Working together and sharing information can enhance efficiency and uncover untapped opportunities, allowing for the full potential of data-sharing to be realised. However, data is often kept isolated and restricted in order to prevent it from being compromised and to comply with various regulations. Professionals will share their experiences on how they have improved collaboration both within their organisations and with external partners, the challenges they have faced and how they have overcome them, and the potential for partnerships created by PETs.

Synthetic data technology is becoming increasingly popular among companies. It allows them to create new products and services and refine existing ones in a safe and cost-effective way. The synthetic data landscape is constantly evolving, and it is essential for companies to build AI toolboxes they can trust.  However, there is considerable tension regarding generative AI, and regulated enterprises need to ensure that their AI toolbox can be audited, understood, and explained.

Synthetic data can play an important role in achieving an efficient toolbox. It offers a safe and cost-effective way to test and refine products and services by generating data that mirrors real-world scenarios.  With applications ranging from mitigating data-sharing risks to improving real-world data quality, synthetic data is a powerful tool for enterprises looking to stay ahead of the curve. 

• Health Sector
• Financial Sector
• Data Governance
• Legal Requirements

Privacy Enhancing Tech offers a secure way to use data, promising to unlock new use-cases. However, uncertainty around the legal status of data processed by PETs might impact their adoption. This session will explore the legal implications of using Privacy Enhancing Technology and how they impact key privacy principles such as: transparency, anonymisation, data transfers, etc.

In the modern world of data privacy regulations, it is no longer possible to join data sets collected from different sources for different purposes without a lawful basis such as explicit consent. This session will introduce the latest innovations in data collaboration, clean rooms and enablement strategies that leverage privacy-enhancing technologies to fast-track analytics programs.

There is brewing curiosity about how advertising manages to break through the third-party problem despite privacy concerns. Discuss the significant risks that signal loss poses for both advertisers and publishers if ads cannot be shown on platforms. Explore how technology takes precedence over privacy concerns when new parties join conversations about advertising partnerships, even within large marketplaces like Magnite. Is the key to breaking through the third-party problem lie in a high enough financial incentive? 

This panel discusses the importance of having all stakeholders on board, from legal compliance to security teams, to ensure the effective implementation of privacy-enhancing technologies. There must be an acknowledgement that technology obstacles are common in two-sided marketplaces, where one party may be more familiar with the technology involved than others, causing pilot projects to fail at early stages. In order to solve these problems, there needs to be a focus shift from technology implementation to enabling value across different functions. Learn more about the organisational hurdles for implementing PETs and how cross-functional collaboration can overcome them.

As data becomes more valuable, it's important for data scientists to leverage privacy-enhancing technologies (PETs) while ensuring the integrity of their results through appropriate legal and governance frameworks, including audits. However, it's also crucial for PETs to be made more accessible to non-technical users. To make PETs work effectively, all players, from legal compliance to security teams, must come together. It's also important to focus less on technology and more on enabling value across different functions.

While the digitisation of information continues to grow, organisations must be strategic about preserving privacy. Regulations, governance, and policies are all at the forefront of standardising data collaboration practices. While they may differ by nation, industry, or even project type or scope, data-driven enterprise customers understand the importance of these standards. To stay on top of developments in the PETs landscape, it's important for data-driven enterprises to understand how it has changed, how it will evolve, and what the top priorities should be.