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Responsible Data Use in an Age of AI
As the world becomes increasingly reliant on artificial intelligence (AI), it’s essential for businesses to adopt responsible data use practices to ensure compliance with regulations and maintain public trust. The EU AI Act, which sets international rules for AI development and use, marks a significant shift towards a more regulated approach to AI deployment.
However, as the act takes shape, it’s clear that many elements are still open to interpretation, leaving businesses struggling to maintain compliance and handle data responsibly. As someone who has witnessed these challenges firsthand, I firmly believe that striking a balance between regulatory compliance and continued innovation is crucial for both safety and progress in the evolving world of AI.
One critical aspect of this responsible data use is ensuring transparency obligations. According to the EU AI Act, foundational AI models must comply with transparency requirements, meaning users must be informed when interacting with AI systems. This means that companies using AI must prioritize clarity and openness when dealing with end-users.
Another crucial step in responsible data use is the ethical collection of data. As AI relies heavily on data feeds, ensuring the secure and responsible collection of this information is essential for innovation. Compliance with regulations like GDPR and the EU AI Act goes beyond mere adherence to rules; it’s about creating systems that are both ethical and secure.
To achieve this compliance, businesses must establish a clear framework for data governance that aligns with the EU AI Act and GDPR requirements. This includes outlining roles, responsibilities, and protocols for handling data. It’s also vital to only collect data necessary to achieve your purpose and avoid unnecessary collection, which can put both users’ privacy and security at risk.
When it comes to AI risk assessments, a structured approach is essential. This involves identifying AI systems and data usage, cataloging all processing activities, and understanding the data being used and its intended outcomes. A multidisciplinary team must be involved in this process to provide diverse perspectives on risks and mitigation strategies. Moreover, an ongoing monitoring approach is necessary to continually reassess risks as AI systems evolve and regulatory landscapes change.
Furthermore, companies should not underestimate the importance of human oversight in AI decision-making. Establishing a centralized team with legal and technical experts can help ensure accountability and protect end-users’ interests.
Finally, it’s essential to prioritize employee training on compliance requirements and best practices in AI and privacy legislation. Without proper understanding and awareness among employees, businesses may inadvertently compromise data security or violate regulations.
As the world continues to rely more heavily on AI, it’s our responsibility as business leaders to ensure responsible data use practices that not only protect users but also foster innovation.
Source: https://www.forbes.com/councils/forbestechcouncil/2025/03/27/responsible-data-use-in-an-age-of-ai/
