Artificial Intelligence Legislation and Controls
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Generative AI, a technology that can create various types of content, such as texts, images, audio, and source code, is gaining attention in the tech sector. As it operates in sectors with regulatory requirements, ensuring compliance becomes paramount, especially in critical areas like finance and healthcare.
In these sectors, the regulatory focus centres on risk-based oversight, transparency, data protection, and ethical use. The EU AI Act, the world’s first comprehensive AI-specific regulation, significantly shapes these obligations. It categorizes AI systems into four risk levels, with finance and medical AI applications frequently deemed "high-risk" due to their potential impact on safety and fundamental rights.
Key challenges related to generative AI regulatory compliance include customization complexities, data sovereignty and residency, auditability and transparency, ethical governance, and intellectual property challenges. For instance, defining when a custom model becomes a “new” AI provider subject to full obligations can be complex. Compliance with data locality laws can be complicated when using cloud-based generative AI solutions that operate across borders. Maintaining detailed logs and records of AI training data and decision-making processes is critical during regulatory audits.
In finance, the EU AI Act places fintech AI tools like credit scoring, fraud detection, robo-advisors, and algorithmic trading under "high-risk," imposing stringent requirements on transparency, data quality, and accountability that directly impact fintech innovation and operations worldwide.
Businesses must proactively manage risks, ensure transparency, protect data, continuously monitor, and adapt to jurisdiction-specific legal frameworks to deploy generative AI technologies compliantly, safely, and ethically.
For more insights on the legal and governance issues of generative AI, you can refer to the article published by the British Polish Chamber of Commerce here.
It's essential to remember that using generative AI in customer-facing applications can lead to intellectual property challenges. Interaction with customers can limit access to an organization's internal data for personalized deployment of generative AI. As the EU AI Act regulation expands, these obligations are likely to increase.
In conclusion, navigating the regulatory landscape of generative AI, particularly in finance and healthcare, requires a proactive approach, understanding of evolving laws, and a commitment to compliance, transparency, and ethical use.
In the finance sector, intellectual property challenges may arise when using generative AI in customer-facing applications, as interaction with customers can limit access to an organization's internal data for personalized deployment. As the EU AI Act regulation expands, these intellectual property obligations are likely to increase.
To deploy generative AI technologies compliantly, safely, and ethically in sectors with regulatory focus, such as finance and healthcare, businesses must continuously monitor and adapt to jurisdiction-specific legal frameworks, including considering intellectual property implications of using AI in customer interactions.
