Privacy and Artificial Intelligence - 2.4 Dynamic Consent Management and User Empowerment

2.4 Dynamic Consent Management and User Empowerment

Introduction

Dynamic consent management is a flexible, ongoing process that allows individuals to control and update their consent preferences over time, adapting to changing circumstances and uses of their data. This approach is especially important in the context of artificial intelligence (AI), where data collection and processing are continuous and often used in new and unforeseen ways. Dynamic consent empowers users by giving them more control over their personal information, enhancing transparency, trust, and engagement. It moves beyond traditional static, one-time consent models to a more interactive and personalized framework that respects user autonomy and privacy (Khalid et al., 2023; Prinsen, 2024).

Dynamic consent is not just a technical solution but a shift in how organizations and individuals interact with data. It recognizes that people’s preferences and contexts change, and it provides a way for them to adjust their permissions as needed. For example, someone using a health app might initially agree to share their data for research but later decide to restrict access to certain types of studies. With dynamic consent, this change can be made quickly and easily, ensuring that the user’s wishes are always reflected in how their data is used.

Technical or Conceptual Background

Dynamic consent management systems involve several key actors: the Data Subject, who is the individual providing their data and consent; the Data Controller, who manages the data and consent records; the Data Auditor, who oversees compliance and security; and the Data Requester, who seeks access to the data for specific purposes (Khalid et al., 2023; Prinsen, 2024). These systems are designed to ensure that consent is freely given, explicit, informed, precise, and revocable, allowing users to tailor their preferences and update them as needed.

A central feature of dynamic consent is its ongoing nature. Unlike traditional consent, which is often obtained once and remains unchanged, dynamic consent allows individuals to review, modify, or revoke their permissions at any time. This is particularly important in AI systems, where data may be used for purposes that were not anticipated at the time of initial consent. For example, a medical research project might use patient data for new studies as technology advances. With dynamic consent, participants can be informed of these new uses and decide whether to continue their involvement (Prinsen, 2024; Lay et al., 2025).

Technologies such as blockchain provide immutable records of consent transactions, enhancing transparency and auditability. Advanced cryptographic methods like attribute-based encryption and zero-knowledge proofs help protect privacy while enabling secure data sharing. These technical solutions support the dynamic nature of consent, ensuring that users’ choices are respected throughout the data lifecycle (Khalid et al., 2023; Williams et al., 2015).

Another important aspect is the digital interface that enables dynamic consent. This interface allows users to view their current consent settings, update preferences, and receive information about how their data is being used. It can also provide notifications when new uses are proposed or when data is accessed by third parties. This level of interactivity helps users feel more informed and in control, which is essential for building trust in AI systems (Williams et al., 2015; Prinsen, 2024).

Problems Being Solved or Best Practice Being Applied

Dynamic consent management and user empowerment directly address the problem identified in Sub-Point 1.4: Inadequate Consent Management and User Rights. This approach provides a solution for ensuring that individuals have ongoing control over how their personal data is used, addressing the limitations of traditional static consent models which often fail to accommodate changing user preferences or new data uses. In many cases, people may not fully understand the implications of their initial consent, especially as technology evolves and new applications for data emerge. Dynamic consent provides a mechanism for ongoing engagement, allowing individuals to stay informed and make decisions based on current information (Lay et al., 2025; Prinsen, 2024).

A key benefit of dynamic consent is its ability to support granular control. Users can specify different levels of permission for different types of data or for different purposes. For example, someone might allow their health data to be used for academic research but not for commercial projects. They might also choose to be contacted for new research opportunities or to receive updates on how their data is being used. This flexibility helps ensure that users’ preferences are respected and that they remain engaged with the organizations that hold their data (Lay et al., 2025; Williams et al., 2015).

Dynamic consent is widely applied in healthcare and biomedical research, where ongoing participant engagement and data protection are critical. In these fields, dynamic consent has been shown to improve trust, increase participation rates, and reduce the risk of privacy violations. It also helps organizations comply with regulatory requirements by providing clear records of consent and enabling rapid response to user requests for changes or withdrawals (Prinsen, 2024; Lay et al., 2025). By addressing Sub-Point 1.4, dynamic consent management ensures that individuals are empowered to exercise their rights and that organizations maintain transparency and accountability in their data practices.

Role of Government and Regulatory Authorities

Governments and regulatory authorities play a pivotal role in promoting and enforcing dynamic consent management. They establish legal frameworks that require organizations to implement consent mechanisms that are flexible, transparent, and user-centric. For example, the European Union’s General Data Protection Regulation (GDPR) mandates that consent must be specific, informed, and revocable, aligning with the principles of dynamic consent (European Parliament, 2016; EDPB, 2023).

Regulators provide guidance and resources to help organizations adopt dynamic consent, including best practice frameworks, technical standards, and compliance checklists. They also conduct audits and investigations to ensure adherence to consent requirements, imposing penalties for non-compliance. Public awareness campaigns and educational initiatives further support understanding of consent rights and responsibilities (EDPB, 2023; ICO, 2024).

International cooperation among regulatory bodies fosters harmonization of consent standards, facilitating cross-border data flows while protecting individual rights. Organizations like the OECD and UNESCO promote ethical AI governance that includes dynamic consent as a key component of privacy protection (OECD, 2023; UNESCO, 2021).

In addition to setting rules and enforcing compliance, governments invest in research and development to advance privacy-enhancing technologies. They support initiatives that explore new ways to implement dynamic consent, such as blockchain-based consent registries or AI-powered consent management tools. By fostering innovation and collaboration, governments help create a safer and more trustworthy environment for data use (Digital Watch Observatory, 2025; ITU, 2024).

Governments also play a role in raising awareness about the importance of consent and privacy. They run public campaigns, host workshops, and provide educational materials to help people understand their rights and how to exercise them. This is especially important in the context of AI, where the complexity of data processing can make it difficult for individuals to know what is happening with their information (ICO, 2024; OECD, 2023).

Role of Organizations and Businesses

Organizations and businesses are responsible for integrating dynamic consent into their AI systems and data practices. This involves developing policies that prioritize user control, transparency, and ongoing communication. Privacy impact assessments and risk analyses help identify areas where dynamic consent can mitigate privacy risks (IAPP, 2024).

Technical implementation includes deploying user-friendly interfaces that allow individuals to view, modify, and revoke their consent preferences easily. Organizations must ensure that consent records are securely stored and that data access aligns with current user permissions. Training programs equip employees with the knowledge to support dynamic consent processes and respond to user inquiries effectively (PCPD, 2025).

Continuous monitoring and auditing of consent management systems are essential to maintain compliance and adapt to evolving regulatory requirements. Organizations should also provide clear privacy notices and facilitate user rights such as data access and deletion requests, reinforcing trust and accountability (ICO, 2024; IAPP, 2024).

Organizations can also benefit from dynamic consent by improving their reputation and building stronger relationships with users. When people trust that their preferences will be respected and that they can change their mind at any time, they are more likely to engage with services and share their data. This is particularly important in sectors like healthcare, finance, and education, where trust is essential for successful outcomes (Lay et al., 2025; Williams et al., 2015).

Another important aspect is the use of technology to support dynamic consent. Organizations can leverage tools like blockchain for secure, tamper-proof consent records, and AI-powered interfaces to personalize consent information and make it easier to understand. These innovations help ensure that dynamic consent is not only compliant but also user-friendly and effective (Khalid et al., 2023; Williams et al., 2015).

Role of Vendors and Third Parties

Vendors and third-party providers supply critical components and services that enable dynamic consent management. They must ensure their products support flexible consent mechanisms, secure data handling, and compliance with relevant regulations. Transparency about data processing practices and security measures is vital to maintain trust (Cloud Security Alliance, 2023; ISACA, 2025).

Vendors should offer tools for consent tracking, audit logging, and user preference management. Regular security assessments and certifications demonstrate their commitment to privacy and security. Collaboration with client organizations helps tailor solutions to specific needs and regulatory contexts (ISACA, 2025; Cloud Security Alliance, 2023).

Vendors also play a role in advancing the technology behind dynamic consent. They invest in research and development to create new features, such as AI-driven consent recommendations, personalized notifications, and automated compliance checks. By staying at the forefront of innovation, vendors help organizations keep pace with evolving privacy expectations and regulatory requirements (Khalid et al., 2023; Williams et al., 2015).

Another important responsibility is to provide clear documentation and support for integrating dynamic consent into existing systems. This includes technical guides, training materials, and customer support services to help organizations implement and maintain dynamic consent solutions (ISACA, 2025; Cloud Security Alliance, 2023).

Role of Employees and Internal Teams

Employees and internal teams play a crucial role in implementing and maintaining dynamic consent management. Developers design and build systems that support consent flexibility and security. Data protection officers oversee compliance and manage user rights requests. Customer support teams assist users in understanding and exercising their consent options (IAPP, 2024; ENISA, 2021).

Training and awareness programs ensure that all staff understand the importance of dynamic consent and their responsibilities. Internal audits and incident response plans help detect and address issues promptly, maintaining system integrity and user trust (ENISA, 2021; IAPP, 2024).

Employees also contribute to the ongoing improvement of consent management processes. They gather feedback from users, monitor system performance, and suggest enhancements to make consent interfaces more intuitive and effective. This continuous improvement cycle helps organizations stay responsive to user needs and regulatory changes (IAPP, 2024; ENISA, 2021).

Another important function is to ensure that consent records are accurate and up to date. This includes verifying that data access permissions match current user preferences and that any changes are promptly reflected in the system. By maintaining high standards of data governance, employees help protect user privacy and build trust in AI systems (PCPD, 2025; ICO, 2024).

Role of Industry Groups and Professional Bodies

Industry groups and professional bodies develop standards, guidelines, and certifications that promote best practices in dynamic consent management. They facilitate knowledge sharing, research, and advocacy to advance privacy-enhancing technologies and user empowerment (IEEE, 2022; IAPP, 2024).

These organizations engage with policymakers to shape regulations that support dynamic consent and protect individual rights. They also provide training and resources to help organizations implement effective consent management strategies (OECD, 2023; IEEE, 2022).

Industry groups play a key role in fostering collaboration and innovation. They organize conferences, workshops, and working groups where experts from different sectors can share insights and develop new solutions. This collaborative approach helps accelerate the adoption of dynamic consent and ensures that best practices are widely disseminated (IEEE, 2022; IAPP, 2024).

Professional bodies also certify individuals and organizations that meet high standards of privacy and consent management. These certifications provide assurance to users and regulators that certified entities are trustworthy and compliant with relevant laws and standards (IAPP, 2024; IEEE, 2022).

Another important function is to advocate for user rights and ethical data practices. Industry groups and professional bodies campaign for stronger privacy protections, greater transparency, and more meaningful user control over personal data. By raising awareness and influencing policy, they help create a more equitable and trustworthy digital environment (OECD, 2023; IEEE, 2022).

Role of International and Multilateral Organizations

International and multilateral organizations foster global collaboration on dynamic consent standards and ethical AI governance. They develop frameworks that encourage transparency, user control, and privacy protection across jurisdictions (UNESCO, 2021; ITU, 2024).

These bodies support capacity building and technical assistance, especially in developing countries, to promote equitable access to privacy-enhancing technologies. They also facilitate dialogue among stakeholders to address emerging challenges and harmonize approaches to consent management (Digital Watch Observatory, 2025; UNESCO, 2021).

International organizations play a key role in setting global standards for consent and privacy. They publish guidelines, best practices, and policy recommendations that influence national regulations and industry practices. By promoting a consistent approach to consent, they help ensure that user rights are protected regardless of where data is processed or stored (OECD, 2023; UNESCO, 2021).

Another important function is to monitor trends and identify emerging risks. International organizations conduct research, collect data, and publish reports on the state of privacy and consent around the world. This intelligence helps governments, businesses, and civil society stay informed and proactive in addressing new challenges (Digital Watch Observatory, 2025; ITU, 2024).

International organizations also provide platforms for collaboration and knowledge exchange. They host conferences, working groups, and online forums where experts can share experiences, discuss innovations, and develop joint solutions. This collaborative approach helps accelerate progress and ensures that best practices are widely adopted (UNESCO, 2021; ITU, 2024).

Role of Consumers and Users

Consumers and users are empowered by dynamic consent to take control of their personal data. They can update their preferences, revoke consent, and receive information about how their data is used. This active participation fosters trust and accountability (IAPP, 2024; Lay et al., 2025).

User feedback helps organizations improve consent processes and address concerns. Educational initiatives raise awareness about privacy rights and the benefits of dynamic consent, enabling informed decision-making (ICO, 2024; Lay et al., 2025).

Another important aspect is the ability to exercise rights under data protection laws. Users can request access to their data, correct inaccuracies, or ask for their information to be deleted. These rights empower individuals to hold organizations accountable and ensure that their preferences are respected (European Parliament, 2016; ICO, 2024).

Users also play a role in shaping the market for privacy-enhancing technologies. By demanding transparency, control, and accountability, they drive innovation and encourage organizations to adopt best practices. This consumer-driven approach helps raise standards across industries and ensures that privacy remains a priority (Lay et al., 2025; Williams et al., 2015).

Role of Members of the Public

Members of the public influence dynamic consent adoption through advocacy, education, and participation in policymaking. Civil society organizations promote awareness of privacy rights and push for stronger consent frameworks (EFF, 2023; OECD, 2023).

Public consultations ensure that regulations reflect societal values and protect vulnerable groups. Media coverage and educational programs inform the public about the importance of consent and privacy in AI (OECD, 2023; EFF, 2023).

Another important function is to hold organizations and governments accountable. Members of the public can report concerns, participate in audits, and advocate for stronger protections. This civic engagement helps ensure that privacy rights are upheld and that consent practices are fair and transparent (EFF, 2023; OECD, 2023).

Public opinion also influences the development of new technologies and policies. By expressing their preferences and concerns, members of the public help shape the direction of innovation and ensure that AI systems are designed with user interests in mind (OECD, 2023; EFF, 2023).

Role of Artificial Intelligence Itself

AI can support dynamic consent by automating consent tracking, monitoring compliance, and providing personalized communication. AI systems can detect anomalies in consent usage and generate audit trails to ensure accountability (Veale, 2022; Williams et al., 2015).

AI-powered interfaces can personalize consent information, making it easier for users to understand and make informed decisions. For example, AI can highlight the most relevant details, use plain language, or provide interactive explanations. These features help ensure that consent is truly informed and that users feel confident in their choices (Williams et al., 2015; Veale, 2022).

AI can also help organizations manage large volumes of consent records and respond quickly to user requests. Automated workflows can process changes to consent preferences, update records, and notify relevant parties. This efficiency helps organizations stay compliant and responsive to user needs (Veale, 2022; Williams et al., 2015).

However, human oversight is essential to ensure AI-driven consent management respects user autonomy and privacy, avoiding biases or errors. Organizations must ensure that AI systems are transparent, explainable, and subject to regular review (Veale, 2022; Williams et al., 2015).

Role of Bad Actors

Bad actors may attempt to exploit dynamic consent systems by manipulating consent records, unauthorized data access, or social engineering attacks. Robust security measures and continuous monitoring are necessary to mitigate these risks (ISACA, 2025; Symantec, 2024).

Collaboration among organizations, governments, and industry is vital to share threat intelligence and develop effective countermeasures against malicious activities. By working together, stakeholders can identify emerging threats and respond quickly to protect user data and trust (ISACA, 2025; Symantec, 2024).

Bad actors may also target the technology underlying dynamic consent, such as blockchain or encryption systems. Organizations must ensure that these technologies are implemented securely and that vulnerabilities are promptly addressed. Regular security assessments and penetration testing help identify and fix weaknesses before they can be exploited (ISACA, 2025; Symantec, 2024).

Another important consideration is the risk of insider threats. Employees or contractors with access to consent systems may misuse their privileges for personal gain or to harm the organization. Strong access controls, monitoring, and accountability mechanisms help prevent and detect such incidents (ISACA, 2025; Symantec, 2024).

Glossary

Term	Meaning and Example Sentence
Data Subject	The individual whose personal data is collected and controlled. Example: "The data subject can update their consent preferences anytime."
Data Controller	The entity responsible for managing personal data and consent records. Example: "The data controller ensures data is used according to consent."
Data Auditor	An independent party that verifies compliance with consent and privacy policies. Example: "The data auditor checks that consent records are accurate."
Data Requester	An individual or organization requesting access to personal data for specific purposes. Example: "The data requester must have consent to use the data."
Consent	Permission given by a data subject for specific data processing activities. Example: "Consent can be withdrawn or updated at any time."
Blockchain	A secure, decentralized ledger that records transactions transparently. Example: "Blockchain ensures consent records cannot be altered."
Encryption	A method of scrambling data to protect it from unauthorized access. Example: "Encryption keeps personal data safe during transmission."
Privacy by Design	Integrating privacy protections into technology from the start. Example: "Privacy by Design ensures data is protected throughout its lifecycle."
User Empowerment	Giving users control over their personal data and privacy choices. Example: "User empowerment is central to dynamic consent management."

Questions

1. What is dynamic consent management, and how does it differ from traditional consent models?

2. Who are the key actors involved in dynamic consent management systems?

3. How do governments support the adoption of dynamic consent management?

4. What responsibilities do organizations have in implementing dynamic consent?

5. How can AI assist in dynamic consent management?

Answer Key

1. Suggested Answer: Dynamic consent management is a flexible, ongoing process that allows individuals to control and update their consent preferences over time, unlike traditional static consent which is one-time and fixed (Khalid et al., 2023; Prinsen, 2024).

2. Suggested Answer: The key actors are Data Subject, Data Controller, Data Auditor, and Data Requester, each playing a role in managing and using personal data with consent (Khalid et al., 2023).

3. Suggested Answer: Governments create laws, enforce compliance, provide guidance, promote international cooperation, and raise public awareness to support dynamic consent (European Parliament, 2016; EDPB, 2023).

4. Suggested Answer: Organizations develop policies, implement technical controls, train employees, monitor systems, and ensure transparency and user rights facilitation (IAPP, 2024; ICO, 2024).

5. Suggested Answer: AI can automate consent tracking, monitor compliance, provide personalized communication, and generate audit trails, but requires human oversight to avoid errors (Veale, 2022; Williams et al., 2015).

References

Khalid, M. I., Ahmed, M., & Kim, J. (2023). Enhancing data protection in dynamic consent management systems: Formalizing privacy and security definitions with differential privacy, decentralization, and zero-knowledge proofs. Sensors, 23(17), 7604. https://doi.org/10.3390/s23177604
Prinsen, L. (2024). Introducing dynamic consent for improved trust and privacy in research involving human biological material and associated data in South Africa. Frontiers in Genetics, 15, 1272924. https://doi.org/10.3389/fgene.2024.1272924
European Parliament. (2016). Regulation (EU) 2016/679 (General Data Protection Regulation). Official Journal of the European Union. https://eur-lex.europa.eu/eli/reg/2016/679/oj
EDPB. (2023). Guidelines on data protection by design and by default. European Data Protection Board. https://edpb.europa.eu/our-work-tools/our-documents/guidelines/guidelines-042020-data-protection-design-and_en
ICO. (2024). Data minimization and privacy-preserving techniques in AI systems. Information Commissioner’s Office. https://ico.org.uk/about-the-ico/ico-and-stakeholder-consultations/ico-call-for-input-artificial-intelligence/
IAPP. (2024). Privacy and security by design: Best practices for AI. International Association of Privacy Professionals. https://iapp.org/resources/article/privacy-and-security-by-design-best-practices-for-ai/
Cloud Security Alliance. (2023). Security guidance for critical areas of focus in cloud computing. https://cloudsecurityalliance.org/research/security-guidance/
ISACA. (2025). Six steps for third-party AI risk management. ISACA Now Blog. https://www.isaca.org/resources/news-and-trends/isaca-now-blog/2025/six-steps-for-third-party-ai-risk-management
ENISA. (2021). Privacy and security by design in AI systems. European Union Agency for Cybersecurity. https://www.enisa.europa.eu/publications/privacy-and-security-by-design-in-ai-systems
Veale, M. (2022). AI and privacy: The role of automation in compliance. Harvard Journal of Law & Technology, 35(1), 1–73. https://jolt.law.harvard.edu/assets/articlePDFs/v35/35HarvJLTech1.pdf
Symantec. (2024). Threat intelligence and cybersecurity trends. https://www.symantec.com/security-center
Williams, H., Spencer, K., Sanders, C., Lund, D., Whitley, E. A., Kaye, J., & Dixon, W. G. (2015). Dynamic consent: A possible solution to improve patient confidence and trust in how electronic patient records are used in medical research. JMIR Medical Informatics, 3(1), e3. https://doi.org/10.2196/medinform.3525
OECD. (2023). OECD guidelines on the protection of privacy and transborder flows of personal data. https://www.oecd.org/digital/privacy/
UNESCO. (2021). Recommendation on the ethics of artificial intelligence. https://unesdoc.unesco.org/ark:/48223/pf0000380455
ITU. (2024). Standardization of AI and cybersecurity. International Telecommunication Union. https://www.itu.int/en/ITU-T/study-groups/2017-2020/17/Pages/default.aspx
Digital Watch Observatory. (2025). Global consensus grows on inclusive and cooperative AI governance at IGF 2025. https://dig.watch/updates/global-consensus-grows-on-inclusive-and-cooperative-ai-governance-at-igf-2025
Lay, W., Gasparini, L., Siero, W., & Hughes, E. K. (2025). A rapid review of the benefits and challenges of dynamic consent. Research Ethics, 21(1), 180–202. https://doi.org/10.1177/17470161241278064
EFF. (2023). Digital rights and privacy advocacy. Electronic Frontier Foundation. https://www.eff.org
PCPD. (2025). The Privacy Commissioner’s Office has completed compliance checks on AI systems. https://www.pcpd.org.hk/english/news_events/media_statements/press_20250508.html
IEEE. (2022). IEEE 7010-2020: Recommended practice for assessing the impact of autonomous and intelligent systems on human well-being. https://standards.ieee.org/ieee/7010/10781/