Privacy and Artificial Intelligence - 2.1 Privacy and Security by Design

2.1 Privacy and Security by Design

Introduction

Privacy and Security by Design means building artificial intelligence (AI) systems that protect people’s information and safety from the very start—like adding seat belts to a car during design instead of after accidents happen. This approach embeds privacy protections and security controls directly into AI systems, making them safer and more trustworthy for everyone, including children (Cavoukian, 2009; ENISA, 2021). For example, when developers create a smart toy, they build in features that prevent it from recording private conversations, ensuring children’s safety from the beginning. This is important because it helps stop problems before they happen, rather than trying to fix them later when it might be too late.

When we use new technology, like smart toys, voice assistants, or AI-powered apps, there is always a chance that something could go wrong. Maybe the toy accidentally records what you say, or the app collects too much information about you without you knowing. Privacy and Security by Design helps prevent these mistakes by making sure the people who create these technologies think about privacy and security at every step, not just as an afterthought. This way, everyone—including kids—can use technology with confidence that their information is safe.

Technical or Conceptual Background

Privacy by Design (PbD) and Security by Design (SbD) are frameworks that require privacy and security measures to be built into technology during development—not added later. Privacy by Design is based on seven foundational principles, including proactive prevention (stopping problems before they start), privacy as the default setting (making sure privacy is always on unless you choose otherwise), and end-to-end security (keeping data safe throughout its entire lifecycle) (Cavoukian, 2009). Security by Design focuses on making sure that systems automatically protect users unless they choose otherwise, which is sometimes called “secure default settings” (OWASP, 2023).

For AI, this means using special techniques to keep personal information private, even when the AI is doing complex tasks. For example, federated learning is a method where data stays on users’ own devices, so the AI learns from your information without actually seeing it. Another example is homomorphic encryption, which lets the computer answer questions using your data while it is still scrambled, so no one can read your private details (Acar et al., 2021). These methods help keep your information safe, even if someone tries to look at it.

Privacy and Security by Design also means thinking about how the AI will be used in real life. For kids, this means making sure that toys and apps do not collect too much information, do not share it with strangers, and do not keep it longer than necessary. For everyone, it means knowing what information is being collected, why it is being collected, and who can see it. This way, people can trust that their information is being handled carefully and responsibly.

Problems Being Solved or Best Practice Being Applied

Privacy and Security by Design directly addresses the problems of excessive data collection (Part 1.1) and unauthorized access (Part 1.2). By designing AI to collect only the information it really needs—called “data minimization”—and by building strong controls to make sure only the right people can access the data, these risks are greatly reduced. For example, a voice assistant built with Privacy by Design would only listen when you say a special word, like “Hey, Assistant,” instead of recording everything you say all the time (Cavoukian, 2009). This way, your private conversations stay private.

Another important part of Privacy and Security by Design is making sure that the people who use AI systems know what is happening with their information. This is called transparency. For example, if you use an AI app, it should tell you what information it collects and how it uses that information. If you are a kid, your parents or teachers can help you understand these notices and make sure your information is safe.

Security by Design also helps prevent hackers and other bad people from getting access to your information. By building strong protections into the system from the beginning, like encryption and secure passwords, it is much harder for someone to break in and steal your data. This is especially important for kids, because they might not always know when something is not safe.

Role of Government and Regulatory Authorities

The role of government and regulatory authorities in adopting Privacy and Security by Design is crucial for ensuring that AI systems are developed and deployed in ways that protect individuals’ privacy and security from the outset. Governments around the world enact laws and regulations that require organizations to integrate privacy and security principles into their AI technologies. For example, the European Union’s General Data Protection Regulation (GDPR) explicitly requires data protection by design and by default (European Parliament, 2016). This means that organizations must implement appropriate technical and organizational measures to ensure that personal data is processed with the highest privacy standards.

Regulatory authorities, such as the European Data Protection Board (EDPB) and national data protection agencies, play a key role in making sure these laws are followed. They provide guidance, monitor compliance, and enforce regulations through audits and penalties. They also issue recommendations and best practices to help organizations understand how to implement Privacy and Security by Design effectively (EDPB, 2023). For example, they might publish checklists or guidelines that explain how to build privacy and security into new AI products.

In addition to national regulations, governments participate in international cooperation to harmonize privacy standards and promote cross-border data protection. Organizations like the Organisation for Economic Co-operation and Development (OECD) develop guidelines on privacy and security by design that influence global policy (OECD, 2023). Governments also fund research and development initiatives to advance privacy-enhancing technologies and support the creation of standards that facilitate secure AI innovation.

Furthermore, governments play a role in raising public awareness about privacy rights and the importance of secure AI systems. Through public consultations, workshops, and educational campaigns, they engage with stakeholders, including businesses, academia, and civil society, to foster a culture of privacy and security. For example, they might run campaigns to teach kids and their families about safe technology use, or they might hold events where people can learn about their rights and how to protect their information.

Governments also work with other countries to make sure that privacy and security standards are strong everywhere. This is important because AI systems often work across borders, and information can be shared between countries. By working together, governments can help make sure that everyone’s information is protected, no matter where they live.

Role of Organizations and Businesses

Organizations and businesses are at the forefront of implementing Privacy and Security by Design in AI systems. Their role involves embedding privacy and security considerations into every stage of the AI lifecycle, from design and development to deployment and maintenance. This proactive approach helps prevent data breaches, unauthorized access, and other privacy risks.

To achieve this, organizations must establish comprehensive policies that prioritize data minimization, secure data storage, and robust access controls. They should conduct privacy impact assessments (PIAs) and security risk assessments regularly to identify potential vulnerabilities and address them before they can be exploited (IAPP, 2024). For example, before launching a new AI app for kids, a company might check to see what information the app collects, how it is stored, and who can access it. If they find any problems, they can fix them before the app is released.

Training and awareness programs are essential to equip employees with the knowledge and skills needed to uphold privacy and security standards. This includes educating developers on secure coding practices, data scientists on ethical data use, and all staff on recognizing and reporting security incidents. For example, a company might hold workshops where employees learn how to spot phishing emails or how to handle personal information safely.

Organizations also need to appoint dedicated privacy and security officers who oversee compliance with relevant laws and internal policies. These officers coordinate with legal teams, IT departments, and external auditors to ensure that AI systems meet regulatory requirements and industry standards (ISO/IEC 27550, 2019). For example, a privacy officer might review new AI projects to make sure they follow the rules and protect users’ information.

Moreover, businesses must foster a culture of accountability and transparency by documenting data processing activities and providing clear privacy notices to users. They should implement mechanisms for users to exercise their rights, such as data access, correction, and deletion, in compliance with regulations like the GDPR (European Parliament, 2016). For example, if a child or their parent wants to know what information a toy collects, the company should be able to provide a clear and simple explanation.

Finally, organizations should engage in continuous monitoring and auditing of AI systems to detect and respond to emerging threats promptly. This includes adopting advanced security technologies such as encryption, anomaly detection, and incident response frameworks to maintain the integrity and confidentiality of personal data (ENISA, 2021). For example, a company might use special software to watch for unusual activity that could signal a hacker trying to break in.

Role of Vendors and Third Parties

Vendors and third-party service providers play a significant role in the successful implementation of Privacy and Security by Design in AI systems. These external entities often supply critical components such as cloud infrastructure, AI models, data processing services, and security tools that organizations rely on. For example, a company that makes smart toys might buy AI software from another company, or use cloud storage to keep kids’ data safe.

It is essential for vendors to adhere to stringent privacy and security standards to prevent introducing vulnerabilities into the AI supply chain. This includes obtaining relevant certifications like ISO/IEC 27001 for information security management and SOC 2 for service organization controls, which demonstrate their commitment to protecting data (Cloud Security Alliance, 2023). For example, a cloud provider might show customers a certificate to prove that their data is stored securely.

Vendors must also provide transparency about their data handling practices, including how they collect, store, and process personal information. Clear contractual agreements should define responsibilities, data ownership, and compliance obligations to ensure that vendors uphold privacy and security requirements (NIST, 2023). For example, a contract might say that the vendor cannot use kids’ data for advertising.

Regular audits and assessments of third-party vendors help organizations verify that their partners maintain adequate security controls and comply with applicable regulations. This is particularly important in AI, where the complexity of systems and data flows can obscure potential risks (ISACA, 2025). For example, a company might hire an outside expert to check that a vendor’s AI software is safe and private.

Furthermore, vendors should implement privacy-enhancing technologies (PETs) such as data anonymization, encryption, and secure multi-party computation to minimize data exposure. They should also support incident response and breach notification processes to enable timely mitigation of security events (ENISA, 2021). For example, if a hacker tries to steal data, the vendor should have a plan to stop the attack and tell customers quickly.

Collaboration between organizations and vendors is vital for maintaining a secure AI ecosystem. This includes sharing threat intelligence, best practices, and jointly developing solutions to emerging privacy and security challenges (Verasafe, 2025). For example, companies and vendors might work together to create new tools that help protect kids’ information online.

Role of Employees and Internal Teams

Employees and internal teams are critical to the effective adoption of Privacy and Security by Design in AI systems. Their daily actions and decisions directly impact the security posture and privacy compliance of AI technologies.

Developers and data scientists must be trained in secure coding practices, ethical data handling, and privacy principles to build AI models that respect user rights and minimize risks. This includes understanding how to implement data minimization, avoid bias, and ensure model explainability (IAPP, 2024). For example, a developer might learn how to write code that only collects the information needed for a game to work, and nothing more.

Security teams are responsible for conducting vulnerability assessments, penetration testing, and monitoring AI systems for suspicious activities. They play a key role in incident response, helping to contain and remediate breaches or failures promptly (ISACA, 2025). For example, if someone tries to hack into a smart toy, the security team would work to stop the attack and protect kids’ information.

Privacy officers or data protection officers (DPOs) oversee compliance with data protection laws and internal policies. They coordinate privacy impact assessments, manage user data requests, and serve as liaisons with regulatory authorities (ISO/IEC 27550, 2019). For example, a privacy officer might review a new AI project to make sure it follows the rules and protects users’ information.

Cross-functional collaboration among legal, IT, product, and compliance teams ensures that privacy and security considerations are integrated into business processes and decision-making. Regular training and awareness programs help maintain a culture of privacy and security throughout the organization (ENISA, 2021). For example, all employees might attend a workshop on how to keep kids’ data safe.

Employees at all levels should be encouraged to report potential security incidents or privacy concerns without fear of retaliation. Establishing clear communication channels and whistleblower protections supports proactive risk management (IAPP, 2024). For example, if an employee notices something strange happening with an AI system, they should feel safe telling their manager.

Role of Industry Groups and Professional Bodies

Industry groups and professional bodies play a pivotal role in shaping the standards, best practices, and ethical frameworks that guide Privacy and Security by Design in AI. These organizations bring together experts from academia, industry, and government to develop consensus-driven guidelines and certifications.

For example, the Institute of Electrical and Electronics Engineers (IEEE) has developed standards such as IEEE 7010, which addresses ethical considerations in AI system design, including privacy and security aspects (IEEE, 2022). Similarly, the International Organization for Standardization (ISO) provides frameworks like ISO/IEC 27550 for privacy engineering, helping organizations implement privacy by design systematically (ISO/IEC, 2019).

Professional bodies also offer training and certification programs, such as the Certified Information Privacy Professional (CIPP) and Certified Information Systems Security Professional (CISSP), which equip practitioners with the knowledge to implement and audit privacy and security controls effectively (IAPP, 2024). For example, a privacy officer might get a CIPP certificate to show they know how to protect kids’ information.

These groups advocate for responsible AI development by publishing white papers, hosting conferences, and engaging with policymakers to influence legislation and regulation. They also facilitate knowledge sharing and collaboration across sectors, fostering innovation while maintaining privacy and security standards (IEEE, 2022). For example, they might organize events where companies share tips on how to make AI safer for kids.

By setting industry-wide benchmarks and promoting ethical conduct, these organizations help build public trust in AI technologies and encourage widespread adoption of Privacy and Security by Design principles.

Role of International and Multilateral Organizations

International and multilateral organizations play a crucial role in promoting global cooperation and harmonization of Privacy and Security by Design principles in AI. These entities facilitate the development of international standards, guidelines, and frameworks that help countries align their regulatory approaches and foster cross-border collaboration.

The Organisation for Economic Co-operation and Development (OECD) has been instrumental in developing privacy guidelines that emphasize data protection by design and by default, influencing policies worldwide (OECD, 2023). The United Nations has also engaged in AI governance discussions, advocating for human rights-based approaches to AI development, including privacy and security safeguards (UNESCO, 2021).

The International Telecommunication Union (ITU) works on standardizing AI technologies and promoting cybersecurity measures that support Privacy and Security by Design (ITU, 2024). Similarly, the World Economic Forum (WEF) facilitates multi-stakeholder dialogues to address AI risks and promote responsible innovation (WEF, 2023).

These organizations provide platforms for knowledge exchange, capacity building, and technical assistance, especially for developing countries that may lack resources to implement robust privacy and security measures. They also encourage the adoption of privacy-enhancing technologies and ethical AI practices globally.

By fostering international cooperation, these bodies help create a more consistent and effective global environment for AI privacy and security, reducing regulatory fragmentation and enhancing trust across borders.

Role of Consumers and Users

Consumers and users have an important role in driving the adoption of Privacy and Security by Design in AI systems. Their awareness, choices, and feedback can influence how organizations develop and deploy AI technologies.

Informed consumers can demand products and services that prioritize privacy and security, encouraging companies to adopt better design practices. For example, users may prefer AI-powered applications that offer clear privacy settings, data control options, and transparent information about data use (IAPP, 2024). If you are a kid, your parents might help you choose apps that are safe and private.

Users can also exercise their rights under data protection laws, such as requesting access to their data, correcting inaccuracies, or opting out of certain data processing activities. These rights empower individuals to take control of their personal information and hold organizations accountable (European Parliament, 2016). For example, if you find out a toy is collecting too much information, you or your parents can ask the company to delete it.

Feedback mechanisms, such as user surveys, complaint channels, and public forums, provide valuable insights into user concerns and experiences. Organizations can use this input to improve AI system design, address privacy risks, and enhance user trust (ENISA, 2021). For example, if lots of kids say a game is not safe, the company might change how it works.

Educational initiatives aimed at consumers help raise awareness about privacy risks and best practices for safe AI use. This includes understanding the implications of data sharing, recognizing phishing or social engineering attacks, and using privacy-enhancing tools (IAPP, 2024). For example, schools might teach kids how to spot fake emails or how to use strong passwords.

Ultimately, empowered consumers contribute to a market environment where privacy and security are competitive advantages, motivating continuous improvement in AI system design.

Role of Members of the Public

Members of the public play a vital role in shaping the landscape of Privacy and Security by Design through advocacy, education, and participation in policy development. Public opinion and activism can influence lawmakers and organizations to prioritize privacy and security in AI systems.

Civil society organizations and advocacy groups raise awareness about privacy risks and push for stronger regulations and ethical AI practices. For example, groups like the Electronic Frontier Foundation (EFF) campaign for digital rights and transparency in AI development (EFF, 2023). If you or your family care about privacy, you might join a group like this to help make technology safer for everyone.

Public consultations and participatory policymaking processes allow citizens to voice their concerns and contribute to the creation of balanced and effective privacy laws. This engagement helps ensure that regulations reflect societal values and protect vulnerable populations (OECD, 2023). For example, governments sometimes ask the public for their opinions on new privacy laws.

Educational programs and media coverage inform the public about the importance of privacy and security by design, empowering individuals to make informed choices and demand accountability (IAPP, 2024). For example, news stories about data breaches can help people understand why privacy matters.

By fostering a culture of privacy and security, members of the public help create an environment where organizations are motivated to adopt best practices and where AI technologies are developed responsibly.

Role of Artificial Intelligence itself

Artificial Intelligence itself can play a proactive role in supporting Privacy and Security by Design. AI technologies can be designed to automate privacy and security functions, reducing human error and increasing efficiency.

For instance, AI can be used to detect anomalies in data access patterns, flagging potential breaches or unauthorized activities in real time. Machine learning models can identify suspicious behavior faster than traditional methods, enabling quicker incident response (Veale, 2022). For example, if someone tries to log in to a smart toy from a strange location, the AI might notice and block the attempt.

AI can also assist in data anonymization and pseudonymization, transforming personal data to protect identities while preserving utility for analysis. Techniques like differential privacy can be integrated into AI systems to provide mathematical guarantees of privacy (Dwork & Roth, 2014). For example, a research project might use AI to study how kids learn, but only use information that cannot be traced back to any one child.

Moreover, AI can help automate compliance monitoring by continuously checking whether data processing activities align with regulatory requirements and internal policies. This includes generating audit trails and producing reports for regulators (Veale, 2022). For example, an AI system might check every day to make sure a company is following the rules about kids’ data.

However, AI systems must be carefully designed to avoid introducing new risks, such as bias or over-reliance on automated decisions. Human oversight remains essential to ensure that AI supports privacy and security goals effectively and ethically (Veale, 2022). For example, a person should always check to make sure the AI is not making mistakes.

Role of Bad Actors

Bad actors, including hackers, cybercriminals, and malicious insiders, pose significant challenges to the implementation of Privacy and Security by Design in AI systems. Their activities aim to exploit vulnerabilities, steal sensitive data, or disrupt AI operations for financial gain, political motives, or other malicious purposes.

Cyberattacks such as data breaches, ransomware, and supply chain attacks can compromise AI systems and the personal information they process. For example, adversaries may target AI training data to introduce bias or manipulate outcomes, a tactic known as data poisoning (Biggio & Roli, 2018). If a bad person changes how an AI learns, it might start making wrong decisions, like letting a stranger into a smart toy.

Insider threats, where employees or contractors misuse access privileges, can also undermine privacy and security efforts. These individuals may exfiltrate data or sabotage AI models, causing significant harm (Greitzer & Frincke, 2010). For example, an employee might steal kids’ data and sell it to someone else.

Bad actors continuously evolve their techniques, leveraging AI themselves to automate attacks, evade detection, and exploit new vulnerabilities. This arms race necessitates robust, adaptive security measures embedded in AI systems from the design phase (Symantec, 2024). For example, a hacker might use AI to create fake messages that trick people into giving away their passwords.

Understanding the tactics, techniques, and procedures (TTPs) of bad actors helps organizations anticipate threats and develop effective countermeasures. Collaboration between industry, government, and academia is essential to share threat intelligence and improve resilience against malicious activities (ISACA, 2025). For example, companies might share information about new hacking tricks so everyone can protect themselves.

Glossary

Term	Meaning and Example Sentence
Privacy by Design	Building systems to protect data from the start. Example: "Privacy by Design made the app safe for kids by blocking hidden data collection."
Data Minimization	Collecting only needed information. Example: "Data minimization meant the game didn’t ask for your address."
Homomorphic Encryption	Processing data while it’s still scrambled. Example: "Homomorphic encryption let the computer answer questions without seeing private details."
Default Settings	Automatic safety features. Example: "Default settings kept the smartwatch’s camera off until you turned it on."
Zero-Trust Architecture	Verifying every user and device. Example: "Zero-trust architecture made the robot check IDs constantly, like a guard at a castle gate."

Questions

1. What is Privacy and Security by Design, and why is it important for AI systems?

2. How do governments enforce Privacy and Security by Design principles?

3. What roles do organizations and businesses play in implementing these principles?

4. Why is the role of vendors and third parties critical in Privacy and Security by Design?

5. How can employees contribute to maintaining privacy and security in AI systems?

Answer Key

1. Suggested Answer: Privacy and Security by Design means integrating privacy and security protections into AI systems from the start to prevent risks like excessive data collection and unauthorized access (Cavoukian, 2009; ENISA, 2021).

2. Suggested Answer: Governments enforce these principles through laws like the GDPR, which require organizations to implement data protection by design and by default, and through regulatory oversight and penalties (European Parliament, 2016; EDPB, 2023).

3. Suggested Answer: Organizations develop policies, conduct risk assessments, train employees, and implement technical controls to embed privacy and security in AI systems (IAPP, 2024; ISO/IEC 27550, 2019).

4. Suggested Answer: Vendors provide critical AI components and services and must comply with security standards and transparency requirements to prevent supply chain risks (Cloud Security Alliance, 2023; ISACA, 2025).

5. Suggested Answer: Employees contribute by following secure coding practices, participating in training, monitoring systems, and reporting incidents to maintain privacy and security (IAPP, 2024; ISACA, 2025).

References

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