Responsible AI Principles for Hindustan Pharma: Serving Lives with Integrity

Upholding Trust, Ethics, and Community Well-being in the AI Era

Title Slide & Introduction

    Main Title

    Responsible AI Principles: Serving Lives with Integrity

    Subtitle

    Upholding Trust, Ethics, and Community Well-being in the AI Era

    Alignment

    AI Aligned with Hindustan Pharma’s Mission: 'Connect People and Communities by Serving Lives'

    Presenter

    [Your Name/Department]

    Date

    [Date]

    Principles 1 & 2 – Ethical Core & Patient Focus

      Principle 1: Ethical AI by Design

      Ensure all AI systems adhere to the highest ethical standards: Fairness, Transparency, and Integrity

      Example for Principle 1

      Regularly audit AI-driven diagnostic support tools to ensure they do not discriminate based on race, gender, or region

      Execution for Principle 1 - 1

      Establish an AI Ethics Review Board

      Execution for Principle 1 - 2

      Integrate ethical checklists and bias assessment protocols

      Execution for Principle 1 - 3

      Mandatory ethics training for all AI teams

      Principles 1 & 2 – Ethical Core & Patient Focus

        Principle 2: Patient and Community-Centric AI

        Prioritize community well-being, affordability, and access in AI solutions

        Example for Principle 2

        Use AI to optimize drug distribution to remote areas, identifying underserved populations and predicting demand spikes

        Execution for Principle 2 - 1

        Deploy AI for supply chain optimization, targeting last-mile delivery

        Execution for Principle 2 - 2

        Engage communities in pilot studies for real-life impact assessment

        Key Focus

        This principle aligns AI with Hindustan Pharma's mission to serve lives inclusively

        Principles 3 & 4 – Quality, Trust, and Accountability

          Principle 3: Data Quality and Model Reliability

          Guarantee the accuracy, reliability, and consistency of AI outputs

          Example for Principle 3

          Implementing strict quality controls on AI models that predict drug impurities, ensuring results meet global safety norms each time

          Execution for Principle 3 - 1

          Cross-functional QA teams review models before launch

          Execution for Principle 3 - 2

          Real-time monitoring dashboards to flag anomalies and model drift

          Execution for Principle 3 - 3

          Continuous retraining using clean, up-to-date data

          Principles 3 & 4 – Quality, Trust, and Accountability

            Principle 4: Trust, Transparency, and Accountability

            Be transparent in how AI systems operate and hold teams accountable for decisions

            Example for Principle 4

            Provide audited logs and Explainable AI (XAI) outputs to regulators and stakeholders for automated pharmacovigilance

            Execution for Principle 4 - 1

            Implement 'explainability modules' for non-technical users

            Execution for Principle 4 - 2

            Publicly document AI use cases, risks, and mitigations

            Execution for Principle 4 - 3

            Maintain full traceability throughout the AI lifecycle

            Principles 5 & 6 – Growth and Sustainability

              Principle 5: Inclusive and Sustainable Innovation

              Leverage AI for continuous innovation, valuing diversity, and driving positive societal and environmental outcomes

              Example for Principle 5

              Apply AI to develop eco-friendly manufacturing processes or identify drug formulations that reduce environmental impact

              Execution for Principle 5 - 1

              Organize open AI innovation challenges

              Execution for Principle 5 - 2

              Integrate sustainability KPIs in all major AI projects

              Execution for Principle 5 - 3

              Collaborate with NGOs and academia on co-creating community health solutions

              Principles 5 & 6 – Growth and Sustainability

                Principle 6: Empowerment and Growth

                Foster a learning culture by upskilling employees and ensuring their active involvement in AI transformation

                Example for Principle 6

                Launch a 'Citizen Data Scientist' program making basic AI education accessible to all staff

                Execution for Principle 6 - 1

                Partner with educational institutions for AI upskilling programs

                Execution for Principle 6 - 2

                Recognize and reward employee-led innovation

                Execution for Principle 6 - 3

                Set up an open forum for employees to raise concerns or ideas

                Execution Roadmap Summary

                  Principle Focus 1

                  Ethics & Integrity: Establish AI Ethics Review Board & Mandate Training

                  Impact 1

                  Ensures adherence to ethical standards

                  Principle Focus 2

                  Community Focus: Deploy AI for Last-Mile Delivery Optimization

                  Impact 2

                  Improves affordability and access to medicines

                  Principle Focus 3

                  Quality & Reliability: Implement Real-Time Monitoring & QA Teams

                  Execution Roadmap Summary

                    Impact 3

                    Guarantees safety and accuracy; minimizes drift

                    Principle Focus 4

                    Trust & Accountability: Integrate Explainable AI (XAI) Modules

                    Impact 4

                    Builds confidence with regulators and end-users

                    Principle Focus 5

                    Innovation & Sustainability: Integrate Sustainability KPIs in AI Projects

                    Impact 5

                    Drives eco-friendly and inclusive solutions

                    Execution Roadmap Summary

                      Principle Focus 6

                      People & Culture: Launch Citizen Data Scientist Program

                      Impact 6

                      Fosters an empowered, AI-literate workforce

                      Overall Summary

                      This roadmap ensures comprehensive implementation of responsible AI principles

                      Key Benefit

                      Enhances trust and effectiveness in AI applications

                      Next Review

                      Regular updates to track progress

                      Call to Action & Next Steps

                        Key Takeaway

                        Responsible AI is not just compliance; it’s an investment in the future of healthcare and trust

                        Call to Action

                        All Department Heads: Please appoint an AI Liaison to collaborate with the new AI Ethics Review Board by [Date]

                        Next Step 1

                        Open for Questions and Discussion

                        Title of Slide

                        Our Commitment: Next Steps

                        Visual Emphasis

                        Incorporate visuals to highlight commitment and forward momentum