Privacy and Artificial Intelligence - 2.6 Privacy-Enhancing Technologies (PETs)

2.6 Privacy-Enhancing Technologies (PETs)

Introduction

Privacy-enhancing technologies (PETs) are advanced tools and methods designed to protect personal information while still allowing organizations to use, analyze, and share data for valuable insights. These technologies help minimize the collection of sensitive data and ensure that only necessary information is processed, making it much harder for unauthorized parties to access or misuse personal details (OECD, 2025; Usercentrics, 2024). PETs are essential for building trust in artificial intelligence (AI) systems, enabling secure data collaboration, and meeting regulatory requirements for privacy and data protection (OECD, 2025; Syntho, 2024).

PETs include a wide range of techniques such as encryption, anonymization, pseudonymization, differential privacy, secure multi-party computation, federated learning, and trusted execution environments. Each of these methods addresses different privacy risks and can be combined for stronger protection. For example, a healthcare provider might use federated learning to train an AI model on patient data from multiple hospitals without ever sharing raw patient records. This approach allows valuable research while keeping personal information private (OECD, 2025; Finextra, 2024).

Technical or Conceptual Background

Privacy-enhancing technologies are designed to protect data at every stage of its lifecycle: during collection, storage, processing, and sharing. The goal is to ensure that sensitive information is either not collected in the first place or is transformed in a way that makes it difficult or impossible to identify individuals (OECD, 2025; Usercentrics, 2024).

Encryption is a foundational PET that scrambles data so it can only be read by someone with the correct key. This protects information both in transit and at rest, preventing unauthorized access even if the data is intercepted or stolen (Finextra, 2024; Syntho, 2024).

Anonymization and pseudonymization are techniques that remove or replace identifying information in datasets. Anonymization makes it impossible to link data back to individuals, while pseudonymization replaces identifiers with codes that can be reversed only with additional information (Finextra, 2024; ICO, 2024). These methods are widely used in research, analytics, and data sharing.

Differential privacy is a mathematical approach that adds controlled noise to data or query results, making it hard to determine whether a specific individual’s information is included in the dataset. This technique is especially useful for publishing aggregate statistics while protecting individual privacy (ISACA, 2024; OECD, 2025). For example, the US Census Bureau uses differential privacy to release population statistics without revealing details about individual citizens (ISACA, 2024).

Secure multi-party computation (SMPC) allows multiple parties to jointly compute a function over their inputs while keeping those inputs private. This means organizations can collaborate on data analysis without revealing sensitive information to each other (OECD, 2025; Finextra, 2024).

Federated learning is a machine learning approach where an AI model is trained across multiple decentralized devices or servers holding local data samples. The model is updated based on local data, but the raw data never leaves the original location. This is particularly valuable in healthcare, finance, and other sectors where data privacy is a top concern (OECD, 2025; Syntho, 2024).

Trusted execution environments (TEEs) are secure areas within a computer’s processor that protect code and data from being accessed or tampered with by other processes or users. TEEs enable secure computation on sensitive data, even in shared or untrusted environments (OECD, 2025; Finextra, 2024).

By combining these technologies, organizations can maximize data utility while minimizing privacy risks. PETs are not a one-size-fits-all solution, but rather a toolkit that can be tailored to different use cases and regulatory environments (OECD, 2025; CIPL, 2023).

Problems Being Solved or Best Practice Being Applied

Privacy-enhancing technologies (PETs) address several critical challenges identified in Part 1 of the course, most notably Sub-Point 1.1: Excessive Data Collection and Lack of Minimization and Sub-Point 1.2: Unauthorized Access and Data Breaches. These technologies provide practical solutions to reduce the risks associated with collecting, storing, and sharing personal data in artificial intelligence (AI) systems (OECD, 2025; Syntho, 2024).

One of the main problems is the risk of personal data being exposed, stolen, or misused, which can lead to identity theft, financial loss, reputational damage, and regulatory penalties (Syntho, 2024; Usercentrics, 2024). PETs help organizations minimize these risks by reducing the amount of sensitive data they collect and store—addressing Sub-Point 1.1—and by protecting data throughout its lifecycle, which directly combats Sub-Point 1.2.

Another challenge is the need to share data for research, innovation, and collaboration while respecting privacy and legal requirements. PETs enable secure data sharing and collaboration by allowing organizations to analyze and use data without direct access to raw personal information (OECD, 2025; Finextra, 2024). This supports best practices for data minimization and robust access controls, reinforcing the solutions to Sub-Point 1.1 and Sub-Point 1.2.

PETs also help organizations comply with strict data protection laws such as the General Data Protection Regulation (GDPR), the California Consumer Privacy Act (CCPA), and the Health Insurance Portability and Accountability Act (HIPAA). These regulations require organizations to protect personal data and, in many cases, encourage or mandate the use of privacy-enhancing technologies (Usercentrics, 2024; Syntho, 2024). By doing so, PETs help address Sub-Point 1.1 and Sub-Point 1.2 by ensuring that only necessary data is collected and that unauthorized access is prevented.

Best practices for implementing PETs include conducting privacy impact assessments, selecting the right combination of technologies for each use case, and regularly reviewing and updating privacy measures as technology and regulations evolve (ICO, 2024; CIPL, 2023). Organizations should also provide clear information to users about how their data is protected—supporting transparency and accountability—and allow users to exercise their privacy rights, such as access, correction, and deletion (Usercentrics, 2024; Syntho, 2024). These practices not only address Sub-Point 1.1 and Sub-Point 1.2 but also contribute to broader goals of user empowerment and regulatory compliance.

Role of Government and Regulatory Authorities

Governments and regulatory authorities play a crucial role in promoting and supporting the adoption of privacy-enhancing technologies. They set legal standards, provide guidance, and enforce compliance with data protection laws, creating a strong incentive for organizations to use PETs (OECD, 2025; Duality Tech, 2023).

Regulatory bodies such as the European Data Protection Board (EDPB), the UK Information Commissioner’s Office (ICO), and the US Federal Trade Commission (FTC) publish guidelines and best practices for implementing PETs. These guidelines help organizations understand which technologies are appropriate for different use cases and how to integrate them into their data protection strategies (ICO, 2024; OECD, 2025).

Governments also encourage innovation in PETs through funding, research grants, and regulatory sandboxes. Regulatory sandboxes allow organizations to test new privacy technologies in a controlled environment, reducing the risk of non-compliance and fostering innovation (OECD, 2025; Duality Tech, 2023). For example, the UK ICO has established a regulatory sandbox for privacy-enhancing technologies, supporting projects that explore new ways to protect personal data (ICO, 2024).

In addition to setting rules and supporting innovation, governments raise public awareness about the importance of privacy and the benefits of PETs. They run educational campaigns, host workshops, and provide resources to help individuals and organizations understand their rights and responsibilities (OECD, 2025; Duality Tech, 2023).

International cooperation is also important, as data flows across borders and privacy risks are global. Organizations like the OECD, G7, and UNESCO promote global standards for privacy and encourage the responsible use of PETs (OECD, 2025; UNESCO, 2021). These efforts help harmonize regulations, facilitate cross-border data sharing, and ensure that privacy protections keep pace with technological advancements.

Governments can also serve as model users of PETs, demonstrating best practices and creating demand for privacy-enhancing technologies. By adopting PETs in their own operations, governments show leadership and help build a market for innovative privacy solutions (OECD, 2025; Jones Day, 2011).

Role of Organizations and Businesses

Organizations and businesses are responsible for implementing privacy-enhancing technologies in their data practices. This involves assessing privacy risks, selecting appropriate PETs, and integrating them into data collection, processing, and sharing workflows (CIPL, 2023; Syntho, 2024).

One of the first steps is to conduct a privacy impact assessment to identify where sensitive data is collected, stored, and used, and to determine which PETs are best suited to protect that data (ICO, 2024; CIPL, 2023). Organizations should consider the specific needs of their industry, the types of data they handle, and the regulatory requirements they must meet.

For example, a financial institution might use encryption and pseudonymization to protect customer data, while a healthcare provider might use federated learning to enable collaborative research without sharing raw patient records (OECD, 2025; Finextra, 2024). Retailers can use differential privacy to analyze customer purchase patterns without accessing personal information, enabling targeted marketing while protecting privacy (OECD, 2025; Usercentrics, 2024).

Training and awareness are also critical. Employees need to understand how PETs work, why they are important, and how to use them effectively. Regular training helps ensure that privacy protections are consistently applied and that staff are prepared to respond to privacy incidents or user requests (CIPL, 2023; ICO, 2024).

Organizations should also monitor and audit their use of PETs to ensure ongoing effectiveness. This includes reviewing access logs, checking for vulnerabilities, and updating privacy measures as needed (CIPL, 2023; Syntho, 2024). Clear documentation and transparency about data handling practices help build trust with users and regulators.

By adopting PETs, organizations can reduce the risk of data breaches, comply with regulations, and build trust with customers and partners. PETs also enable new opportunities for data collaboration and innovation, helping organizations stay competitive in a data-driven world (OECD, 2025; Finextra, 2024).

Role of Vendors and Third Parties

Vendors and third-party providers play a key role in supporting the adoption and implementation of privacy-enhancing technologies. They develop and supply tools, platforms, and services that enable organizations to protect personal data and comply with regulatory requirements (OECD, 2025; CIPL, 2023).

Vendors offer a wide range of PETs, including encryption software, anonymization tools, differential privacy solutions, secure multi-party computation platforms, and federated learning frameworks. These products are designed to be easy to integrate into existing systems and workflows, reducing the technical barriers to adoption (OECD, 2025; Finextra, 2024).

Third-party auditors and consultants provide independent assessments of privacy practices, helping organizations identify risks and implement effective PETs. They also offer training, support, and guidance to ensure that privacy measures are correctly applied and maintained (CIPL, 2023; ISACA, 2024).

Vendors and third parties should be transparent about their own data handling practices and security measures. They should provide clear documentation, support compliance with relevant regulations, and respond quickly to any identified vulnerabilities or privacy incidents (OECD, 2025; Syntho, 2024).

Collaboration between organizations and vendors is essential for advancing the state of the art in PETs. Vendors can help organizations stay up to date with the latest privacy technologies and best practices, while organizations provide valuable feedback and use cases that drive innovation (OECD, 2025; CIPL, 2023).

Role of Employees and Internal Teams

Employees and internal teams are essential for the successful implementation and operation of privacy-enhancing technologies. Developers, data scientists, and IT staff design and build systems that incorporate PETs, ensuring that privacy protections are embedded from the start (CIPL, 2023; Syntho, 2024).

Data protection officers and compliance teams oversee the implementation of privacy policies and ensure that PETs are used correctly. They manage user rights requests, conduct internal audits, and respond to privacy incidents (ICO, 2024; CIPL, 2023).

Customer support and user experience teams communicate with users about privacy protections, explain how their data is protected, and help them exercise their privacy rights (Usercentrics, 2024; Syntho, 2024). Clear, user-friendly interfaces and documentation make it easier for users to understand and trust privacy measures.

Training and awareness programs help all employees understand the importance of privacy and how to use PETs effectively. Regular training ensures that staff are prepared to recognize and respond to privacy risks, and that privacy protections are consistently applied across the organization (CIPL, 2023; ICO, 2024).

Internal teams also monitor and audit privacy practices to ensure ongoing effectiveness. They review access logs, check for vulnerabilities, and update privacy measures as needed. By maintaining high standards of data governance, employees help protect user privacy and build trust in AI systems (CIPL, 2023; Syntho, 2024).

Role of Industry Groups and Professional Bodies

Industry groups and professional bodies develop standards, guidelines, and certifications to promote best practices in privacy-enhancing technologies. They facilitate knowledge sharing, research, and advocacy to advance privacy protections and support responsible data use (OECD, 2025; CIPL, 2023).

Organizations such as the International Organization for Standardization (ISO), the National Institute of Standards and Technology (NIST), and the International Association of Privacy Professionals (IAPP) publish technical standards and best practices for PETs. These standards help organizations select, implement, and audit privacy measures, and provide a common language for discussing privacy risks and controls (OECD, 2025; NIST, 2020).

Professional bodies offer training and certification programs for privacy professionals, helping them develop the skills needed to implement and manage PETs. These programs cover topics such as data anonymization, encryption, differential privacy, and secure data sharing (IAPP, 2024; CIPL, 2023).

Industry groups also advocate for strong privacy regulations and support public awareness campaigns. They organize conferences, workshops, and working groups where experts can share insights, discuss emerging challenges, and develop new solutions (OECD, 2025; CIPL, 2023).

By setting industry-wide benchmarks and promoting ethical conduct, industry groups and professional bodies help build public trust in AI technologies and encourage widespread adoption of privacy-enhancing technologies (OECD, 2025; CIPL, 2023).

Role of International and Multilateral Organizations

International and multilateral organizations play a key role in promoting global standards for privacy and supporting the responsible use of privacy-enhancing technologies. They develop frameworks, guidelines, and recommendations that influence national policies and industry practices (OECD, 2025; UNESCO, 2021).

The OECD, G7, and UNESCO promote privacy by design and encourage the adoption of PETs to protect personal data and enable secure data sharing (OECD, 2025; UNESCO, 2021). These organizations support capacity building, technical assistance, and research to help countries implement effective privacy protections.

International organizations also facilitate dialogue among stakeholders, helping to address emerging challenges and harmonize approaches to privacy and data protection. They publish reports, host conferences, and provide platforms for collaboration and knowledge exchange (OECD, 2025; UNESCO, 2021).

By fostering global cooperation and setting high standards, international organizations help ensure that privacy protections keep pace with technological advancements and that data flows across borders are safe and secure (OECD, 2025; UNESCO, 2021).

Role of Consumers and Users

Consumers and users play an important role in driving the adoption of privacy-enhancing technologies. By demanding transparency, accountability, and strong privacy protections, they encourage organizations to prioritize privacy and invest in PETs (Usercentrics, 2024; Syntho, 2024).

Users can exercise their rights under data protection laws, such as requesting access to their data, correcting inaccuracies, or asking for their information to be deleted. These rights empower individuals to hold organizations accountable and ensure that their preferences are respected (Usercentrics, 2024; Syntho, 2024).

Feedback mechanisms, such as surveys, complaint channels, and public forums, provide valuable insights into user concerns and experiences. Organizations can use this input to improve their privacy practices and address emerging risks (Usercentrics, 2024; Syntho, 2024).

Educational initiatives help raise awareness about privacy risks and the benefits of PETs. By understanding their rights and how their data is protected, users can make informed decisions and advocate for stronger privacy protections (Usercentrics, 2024; Syntho, 2024).

Ultimately, empowered consumers contribute to a market environment where privacy is a competitive advantage, motivating organizations to adopt best practices and innovate in privacy-enhancing technologies (OECD, 2025; Usercentrics, 2024).

Role of Members of the Public

Members of the public influence the adoption of privacy-enhancing technologies through advocacy, education, and participation in policymaking. Civil society organizations promote awareness of privacy rights and push for stronger privacy protections (OECD, 2025; CIPL, 2023).

Public consultations and participatory policymaking processes allow citizens to voice their concerns and contribute to the creation of balanced and effective privacy laws. Media coverage and educational programs inform the public about the importance of privacy and the risks of data misuse (OECD, 2025; CIPL, 2023).

By holding organizations and governments accountable, members of the public help ensure that privacy protections are robust and that data is used responsibly. Public opinion and activism can influence the direction of innovation and policy, driving progress toward a more privacy-respecting digital society (OECD, 2025; CIPL, 2023).

Role of Artificial Intelligence Itself

Artificial intelligence can support privacy-enhancing technologies by automating privacy protections, detecting anomalies, and generating audit trails (OECD, 2025; Finextra, 2024). AI-powered tools can analyze large datasets for privacy risks, flag potential vulnerabilities, and provide recommendations for improving privacy measures.

For example, AI can help organizations implement differential privacy by automatically adding the right amount of noise to datasets or query results. AI can also monitor data access patterns, detect unauthorized activity, and generate reports for regulators and stakeholders (OECD, 2025; Finextra, 2024).

AI-driven privacy management platforms can personalize privacy settings for users, making it easier for them to understand and control how their data is used. These platforms can provide clear, user-friendly explanations of privacy protections and allow users to update their preferences at any time (Usercentrics, 2024; Syntho, 2024).

However, human oversight is essential to ensure that AI-driven privacy protections are fair, transparent, and effective. Organizations must regularly review and validate the results of AI-powered privacy tools, and involve human experts in interpreting findings and making decisions (OECD, 2025; Finextra, 2024).

Role of Bad Actors

Bad actors, including hackers, cybercriminals, and malicious insiders, pose significant challenges to privacy protections. They may attempt to bypass privacy-enhancing technologies, exploit vulnerabilities, or manipulate data for personal gain (ISACA, 2024; Syntho, 2024).

Robust security measures, continuous monitoring, and independent verification are necessary to protect against these threats. Organizations should implement strong access controls, encryption, and audit trails to prevent unauthorized changes to data or privacy settings (ISACA, 2024; Syntho, 2024).

Collaboration among organizations, governments, and industry groups is essential to share threat intelligence and develop effective countermeasures. By working together, stakeholders can identify emerging risks and respond quickly to protect user privacy and trust (ISACA, 2024; Syntho, 2024).

Bad actors may also target the technology underlying PETs, such as encryption or secure multi-party computation. Organizations must ensure that these technologies are implemented securely and that vulnerabilities are promptly addressed (ISACA, 2024; Syntho, 2024).

Glossary

Term	Meaning and Example Sentence
Privacy-Enhancing Technologies (PETs)	Tools and methods to protect personal data. Example: “PETs help keep sensitive information private while allowing data analysis.”
Encryption	Scrambling data so it can only be read with a key. Example: “Encryption protects data during transmission and storage.”
Anonymization	Removing or altering data to prevent identification. Example: “Anonymization makes it impossible to link data to individuals.”
Pseudonymization	Replacing identifiers with codes that can be reversed. Example: “Pseudonymization allows data analysis without revealing identities.”
Differential Privacy	Adding noise to data to protect individual privacy. Example: “Differential privacy lets organizations publish statistics without revealing personal details.”
Secure Multi-Party Computation (SMPC)	Joint computation on private inputs. Example: “SMPC enables collaboration without sharing raw data.”
Federated Learning	Training AI models on decentralized data. Example: “Federated learning allows hospitals to collaborate on research without sharing patient records.”
Trusted Execution Environment (TEE)	Secure area within a processor for sensitive tasks. Example: “TEEs protect code and data from unauthorized access.”

Questions

1. What are privacy-enhancing technologies (PETs), and why are they important for AI systems?

2. What are some examples of privacy-enhancing technologies, and how do they work?

3. How do governments and regulatory authorities support the adoption of PETs?

4. What responsibilities do organizations and businesses have in implementing PETs?

5. How can consumers and users contribute to the adoption of privacy-enhancing technologies?

Answer Key

1. Suggested Answer: Privacy-enhancing technologies (PETs) are tools and methods designed to protect personal data while enabling analysis and sharing. They are important for AI systems because they help minimize privacy risks, build trust, and ensure compliance with data protection laws (OECD, 2025; Usercentrics, 2024).

2. Suggested Answer: Examples of PETs include encryption, anonymization, pseudonymization, differential privacy, secure multi-party computation, federated learning, and trusted execution environments. These technologies protect data by limiting collection, transforming information, or enabling secure collaboration without exposing raw data (OECD, 2025; Finextra, 2024).

3. Suggested Answer: Governments and regulatory authorities set legal standards, provide guidance, support innovation through funding and sandboxes, and raise public awareness about the importance of PETs. They also enforce compliance and promote international cooperation (OECD, 2025; Duality Tech, 2023).

4. Suggested Answer: Organizations and businesses are responsible for assessing privacy risks, selecting appropriate PETs, integrating them into data practices, training employees, and monitoring effectiveness. They should also be transparent about data handling and respond to user rights requests (CIPL, 2023; Syntho, 2024).

5. Suggested Answer: Consumers and users can drive adoption by demanding transparency and strong privacy protections, exercising their rights under data protection laws, providing feedback, and participating in educational initiatives (Usercentrics, 2024; Syntho, 2024).

References

OECD. (2025). Sharing trustworthy AI models with privacy-enhancing technologies. https://www.oecd.org/en/publications/sharing-trustworthy-ai-models-with-privacy-enhancing-technologies_a266160b-en.html
Usercentrics. (2024). A guide to privacy-enhancing technologies (PETs). https://usercentrics.com/guides/privacy-led-marketing/privacy-enhancing-technologies/
Syntho. (2024). What are privacy-enhancing technologies (PETs)? https://www.syntho.ai/what-are-privacy-enhancing-technologies-pets/
Finextra. (2024). Privacy enhancing technologies: Key to win in today’s evolving world. https://www.finextra.com/blogposting/26348/privacy-enhancing-technologies-key-to-win-in-todays-evolving-world
ISACA. (2024). Exploring practical considerations and applications for privacy-enhancing technologies. https://www.isaca.org/resources/white-papers/2024/exploring-practical-considerations-and-applications-for-privacy-enhancing-technologies
Duality Tech. (2023). How governments can foster the adoption of privacy-enhancing technologies (PETs). https://dualitytech.com/blog/how-governments-can-foster-the-adoption-of-privacy-enhancing-technologies-pets/
ICO. (2024). Privacy-enhancing technologies: Guidance for data protection officers. https://ico.org.uk/media/about-the-ico/consultations/4021464/chapter-5-anonymisation-pets.pdf
CIPL. (2023). Understanding the role of PETs and PPTs in the digital age. https://www.informationpolicycentre.com/uploads/5/7/1/0/57104281/cipl-understanding-pets-and-ppts-dec2023.pdf
UNESCO. (2021). Recommendation on the ethics of artificial intelligence. https://unesdoc.unesco.org/ark:/48223/pf0000380455
NIST. (2020). Privacy framework: A tool for improving privacy through enterprise risk management. https://www.nist.gov/privacy-framework
Jones Day. (2011). Government options for encouraging use of online privacy-enhancing technologies. https://www.jonesday.com/-/media/files/publications/2011/03/government-options-for-encouraging-use-of-online-p/files/advisor03_11_govt/fileattachment/advisor03_11_govt.pdf?rev=d1cb0818265c45acb9b95cf65128b8d9&sc_lang=en