The EU AI Act 

The EU AI Act is one of the first laws in the world designed to regulate AI, setting rules to ensure AI systems are safe, ethical, and respect human rights. It classifies AI systems into four risk categories — from minimal risk to high risk. The stricter the category, the more oversight and compliance are required. The AI Act also outlines use of AI that is prohibited within the EU. Chapter 2, Act 5 of the EU AI Act prohibits the following uses of AI: 

• Using manipulative techniques to distort behavior and impair informed decision-making, causing significant harm;
• Exploiting vulnerabilities related to age, disability, or socio-economic status to distort behavior, causing significant harm;
• Inferring sensitive attributes (e.g., race, political opinions, sexual orientation) through biometric categorization, except for lawful purposes;
• Social scoring that leads to detrimental treatment based on social behavior or personal traits;
• Assessing criminal risk solely based on profiling or personality traits, unless supporting human assessments based on objective facts;
• Compiling facial recognition databases by scraping images from the internet or CCTV footage;
• Inferring emotions in workplaces or educational institutions, except for medical or safety reasons; and
• ‘Real-time’ remote biometric identification in public spaces for law enforcement, with exceptions for serious cases like missing persons or imminent threats.

There are also special considerations and requirements for the development or use of high risk AI systems, which are classified as such in Chapter 3 of the EU AI Act which could result in the necessity of a risk management system. Risk management systems are frameworks for identifying, mitigating, and managing AI-related risks, especially regarding discrimination and data breaches.

Lastly, the providers of General Purpose AI systems (GPAI) are subject to special requirements under Chapter 5. 

Important Principles for Ethical AI Policies to Address

When developing ethical AI, it is important to emphasize fairness, accountability and transparency. It is not just important in the development of AI systems but the use of AI systems. In essence, ethical AI is about ensuring that as AI technology advances, it does so in a way that respects human dignity, promotes fairness, and fosters trust, ultimately contributing to the well-being of individuals and society as a whole. 

Fairness

The primary objective of a fairness policy is to eliminate algorithmic bias and ensure that AI decision-making processes treat all individuals equitably. An AI policy should include comprehensive protocols such as fairness assessments, regular bias audits, and data diversity requirements during the training phases of AI systems. By mandating AI fairness testing before deployment and continuously monitoring systems for potential biases, organizations can proactively address and mitigate any unfair treatment. For instance, consider the case of Amazon’s AI recruitment tool, which was found to exhibit bias in hiring practices against women; this highlighted the necessity of implementing bias mitigation policies in AI-driven recruitment processes to ensure equitable outcomes.

Accountability

Establishing clear lines of responsibility for AI decision-making is crucial to ensuring human oversight and accountability. An AI policy should address the issue of accountability by defining specific roles and responsibilities within the organization for the oversight of AI systems. This includes establishing audit trails to track decisions and requiring regular reviews of AI outputs to ensure accountability. As Data Officers, TechGDPR can help in the development of these policies. Since the role of Data Officer involves data governance, we can help ensure oversight for your organization to maintain control over AI systems and understand their impact on decision-making processes.

Transparency

Transparency in AI systems is essential for building trust among users and complying with regulatory demands. The principle of transparency is also mentioned in Art.12 GDPR. An AI policy should be transparent and include protocols that mandate the use of explainable AI models, thorough documentation of decision-making processes, and clear disclosures in privacy notices regarding AI-driven data usage. A good AI policy should require organizations to provide stakeholders with comprehensible explanations for AI-driven decisions, ensuring that the operations of AI systems are understandable to both users and regulators. Organizations that adopt explainable AI frameworks such as the OECD Transparency and Explainability Principle, for example, can better maintain transparency and meet regulatory requirements, fostering trust and accountability in their AI applications.

The Role of Data Officers in Ethical AI Policy Creation

Data Officer is a new service provided by TechGDPR in which we can help with AI compliance as well as serving as a Data Protection officer, a role which can be mandated by the GDPR. Instead of having multiple people filling these roles, a Data Officer can understand how to navigate everything for your peace of mind. It is not a traditional role for privacy or AI compliance but this innovative role can alleviate stress for how to navigate multiple regulations including the AI Act as it is so new. 

Conclusion

In conclusion, as AI continues to permeate various industries, ensuring its ethical use is paramount. The EU AI Act lays out new legal requirements for AI systems and multiple frameworks including the OECD emphasizing the need for fairness, accountability, and transparency which can be done through the creation of AI policies. Organizations must not only comply with these regulations but also proactively adopt ethical AI practices to build trust and mitigate risks.

TechGDPR’s Data Officer service offers a comprehensive solution, integrating AI compliance with data protection and privacy governance. By crafting and implementing tailored AI policies, a Data Officer can ensure that your organization’s AI systems are not only legally compliant but also ethically sound, fostering a responsible approach to AI development and usage. As the landscape of AI regulation evolves, partnering with a Data Officer will be crucial in navigating these complexities and maintaining your organization’s commitment to ethical AI.

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Risks of using AI

Although the use of AI shows a great deal of potential, it has also been proven to cause a number of harms. For example, the Future of Privacy Forum 2017 identified the possibility of two main categories of harm: individual and collective/societal harms. These are further subdivided into whether they are deemed unfair or downright illegal. Categories of examples are also identified e.g. loss of opportunity, including mostly instances of discrimination, such as the case of the Amazon AI tool, resulting in employment discrimination for women. In addition to harm to the person, AI could also cause harm to the environment due to the high consumption of energy, and organizational harms to those companies that might incur penalties, financial losses and a damage to reputation due to the unlawful or wrong use of AI systems.

Mitigating the risks

Each risk identified above might have its own individual mitigation strategy. However, one all-encompassing way to ensure that an AI system is developed or used causing the least amount of harm possible is building trustworthy and ethical AI from the get-go, and in turn, only use systems guaranteed to be ethical and trustworthy.

A common problem with AI and its associated risk is the fact that it might operate as a black-box, without any transparency and/or fairness in its decision making and ultimately, its output. Overtime, a multitude of supervisory bodies and organizations have developed frameworks and standards in order to define what it means for an AI system to be ethical.

Ethical AI

There are a multitude of frameworks that highlight what is required for an AI system to be ethical. Some of these include, the UNESCO Recommendation on the Ethics of AI, the Council of Europe’s Report “Towards Regulation of AI Systems”, the NIST guidance and the OECD AI Principles, amongst many others. Taking the latter as an example, the list of principles to uphold in order to ensure that an AI system is operating ethically include: 

• Inclusive growth, sustainable development and well-being,
• Human-centered values and fairness,
• Transparency and explainability,
• Robustness, security and safety, and
• Accountability.

In order to follow these principles, an organization needs to consider, among others: 

• Establishing policies and procedures in order to ensure legal review of the development and/or use of the AI system, ensuring fairness, transparency and accountability. For example, policies that cover unfair bias. 
• Implementing principles and processes related to privacy and data protection, such as obtaining consent from individuals whose data is processed by AI, indicating this information in the privacy notice, implementing technical safeguards for the data etc., ensuring transparency and security. 
• Ensuring the quality and integrity of data through the implementation of a data governance system, as it relates to the data used to train the models.

This is also only based on ethical frameworks and guidance published by international bodies and organizations. Additional legal requirements are also anticipated in this regard, especially within the EU market, in light of the EU AI Act, which has been passed and set to come into force starting August 1st, 2024.  Organizations have, therefore, a long way to go to prepare for ensuring that their AI system, or one they are using, is up to code with these requirements and ethical principles.

Efficiently operating an ethical AI system

Navigating all the required best practices, guidance and soon-to-come legally binding regulations can be a daunting task, especially on top of developing and/or utilizing new AI systems. Many departments need to be involved in the process of ensuring that policies and procedures are in place, that they are implemented in practice and monitored to ensure they actually have the intended effect of creating and/or utilizing AI systems in the most ethical way possible.

Adding these requirements on top of existing regulations related to privacy, data protection, information security, and data management, means adding additional load to individuals responsible for the management of compliance. However, TechGDPR can support lightening that load by entrusting it with your compliance needs and appointing it as your externally-sourced Data Officer.

A Data Officer merges the roles in data protection, compliance, ethics, and privacy into one dynamic position. This role also transcends traditional boundaries, ensuring your organization’s data practices adhere to legal standards like GDPR and CCPA, while aligning with ethical guidelines, especially in AI. With a Data Officer, organizations are able to navigate complex data landscapes with ease, transforming data challenges into strategic opportunities.

What the Data Officer can do to ensure ethics are always considered in the use of AI

The Data Officer service by TechGDPR is designed to provide your organization with the expertise and support necessary to navigate the stringent requirements in using personal data, Artificial Intelligence and other EU-based data requirements by integrating responsibilities in data protection, compliance, ethics, and privacy into a multifaceted role.

This position ensures that organizations’ data practices comply with regulations such as GDPR and CCPA, while also adhering to ethical standards, particularly in AI. In fact, our service provides comprehensive supervision over AI ethics and regulatory compliance, ensuring that your AI implementations adhere to the highest standards of responsibility and legality, such as the ethical regulatory requirements of the EU AI Act.

TechGDPR continuously keeps up-to-date with and makes use of guidelines and assessments provided by supervisory authority such as the pilot Trustworthy AI Assessment List by Spain’s AEPD, which includes sections assessing explainability, non-discrimination, environmental sustainability and accountability, amongst others, covering all relevant principles of Ethical AI as listed in the previous paragraphs. Therefore, as a Data Officer, it is the best position to understand and assess all regulatory requirements related to the use of Artificial Intelligence.

Conclusion

While AI presents immense opportunities for businesses, it also brings significant risks that require careful management. Ensuring ethical and trustworthy AI systems is crucial to mitigating potential harms, including discrimination, environmental impact, and regulatory penalties. Organizations can navigate this complex landscape by adhering to established ethical frameworks and leveraging the expertise of TechGDPR as a Data Officer, who can integrate compliance, data protection, and ethical considerations. By doing so, businesses not only comply with emerging regulations, but can also position themselves as responsible and forward-thinking leaders in the AI space.

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