The document explains that AI offers major benefits but raises concerns around bias, transparency, safety, and data misuse, especially in healthcare. It stresses that trustworthy AI must be lawful, ethical, and robust, supported by principles such as security, privacy, fairness, human centricity, transparency, and scientific rigor. Pages 6–10 outline these pillars, while page 11 shows Quantiphi’s lifecycle framework integrating responsible AI into every stage, from data collection to deployment and monitoring. The paper concludes that building trust requires clear governance, explainability, continuous auditing, and a commitment to socially beneficial outcomes.

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