AI compliance refers to the adherence to rules, standards and regulations related to artificial intelligence (AI) and machine learning (ML).
The concept is intended to ensure that AI systems and applications operate in accordance with ethical, legal and social standards.
The rapid development of AI technologies has compelled companies, research organisations and regulatory bodies to pay increased attention to the necessity to ensure that AI systems are developed or deployed in a responsible and ethical manner.
AI compliance may entail the following elements:
- Data protection and security: Ensuring the protection of personal data and secure handling of information in accordance with data protection regulations.
- Transparency: Clear communication as to how AI models work, what data they use and what decisions they make in order to promote trust and understanding.
- Fairness and bias: Avoidance of discriminatory or biased results through careful selection and processing of training data.
- Accountability: Clear assignment of responsibilities for the use of AI systems and mechanisms for tracking and reviewing decisions.
- Security and robustness: Ensuring AI systems are protected against attacks and can function reliably under various conditions.
- Legal conformity: compliance with the relevant legal provisions and regulations concerning the use of AI technologies.
- Ethics and social and environmental compatibility: Consideration of ethical principles and social and environmental impacts in the development and application of AI technologies.
AI compliance is particularly important to promote trust among users, customers and society as a whole in AI systems and to minimise potential risks and challenges. Companies must carefully monitor, evaluate and, if necessary, adapt their AP applications in order to ensure responsible use.
