-rights experiences
Analysis of barriers to exercising data rights
These outputs will be published here as the evidence base develops.
The systems governing digital work are increasingly built around data.
Workers are measured through data, managed through data and, in some forms of AI work, may also contribute personal information that becomes part of the systems they help create.
But workers rarely have equivalent power to inspect, question or influence those systems.
“We want to understand whether workers can use data rights collectively to demand greater transparency, accountability and influence over the digital systems that govern their livelihoods.”
The Nairobi pilot is our starting point. The evidence we build from it will help determine what comes next.
We are interested in learning alongside workers, worker organisations, researchers, data protection practitioners, civil society organisations, regulators and institutions working on the future of digital labour.
We are particularly interested in collaborations that strengthen worker-centred research, improve our evidence base or help translate evidence into practical changes for workers.
Interested in collaborating on research or learning?
Get in touch