THE TECHNOLOGY INTERVIEW
“ Gen AI doesn ’ t have to be complex , but there is much to consider to get it right ”
Consider an insurance company using generative AI to forecast claim amounts for its policyholders . When the policyholders receive the claim amounts , the insurer needs to be able to explain the reasoning behind how they were estimated , making transparency and explainability fundamental .
Due to the complex nature of AI algorithms , achieving explainability can be a challenging but essential part of ensuring responsible AI . Organisations can achieve this by investing in explainable AI techniques ( e . g ., data visualisation or decision tree ), providing thorough documentation , and fostering open communication about the AI decision-making processes .
Privacy is another crucial consideration for responsible AI implementation . Imagine a healthcare organisation leveraging generative AI to predict patient outcomes based on electronic health records . Protecting the privacy of individuals is a must-have , top priority . Generative AI can inadvertently reveal sensitive information or generate synthetic data resembling real individuals .
To address privacy concerns , businesses can implement best practices like data anonymisation , encryption and privacy-preserving AI techniques , such as differential privacy . Concurrently , organisations must remain compliant with data protection regulations such as the General Data Protection Regulation ( GDPR ) and the Health Insurance Portability and Accountability Act ( HIPAA ).
Finally , the evolving regulatory landscape for AI technologies demands a robust governance framework that guides ethical and responsible AI deployment .
Organisations can refer to resources like the European Parliament ’ s Artificial Intelligence Act : or The Bletchley Declaration to help define AI policies and principles . Establishing cross-functional AI ethics committees and developing processes for monitoring and auditing AI systems can help organisations stay ahead of regulatory changes . By adapting to regulation changes and proactively addressing potential risks , organisations can demonstrate their commitment to responsible AI practices .
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