DATA SHARING FOR TOMORROW: BALANCING COLLABORATION AND PRIVACY

As data sharing becomes increasingly vital for global collaboration, organisations face the challenge of balancing privacy and control. In this article, 2024 Innovation Challenge Data & AI category winners, Acentrik, explore how emerging technologies and regulatory frameworks are shaping a future where data can be shared securely without compromising ownership or privacy.

Data has become the lifeblood of modern economies, fueling innovation and driving growth across every
sector. According to the World Economic Forum, data access and sharing across borders could generate
social and economic benefits equivalent to as much as 2.5% of a nation's GDP1. The ability to share data,
particularly between the public and private sectors, has become essential for addressing global challenges, from enhancing service delivery during the COVID-19 pandemic2 to building smart, sustainable cities3.

Despite these clear advantages, data sharing – especially when multiple parties are involved – faces a
critical hurdle: data privacy. Both private organisations and governments are often hesitant to share data
due to fears of losing control, potential privacy violations, or the misuse of sensitive information. The absence of robust privacy measures in this equation prevents organisations from capitalising on shared data’s full potential.

Governments are leading the way with frameworks
Recognising the value of data sharing and the barriers posed by privacy concerns, governments worldwide are stepping in with frameworks and regulations designed to protect data privacy while enabling collaboration. Frameworks like the UK’s Data Protection Act and Singapore’s IMDA Trusted Data Sharing Framework provide organisations with clear guidelines to ensure responsible data sharing with strong focus on privacy and security. On a global scale, the European Union’s General Data Protection Regulation (GDPR) has become a gold standard for secure handling of personal data, influencing privacy practices worldwide.

These frameworks establish rules and principles that promote data privacy, transparency, and accountability when sharing information456. From a business perspective, adhering to these regulations may seem daunting. Yet, they are critical for ensuring that shared data is secure, verifiable, and ethically handled, which paves the way for safer, more efficient collaboration. As greater requirements of data to be shared across borders and sectors arise, a unified approach emphasising interoperability, access, and privacy is increasingly necessary. Governments have laid the groundwork by ensuring privacy and ownership of data are respected. This creates a foundation for a new approach to data sharing – one that allows organisations to retain control of their data while collaborating across both public and private sectors.

A new approach: sharing data without moving data
The next step for organisations is adopting a new way of data sharing that allows them to exchange insights without relocating raw data. Traditionally, data sharing involved transferring information to third parties for analysis, introducing risks such as privacy violations, security issues, and potential misuse. Emerging technologies are transforming this process, enabling secure collaboration while keeping data in its original location.

Instead of moving or copying data, algorithms are sent to the data source for analysis, eliminating many of the risks associated with traditional data sharing, as sensitive information never leaves its secure environment. This method empowers organisations to retain full control over their data while allowing others to securely access insights.

Additional benefits of this new way of sharing data
The key element of this approach is its ability to complement existing systems, enabling data interoperability. By connecting directly to diverse data sources, organisations can access and analyse data without exposing it, ensuring that data owners retain full ownership throughout the process. This is particularly beneficial for industries such as healthcare and government, where data protection and privacy regulations are crucial.

The capability to share insights without transferring raw data fosters greater confidence among organisations, knowing that their data remains private and secure, while the insights generated can drive better outcomes.

It also provides an innovative approach to leveraging AI - where data sharing is the foundation to getting the most out of AI development. AI thrives on access to large, diverse datasets from multiple sources, but data is often siloed – stored across different departments or regions – making it difficult to fully utilise. With this method, organisations can train AI models on siloed data across regions while keeping it at the source. This eliminates the need to consolidate data into a central location and adheres with privacy regulations.

The benefits of training AI models on diverse datasets are clear. Models developed this way yield more accurate and actionable insights because they are trained on a wider range of data. For example, governments and private organisations can collaborate to build smart cities by training predictive AI models on traffic patterns, energy consumption and population demographics for urban planning. This facilitates a symbiotic relationship: governments leverage private sector data to enhance public service delivery, while private companies gain opportunities to monetise their data. This ensures mutual benefits for both sectors.

This new approach is a game-changer for organisations looking to break down data silos and collaborate across regions and sectors without sacrificing security. For businesses and governments alike, adopting such methods ensures alignment with global privacy frameworks while facilitating data collaboration that drives economic growth.

As the need for responsible data management continues to grow, prioritizing privacy and security will become increasingly important. Acentrik, an Innovation Challenge winner, supports this by offering a SaaS whitelabel data exchange platform that enables organisations to create greater value from their data in a private and sovereign manner. It serves as a model for how technology can solve the privacy equation that both governments and businesses have been grappling with for years.

As data sharing continues to grow in importance, so too must the technologies that enable its secure exchange. While the foundational frameworks have been set, it is now up to governments, businesses, and technologies to ensure a future where data collaboration can thrive, safely and securely.

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