AI Accountability: Responsibility When AI Goes Wrong

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Decoding AI Risk

Fortanix

9 episodes

1 day ago

Decoding AI Risk explores the critical challenges organizations face when integrating AI models, with expert insights from Fortanix. In each episode, we dive into key issues like AI security risks, data privacy, regulatory compliance, and the ethical dilemmas that arise. From mitigating vulnerabilities in large language models to navigating the complexities of AI governance, this podcast equips business leaders with the knowledge to manage AI risks and implement secure, responsible AI strategies. Tune in for actionable advice from industry experts.

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AI Accountability: Responsibility When AI Goes Wrong

Decoding AI Risk

5 minutes 29 seconds

6 months ago

AI Accountability: Responsibility When AI Goes Wrong

In this episode, we tackle one of the most pressing questions in today’s AI-driven world: Who’s responsible when generative AI gets it wrong?

As enterprises increasingly adopt GenAI for productivity, content creation, and analytics, the stakes rise just as fast. But with those benefits come real challenges—AI hallucinations, misinformation, data privacy breaches, and regulatory risks.

We dive into the rising concerns surrounding AI-generated falsehoods and the legal, ethical, and reputational fallout for businesses.

Who should be held accountable—CISOs, compliance officers, AI developers, or executive leadership? The truth is, responsibility is shared—and avoiding risk means building strong governance from the ground up.

This episode explores the urgent need for AI accountability frameworks, Zero Trust principles in AI deployments, and the role of advanced platforms in securing data, governing models, and preventing harmful outputs.

If you're wondering how to use GenAI safely and responsibly—this conversation is a must-listen and check out the Zero Trust AI platform for secure and compliant GenAI deployments.