{"id":10510,"date":"2025-03-04T08:30:55","date_gmt":"2025-03-04T07:30:55","guid":{"rendered":"https:\/\/lcloud.pl\/?p=10510"},"modified":"2025-02-24T15:02:12","modified_gmt":"2025-02-24T14:02:12","slug":"legal-regulations-and-genai-how-to-prepare","status":"publish","type":"post","link":"https:\/\/lcloud.pl\/en\/legal-regulations-and-genai-how-to-prepare\/","title":{"rendered":"Legal regulations and GenAI. How to prepare?"},"content":{"rendered":"

Generative Artificial Intelligence (GenAI)<\/span> can analyze data and create new content\u2014text, images, code, or music\u2014offering vast opportunities for any organization. However, to effectively deploy GenAI solutions, it is essential to review guidelines and legal regulations right from the planning stage. Doing so helps prevent potential non-compliance issues and ensures adherence to current legislation.<\/span><\/strong><\/p>\n

Below, we will explore the key recommendations from Amazon Web Services and then move on to other regulations that support the creation of a GenAI usage policy within your organization.<\/span><\/p>\n

AWS Recommendations<\/b><\/span><\/h2>\n

Implementing any large-scale technology is a complex process, especially in the rapidly evolving field of artificial intelligence. Although each transformation is unique, there are proven methods for effectively deploying GenAI. One is the collection of best practices from Amazon Web Services, known as <\/span>AWS CAF-AI.<\/span><\/span><\/span><\/p>\n

Defining goals and scope<\/b><\/span><\/h3>\n

Organizations must clearly determine in which areas they plan to implement Generative AI solutions and the objectives they wish to achieve. Common goals include improving operational efficiency, optimizing processes, reducing the time to introduce new solutions, and increasing customer satisfaction. The most important step is identifying which departments and processes will be covered by the GenAI policy.<\/span><\/p>\n

Testing and monitoring GenAI systems<\/b><\/span><\/h3>\n

Each model and solution should be tested to ensure compliance with the company\u2019s internal standards and applicable regulations. The policy should specify which tools are approved for use and how to monitor their performance after implementation.<\/span><\/p>\n

Risk management and regulatory compliance<\/b><\/span><\/h3>\n

A GenAI policy needs to include a detailed risk management plan aligned with requirements such as GDPR and the AI Act. This plan should consider how to classify GenAI systems by risk level, as well as outline procedures to ensure model transparency and impartiality. Maintaining data protection and preventing discrimination are essential.<\/span><\/p>\n

Employee training and engagement<\/b><\/span><\/h3>\n

For a GenAI implementation to be effective, employees must understand how to use this technology ethically and securely. The policy should include training programs for both managers and technical teams responsible for deploying and maintaining GenAI systems. This promotes a thorough understanding of the benefits and risks associated with GenAI.<\/span><\/p>\n

Ethical use of GenAI<\/b><\/span><\/h3>\n

A critical part of a GenAI policy involves establishing ethical guidelines for using generative AI. This covers transparent communication with customers, ensuring model impartiality, and aligning with the company\u2019s core values. Building trust in GenAI\u2014both for employees and customers\u2014is vital for long-term success.<\/span><\/p>\n

Data management and GDPR compliance<\/b><\/span><\/h3>\n

Deploying Generative AI requires a robust data management strategy. GenAI solutions cannot function effectively without high-quality data, so the policy must include guidelines for data collection, storage, and processing, as well as protocols to ensure data security and quality. As organizations using GenAI handle personal data, adherence to data protection regulations\u2014particularly GDPR\u2014is crucial, especially when training GenAI models.<\/span><\/p>\n

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AWS Cloud Adoption Framework for Artificial Intelligence<\/span><\/figcaption><\/figure>\n

Developing a policy governing the use of Generative AI is extremely important for any organization. Such a policy fosters customer and employee trust through the ethical and transparent use of GenAI capabilities, which in turn enhances business relationships and outcomes. It also supports risk management by reducing the likelihood of legal and operational issues, for example those related to privacy violations or insufficient algorithm transparency.<\/span><\/p>\n

How does the law respond to GenAI?<\/b><\/span><\/h2>\n

The next step involves understanding the legal regulations. Below are some key institutions and legal frameworks.<\/span><\/p>\n

AI Working Group (GRAI)<\/b><\/span><\/h3>\n

Created to promote an environment conducive to AI development in both the public and private sectors in Poland, this open-format group brings together a broad representation of the market. Its objective is to support businesses in safely and effectively deploying AI according to best practices and existing legislation. GRAI also provides guidelines to help firms grasp the standards for ethical and transparent AI use, ensuring compliance with legal requirements. The group\u2019s findings are published on the Polish AI Portal.<\/span><\/p>\n

EU AI Act<\/b><\/span><\/h3>\n

The <\/span>EU AI Act<\/span> is the world\u2019s first comprehensive legislative framework regulating artificial intelligence. It goes into partial effect in 2025 and will be fully implemented by 2027. Under the act, AI systems are classified by risk level, with stringent requirements for high-risk systems concerning safety and transparency:<\/span><\/span><\/p>\n