As the use of AI becomes more widespread, companies need to be proactive in assessing their AI applications to ensure compliance with regulations. It is essential for businesses to determine if their AI usage falls under regulated categories and have AI managers in place to ensure that necessary expertise is present within the organization.
Companies must also consider the European legal framework when planning AI projects. Examining who will be utilizing AI tools and the risks they may pose to employees, customers, or external parties is crucial. Prohibited uses of AI, such as emotion recognition in the workplace, need to be avoided to comply with regulations.
High-risk applications of AI, such as in education or human resources management, come with additional obligations like risk and impact assessments. Transparency rules require AI-generated content to be labeled, and users must be informed if they are interacting with artificial intelligence. The potential risk of fines for non-compliance with regulations is significant for companies, with fines ranging up to 35 million euros or 7% of annual turnover.
It is also important for companies that purchase AI systems from third parties to understand the risks associated with these systems and implement appropriate measures to mitigate them. In cases of damages like copyright infringements, companies may seek recourse against the manufacturers, although enforcement may be challenging, especially with manufacturers from the USA or China.
Providers of AI systems must disclose basic functions and training data for their models to comply with European regulations. The details of compliance will likely be determined through court decisions in a manner similar to data protection regulations. Adhering to these regulations is crucial for companies to avoid potential fines and legal repercussions.
In conclusion, companies need to take proactive measures when it comes to assessing their AI applications and ensuring compliance with regulations. They should have an understanding of the potential risks associated with high-risk applications and take steps to mitigate them while also being transparent about their use of artificial intelligence. Failure
