Ensuring AI safety in critical fields
PCQuest|November, 2023
Uncover the nuanced strategies ensuring AI safety in healthcare and cyber-security. Address bias, safeguard patient privacy, and secure AI-driven chatbots. Discover the pivotal role of governance frameworks, data measures, and people involvement in achieving ethical AI practices
Ashok Pandey
Ensuring AI safety in critical fields

In the rapidly advancing landscape of Artificial Intelligence (AI), ensuring the safety of AI systems, particularly in critical sectors like healthcare and cybersecurity, is paramount. The convergence of technological prowess and ethical considerations has brought forth challenges that demand a comprehensive approach.

▾ Guaranteeing Safety in Healthcare and Cybersecurity

Addressing Bias and Discrimination – Responsible AI implementation in healthcare and cybersecurity begins with acknowledging and mitigating biases. Training AI models on diverse and representative datasets becomes a crucial step to avoid biased outcomes that could perpetuate discrimination.

Protecting Patient Privacy – Healthcare organizations, dealing with sensitive patient data, must prioritize robust data protection measures. Transparency in data usage, encryption, and strict access controls are essential components to safeguard patient privacy against potential breaches.

This story is from the November, 2023 edition of PCQuest.

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This story is from the November, 2023 edition of PCQuest.

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