Forget Data Ethics — The Real Battle Is Over Who Owns the Infrastructure

Forget Data Ethics — The Real Battle Is Over Who Owns the Infrastructure

Estimated reading time: 6-7 minutes

• The struggle for power in the digital age is fundamentally about who controls the underlying infrastructure that generates, stores, and processes data, not just how data is used ethically.
• “Data Idealism,” which focuses on transparency and ethical alignment, is critiqued as structurally blind. “Data Realism” offers a corrective by shifting focus to infrastructural ownership, standardization leverage, and strategic capacity.
• Data Realism is built on five core tenets, emphasizing data as an interface to reality, a critical resource shaped by physical systems, a provisional contact with objective truth, a driver of agency, and requiring pragmatic ethics.
• Achieving data sovereignty requires concrete action: investing in sovereign data infrastructure and standards, reforming data access laws for public good, and integrating data strategy with national security and economic policy.
• Digital resilience and sovereignty are paramount to safeguard economies and societies against external regulatory whims or political pressures, making the control of digital infrastructure a foundational contest.

• From Idealism to Realism: The Five Tenets of Data Power
  • 1) The world exists and data are our only contact with it.
  • 2) Data exist with the world.
  • 3) The world leaks through.
  • 4) Data drive agency in the world.
  • 5) Navigating the world with data requires pragmatism.
• The Actionable Path to Data Sovereignty
  • Three Key Actionable Steps:
• Conclusion: The Imperative of Digital Resilience
• FAQ: Understanding Data Realism

In the rapidly evolving digital landscape, conversations around data governance frequently revolve around privacy, algorithmic bias, and ethical guidelines for artificial intelligence. While these discussions are vital, they often operate within a framework that overlooks a more fundamental truth: the struggle for power in the digital age is not merely about how data is used, but who controls the underlying infrastructure that generates, stores, and processes it.

The prevailing discourse, often characterized as “Data Idealism,” suggests that with sufficient transparency, fairness, and ethical alignment, the complex social, political, and economic challenges of our digital era can be effectively managed. However, this perspective, though well-intentioned, may be inherently flawed. It risks blinding us to the concrete realities of who holds the reins of digital power.

“The contemporary discourse on data governance has been compromised by Data Idealism which approaches data as primarily a social and techno-legal artifact. There are variations of data idealism, such as data ethics, “Free Flow with Trust”, data decolonisation, data feminism, ethical AI development and others which basically suggest that much of the social, political, and economic consequences of our digital age can be managed through the mechanisms of transparency, fairness, and ethical alignment. This is a case of structural blindness. Here, I propose Data Realism as a necessary corrective, requiring a shift in focus from the ideas of computational equity to the more concrete realities of infrastructural ownership, standardization leverage, and strategic capacity to manage this non-fungible asset. This requires recognising the following Five key tenets of Data Realism:”

From Idealism to Realism: The Five Tenets of Data Power

Data Realism offers a robust framework for understanding and navigating the complexities of our data-driven world. It compels us to move beyond abstract moral arguments and confront the tangible mechanisms of control. Here are its five core tenets:

1) The world exists and data are our only contact with it.

Data is our interface to reality, imperfect yet indispensable. Data Realism demands broad, cost-effective access to data, advocating for data commons and clear legal frameworks for collecting publicly available information. This fosters competition in AI development by shifting focus from proprietary data hoarding to innovation in modeling and application. It also calls for investment in curated, public datasets to lower barriers for startups and for regulatory policies to mandate data sharing from natural monopolies, ensuring a holistic capture of reality.

2) Data exist with the world.

Data is not an abstraction but a critical resource, shaped by physical systems, power structures, and leaving significant ecological and geopolitical footprints. Its production is inherently “infrastructured.” Data Idealism, by focusing solely on ethics, often implicitly accepts the dominance of existing hegemons. A Data Realist state, conversely, must prioritize sovereign technical standards, link digital industrial geographies to national security, and strategically integrate global technological developments into its long-term calculus, recognizing that the digital society has its own “data powers” and “data provinces.”

3) The world leaks through.

Data Realism rejects both the blind faith of Naive Empiricism (data speaks for itself) and the nihilism of Radical Constructivism (data is purely power-laden construct). It asserts that even through context and ideology, the world’s objective reality—like a temperature reading or a mortality rate—constrains us. To take data seriously means acknowledging it as provisional contact with reality, demanding rigorous scrutiny of the data used in our systems and a commitment to hard facts, even inconvenient ones. Manipulation of data, after all, presupposes a baseline truth that can be distorted.

4) Data drive agency in the world.

A state’s true data capacity is measured not by the volume of data, but by its independent ability to standardize, store, and compute that data without external reliance. This necessitates a systemic integration of military, academic, and industrial objectives, treating digital technical standards as strategic global public goods. National security, often unacknowledged in idealistic debates, is the primary driver of state-level data governance. The goal is to gain leverage to shape the rules of the game, not merely comply with existing frameworks or eliminate dependency through isolation.

5) Navigating the world with data requires pragmatism.

Data Realism champions practical ethics, emphasizing transparency in data collection, cleaning, modeling, and interpretation for those affected by resulting decisions. Beyond a right to audit, data stewards bear the responsibility of protecting and de-risking their data, understanding that data ownership is intertwined with the “ownership of Truth.” Governance’s primary task is to master the structural facts of computation, ownership, and capability. Treating data like an asset with depreciation or appreciation, as accountants do, can incentivize continuous updates and responsible lifecycle management, reducing long-term technical debt.

The Actionable Path to Data Sovereignty

Translating Data Realism into concrete policy requires a strategic and often bold departure from conventional approaches. It demands foresight and a willingness to confront entrenched power structures.

Three Key Actionable Steps:

1. Invest in Sovereign Data Infrastructure & Standards: Nations and leading industries must significantly ramp up investment in building domestic and regional data infrastructure—from secure cloud facilities to advanced data centers. Developing open-source technical and management standards, alongside fostering public-private partnerships for national data commons, is crucial. This strengthens independent data processing capabilities and reduces strategic reliance on foreign providers and frameworks.

2. Reform Data Access Laws for Public Good & Innovation: Policymakers should champion legislation that legalizes the responsible collection of publicly available data, setting clear technical standards for scraping (e.g., rate limits, anonymisation). Simultaneously, incentives should be created for voluntary contribution of high-quality, anonymised datasets to open-source commons, and regulatory policy must mandate data sharing or standardized APIs for public-interest data held by natural monopolies. This fosters a competitive AI ecosystem where innovation, not proprietary data hoarding, is the differentiator.

3. Integrate Data Strategy with National Security & Economic Policy: Governments must recognize data as a strategic national asset, explicitly linking digital industrial geographies to broader national security objectives. All data policies should undergo a rigorous assessment: Does this policy tangibly increase sovereign capacity and reduce structural dependency, or does it merely achieve moral compliance? This shifts states from a “judicial-police” role to a “structural” one, actively building digital capabilities and influencing meta-policy spaces.

Real-World Example: While many global forums debate ethical AI guidelines, the European Union’s Gaia-X initiative offers a tangible illustration of Data Realism in action. Instead of solely relying on ethical appeals to tech giants, Gaia-X focuses on building a federated, open-source data infrastructure designed to give European businesses and governments control over their data, reducing reliance on non-European cloud providers. This isn’t just about ‘trust’; it’s about owning the digital rails and asserting a concrete reality of control.

Conclusion: The Imperative of Digital Resilience

Embracing Data Realism means adopting a philosophy of effective technological acceleration grounded in practical ethics. It calls for a pragmatic approach that directly confronts the measurable facts of computation, ownership, and capability, rather than projecting idealized notions onto data pipelines. As AI and automated systems become increasingly integral to human affairs, recognizing that data ownership implies a profound responsibility—a custody of truth—is paramount. This includes continuous assessment for data depreciation and appreciation, aligning financial incentives with robust data governance.

In a world characterized by geopolitical flux, relying on external, proprietary, or geographically constrained data sources creates significant systemic vulnerabilities. The mandate for states, businesses, and organizations is clear: transition strategically towards data resilience, reliability, and sovereignty. This ensures the uninterrupted operational continuity of our digital lives and economies, safeguarding them against external regulatory whims or political pressures. The true contest for digital mastery isn’t abstract; it’s a foundational struggle over who owns the infrastructure.

FAQ: Understanding Data Realism

Q: What is “Data Idealism” and why is it considered flawed?

A: Data Idealism is a perspective that suggests the complex challenges of our digital age can be managed primarily through mechanisms like transparency, fairness, and ethical alignment in data use. The article argues it’s flawed because it creates a “structural blindness,” overlooking the more fundamental issue of who controls the underlying data infrastructure rather than just how data is used.

Q: What is “Data Realism”?

A: Data Realism is a framework proposed as a corrective to Data Idealism. It shifts focus from abstract notions of computational equity to the concrete realities of infrastructural ownership, standardization leverage, and strategic capacity to manage data. It recognizes data as a non-fungible asset intertwined with physical systems and power structures.

Q: What are the five core tenets of Data Realism?

A: The five core tenets are:

1. Data is our primary, albeit imperfect, contact with the world.
2. Data exists with the world as a critical resource shaped by physical systems and power structures.
3. The world leaks through data, meaning objective reality constrains us even through context.
4. Data drives agency in the world, with a state’s true capacity measured by independent control over data standardization, storage, and computation.
5. Navigating the world with data requires pragmatism and practical ethics, treating data like an asset with a lifecycle to manage depreciation and appreciation.

Q: How can nations achieve “Data Sovereignty”?

A: Nations can achieve Data Sovereignty through three key actionable steps: 1) significantly investing in sovereign data infrastructure and open-source standards; 2) reforming data access laws to promote public good and innovation (e.g., legalizing responsible data collection, mandating data sharing from monopolies); and 3) integrating data strategy explicitly with national security and economic policy to increase sovereign capacity and reduce structural dependency.

Q: Why is controlling data infrastructure more important than just focusing on data ethics?

A: While data ethics are crucial, focusing solely on them without addressing infrastructure ownership creates “structural blindness.” The article posits that the true battle for digital power lies in controlling the *foundational infrastructure* that generates, stores, and processes data. This control dictates a nation’s or organization’s strategic capacity, resilience against external pressures, and its ability to shape the rules and norms of the digital age, ensuring uninterrupted operational continuity and safeguarding economies.