AI is at a critical juncture with regulators finally catching up to the previously unchecked development of AI technologies. This shift requires companies to adopt a proactive attitude towards AI governance, moving beyond mere compliance to building ethical, trustworthy systems. Regulation is a response to emerging risks associated with AI, notably from large language models, which have brought about increased scrutiny after high-profile incidents revealed ethical lapses. Governments are establishing laws like the EU AI Act and the U.S. AI Executive Order to ensure responsible innovation while balancing risk.
Ultimately, regulatory compliance is not just about avoiding penalties. It's about building AI systems that are trustworthy, ethical, and sustainable. Companies that approach AI governance this way will be the ones that come out on top.
Advances with large language models (LLMs) pose new kinds of risks that are not limited to embedded stereotypes, toxicity, prompt injection, sycophancy, and deepfakes.
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