The European Union (EU) is currently in the process of drafting a new law on artificial intelligence (AI), which is expected to have significant implications for businesses that deploy AI in their operations. One of the key issues that the law is expected to address is data protection and privacy, which is a particularly important concern for businesses that rely on AI to process large amounts of personal data.
One of the main ways in which the EU AI law is expected to impact businesses is by setting out clear rules and guidelines on the collection, use, and sharing of personal data for AI purposes. This could include requirements for obtaining explicit consent from individuals before collecting their personal data, as well as restrictions on the use of personal data for purposes that are not clearly outlined in the consent process.
Another potential impact of the EU AI law on businesses is the need to implement robust data protection measures to ensure that personal data is handled securely. This could involve measures such as encrypting personal data, implementing access controls, and conducting regular security assessments. Businesses may also be required to put in place procedures for handling data breaches, including reporting any breaches to the relevant authorities and taking steps to mitigate the impact on individuals whose data has been compromised.
There are a few key ways that businesses can stay informed about the details of the impending EU AI law and ensure that they are in compliance with its provisions:
- Monitor updates and announcements: As the EU AI law is being developed, it is important to stay up-to-date on any updates or announcements that are made about its provisions. This could include monitoring the websites of relevant EU institutions, such as the European Commission, as well as subscribing to newsletters or alerts from organizations that track developments in the field of AI.
- Participate in consultations and workshops: The EU AI law is expected to be developed through a process of consultation and engagement with stakeholders, including businesses, governments, and civil society organizations. Businesses can stay informed and have a say in the development of the law by participating in relevant consultations and workshops.
- Seek legal advice: Businesses may also want to consider seeking legal advice in order to understand the implications of the EU AI law for their operations and to ensure that they are in compliance with its provisions. Legal professionals with expertise in AI and data protection can help businesses to understand their obligations under the law and to put in place appropriate measures to meet those obligations.
- Develop internal policies and procedures: To ensure compliance with the EU AI law, businesses may also want to consider developing internal policies and procedures that outline how personal data is collected, used, and shared for AI purposes. This could include procedures for obtaining consent from individuals, as well as procedures for handling data breaches and responding to requests from individuals to exercise their rights in relation to their personal data.
It is important to note that the EU AI law is not expected to be a blanket ban on the use of personal data for AI purposes. Instead, it is expected to set out clear rules and guidelines that businesses must follow in order to ensure that personal data is used in a way that is ethical, transparent, and accountable. This could include requirements for businesses to provide individuals with clear and concise information about how their personal data will be used, as well as the rights that individuals have in relation to their personal data.
There are a number of ways that a company can use technology to operationalize internal policies and procedures related to the EU AI law and data protection. Some examples might include:
- Implementing consent management systems: A company can use technology to implement consent management systems that allow it to obtain explicit consent from individuals before collecting their personal data. This could involve using online forms or other tools to capture consent, as well as tracking and recording consent in a way that allows the company to demonstrate compliance with the EU AI law.
- Implementing access controls: A company can use technology to implement access controls that restrict access to personal data to only those individuals who are authorized to access it. This could involve using passwords, two-factor authentication, or other security measures to control access to data.
- Encrypting personal data: A company can use technology to encrypt personal data in order to protect it from unauthorized access or misuse. This could involve using encryption algorithms to encode data, as well as implementing measures to ensure that only authorized individuals are able to decrypt the data.
- Implementing data protection and privacy by design: A company can use technology to build data protection and privacy into the design of its AI systems from the outset. This could involve using privacy-enhancing technologies, such as differential privacy, to protect personal data, as well as designing AI systems in a way that minimizes the collection and use of personal data.
- Conducting regular security assessments: A company can use technology to conduct regular security assessments in order to identify vulnerabilities in its systems and processes and to put in place measures to address those vulnerabilities. This could involve using security tools and software to scan for vulnerabilities, as well as implementing measures such as installing security patches and updating software to address identified risks.
Why use technology to operationalize internal policies and procedures?
There are several key advantages to using technology to operationalize internal policies and procedures related to the EU AI law and data protection:
- Efficiency: Using technology to operationalize internal policies and procedures can help to streamline processes and make them more efficient. For example, implementing a consent management system can help to automate the process of obtaining consent from individuals, which can save time and resources.
- Accuracy: Technology can help to ensure that internal policies and procedures are followed accurately and consistently. For example, using access controls to restrict access to personal data can help to prevent unauthorized access or misuse of data.
- Scalability: Technology can help to scale internal policies and procedures to meet the needs of a growing business. For example, implementing a data protection and privacy by design approach can help a company to ensure that its AI systems are designed to protect personal data as the company expands.
There are a number of technology solutions that lead the market in terms of helping companies to operationalize internal policies and procedures related to the EU AI law and data protection. Some examples might include:
- Consent management platforms: These platforms can help companies to obtain, track, and manage consent from individuals in a way that is compliant with the EU AI law. Examples of consent management platforms include OneTrust, TrustArc, and Termly.
- Data encryption tools: These tools can help companies to encrypt personal data in order to protect it from unauthorized access or misuse. Examples of data encryption tools include Symantec Encryption, McAfee Encryption, and VeraCrypt.
- Data protection and privacy by design tools: These tools can help companies to design AI systems in a way that minimizes the collection and use of personal data, and that incorporates privacy-enhancing technologies such as differential privacy. Examples of data protection and privacy by design tools include Microsoft's DP-100 Exam and the Privacy by Design Foundation's Privacy by Design Certificate.
- Security assessment tools: These tools can help companies to conduct regular security assessments in order to identify vulnerabilities in their systems and processes and to put in place measures to address those vulnerabilities. Examples of security assessment tools include Rapid7, Qualys, and Tenable.
Overall, the impending EU AI law is expected to have significant implications for EU businesses that deploy AI in their operations, particularly in terms of data protection and privacy. It will be important for businesses to stay informed about the details of the law as it is developed and to ensure that they are in compliance with its provisions in order to avoid potential fines and other penalties.
