Collaborative Ethical Standards Development

Compliance: Whose Responsibility – Supplier or Brand? In today's interconnected global economy, the question of compliance responsibility has become more pressing than ever. With supply chains stretching across continents & involving numerous stakeholders, determining who holds the mantle of ensuring compliance - be it the supplier or the brand - is a complex yet crucial consideration. The Shared Responsibility Model Traditionally, brands have relied on suppliers to adhere to regulatory standards, ethical practices & quality benchmarks. However, this delegation doesn't absolve brands from accountability. Instances of labor violations, environmental breaches or quality issues can tarnish a brand's reputation, regardless of where the fault originated. Conversely, suppliers often operate under the directives & pressures imposed by brands, including tight deadlines & cost constraints. These pressures can inadvertently lead to corners being cut, resulting in compliance lapses. Legal & Ethical Imperatives Recent regulatory dev. underscore the importance of shared responsibility. For instance, the European Union's Corporate Sustainability Due Diligence Directive mandates that companies not only ensure their operations are compliant but also take responsibility for their entire supply chain. This includes identifying, preventing & mitigating adverse human rights & environmental impacts. Such regulations signify a shift from voluntary compliance to mandatory due diligence, emphasizing that both brands & suppliers must collaborate to uphold standards. Building a Collaborative Compliance Framework To navigate this landscape effectively: * Establish Clear Codes of Conduct: Brands should develop comprehensive supplier CoC that outline expectations regarding labor practices, environmental standards & ethical operations. * Regular Audits & Assessments: Both parties should engage in periodic reviews to ensure ongoing compliance & address potential issues proactively. * Open Communication Channels: Fostering transparent dialogue between brands & suppliers can preempt misunderstandings & facilitate swift resolution of concerns. * Joint Training Programs: Collaborative training initiatives can ensure that all stakeholders are aligned in their understanding of compliance requirements. Conclusion Compliance is not a zero-sum game where responsibility can be shifted entirely to one party. Instead, it thrives on collaboration, mutual respect & shared commitment. By recognizing the intertwined roles of both brands & suppliers, organizations can build resilient, ethical & compliant supply chains that stand up to scrutiny & deliver long-term value. Let's champion a culture where compliance is a collective endeavor, ensuring integrity & excellence at every link of the supply chain. #ComplianceMatters #SupplyChainIntegrity #EthicalSourcing #BrandResponsibility #SustainableBusiness #SharedAccountability #GlobalStandards Shatadru Chattopadhayay Tatheer Zaidi

✳ Bridging Ethics and Operations in AI Systems✳ Governance for AI systems needs to balance operational goals with ethical considerations. #ISO5339 and #ISO24368 provide practical tools for embedding ethics into the development and management of AI systems. ➡Connecting ISO5339 to Ethical Operations  ISO5339 offers detailed guidance for integrating ethical principles into AI workflows. It focuses on creating systems that are responsive to the people and communities they affect. 1. Engaging Stakeholders  Stakeholders impacted by AI systems often bring perspectives that developers may overlook. ISO5339 emphasizes working with users, affected communities, and industry partners to uncover potential risks and ensure systems are designed with real-world impact in mind. 2. Ensuring Transparency  AI systems must be explainable to maintain trust. ISO5339 recommends designing systems that can communicate how decisions are made in a way that non-technical users can understand. This is especially critical in areas where decisions directly affect lives, such as healthcare or hiring. 3. Evaluating Bias  Bias in AI systems often arises from incomplete data or unintended algorithmic behaviors. ISO5339 supports ongoing evaluations to identify and address these issues during development and deployment, reducing the likelihood of harm. ➡Expanding on Ethics with ISO24368  ISO24368 provides a broader view of the societal and ethical challenges of AI, offering additional guidance for long-term accountability and fairness. ✅Fairness: AI systems can unintentionally reinforce existing inequalities. ISO24368 emphasizes assessing decisions to prevent discriminatory impacts and to align outcomes with social expectations.  ✅Transparency: Systems that operate without clarity risk losing user trust. ISO24368 highlights the importance of creating processes where decision-making paths are fully traceable and understandable.  ✅Human Accountability: Decisions made by AI should remain subject to human review. ISO24368 stresses the need for mechanisms that allow organizations to take responsibility for outcomes and override decisions when necessary. ➡Applying These Standards in Practice  Ethical considerations cannot be separated from operational processes. ISO24368 encourages organizations to incorporate ethical reviews and risk assessments at each stage of the AI lifecycle. ISO5339 focuses on embedding these principles during system design, ensuring that ethics is part of both the foundation and the long-term management of AI systems. ➡Lessons from #EthicalMachines  In "Ethical Machines", Reid Blackman, Ph.D. highlights the importance of making ethics practical. He argues for actionable frameworks that ensure AI systems are designed to meet societal expectations and business goals. Blackman’s focus on stakeholder input, decision transparency, and accountability closely aligns with the goals of ISO5339 and ISO24368, providing a clear way forward for organizations.

For AI Systems, ethical / responsible considerations have been an area of focus in global standards since 2016 at IEEE, where I work. So if anyone says, "Who is working on Ethical AI standards?" Answer: IEEE, since 2016, with the first standard launched in the IEEE 7000 series being released in 2020. The standards I've linked to below (which includes standards that have been launched already, plus others that are in development which means anyone can join those Working Groups) began development in 2017. The first standard (IEEE 7010-2020) launched in 2020. All these standards relate to Artificial Intelligence. And as GenAI is not the ONLY TYPE OF AI ARCHITECTURE, all of them support the responsible design of any / all AI Systems. Many (like IEEE 7014-2024) do focus squarely on GenAI issues (and note - '2024' or a year listed in an IEEE standard indicates the year it was released). I'm proud to have helped launch the IEEE 7000 series, what I believe may be the largest suite of socio-technical standards in the world. (I was the founding chair of IEEE 7000 and IEEE 7010, where the amazing Ali Hessami and Sarah Spiekermann drove the completion of 7000 with their amazing Working Group, and the glorious Laura Musikanski became Chair of 7010 (I became Vice-Chair) to lead our incredible working group with people like Daniel S. Schiff and Bogdana Rakova). Some other examples: For IEEE 7001 focused on transparency, the amazing Alan Winfield was Chair and this work provides evergreen, critical ways to understand and implement pragmatic aspects of 'transparency' as defined for technologists focused on all AI Systems (NOT just GenAI). IEEE 7003-2024 focused on issues of algorithmic bias driven by the fantastic Gerlinde Weger is a must read / must use. IEEE 7007 - 2021 (one of the earliest to launch in the series) was Chaired by the beyond insanely incredible Edson Prestes who is a ROCK STAR in the global AI governance community. Name any UN related tech committee in the past few years, Edson is a part of it. Thanks to him for driving the IEEE Ontological Standard for Ethically Driven Robotics and Automation Systems work. And the list goes on and on and on. Please check out the link below and for any Working Group that doesn't have a year listed, this means YOU CAN JOIN THE WORK. Feel free to follow and DM me and I'll give you more details. And THANK YOU to the incredible volunteers who made all this work possible and who have worked since 2016 (even before the work on IEEE 7000 began) to make this series possible. This includes, of course, my colleagues at IEEE Standards Association | IEEE SA including former Managing Director, Konstantinos Karachalios. https://lnkd.in/eRiafAWp

𝗚𝗟𝗢𝗕𝗔𝗟 𝗔𝗜 𝗖𝗢𝗟𝗟𝗔𝗕𝗢𝗥𝗔𝗧𝗜𝗢𝗡: 𝗘𝗧𝗛𝗜𝗖𝗔𝗟 𝗣𝗥𝗢𝗧𝗢𝗖𝗢𝗟𝗦 𝗔𝗖𝗥𝗢𝗦𝗦 𝗕𝗢𝗥𝗗𝗘𝗥𝗦 As AI technologies transcend national boundaries, the need for global ethical alignment has never been more urgent. To prevent fragmentation and ensure responsible AI development, international collaborations are working to establish unified ethical standards across diverse legal and cultural frameworks. 𝗦𝘁𝗲𝗽𝘀 𝗧𝗮𝗸𝗲𝗻: Global initiatives are forming to develop common AI governance protocols. The Organisation for Economic Co-operation and Development (OECD) introduced AI Principles endorsed by over 40 countries, promoting inclusive growth, transparency, and human-centered values. Meanwhile, G20 member states and the Global Partnership on AI (GPAI) are working to harmonize policy approaches and foster international cooperation in areas such as responsible AI, innovation, and the ethical use of AI in healthcare and climate science. 𝗪𝗵𝗼 𝗖𝗼𝗻𝘁𝗿𝗶𝗯𝘂𝘁𝗲𝗱: Key contributors include OECD, G20, and GPAI, each playing a vital role in shaping a collaborative framework for ethical AI. These entities bring together governments, academia, industry, and civil society to address ethical challenges and guide AI development that respects human rights and democratic values across borders. 𝗛𝗼𝘄 𝗬𝗼𝘂 𝗖𝗮𝗻 𝗛𝗲𝗹𝗽: 𝗔𝘀 𝗮 𝗖𝗼𝗺𝗽𝗮𝗻𝘆:   • Align AI practices with globally recognized ethical standards and support cross-border collaborations.   • Participate in international working groups that advance transparent, human-centric AI governance. 𝗔𝘀 𝗮𝗻 𝗜𝗻𝗱𝗶𝘃𝗶𝗱𝘂𝗮𝗹:   • Stay informed about global AI ethics frameworks and advocate for their adoption in your country.   • Support businesses and platforms that commit to international AI ethics protocols. 𝗝𝗼𝗶𝗻 𝘁𝗵𝗲 𝗖𝗼𝗻𝘃𝗲𝗿𝘀𝗮𝘁𝗶𝗼𝗻: International cooperation is key to shaping a future where AI serves humanity responsibly. How do you think cross-border collaboration can help build trust and accountability in global AI development? Stay tuned for next week’s post in this ongoing series, where we explore 𝗔𝗜 𝗥𝗲𝘀𝗸𝗶𝗹𝗹𝗶𝗻𝗴 𝗜𝗻𝗶𝘁𝗶𝗮𝘁𝗶𝘃𝗲𝘀: 𝗧𝗮𝗰𝗸𝗹𝗶𝗻𝗴 𝗝𝗼𝗯 𝗗𝗶𝘀𝗽𝗹𝗮𝗰𝗲𝗺𝗲𝗻𝘁 𝗘𝘁𝗵𝗶𝗰𝗮𝗹𝗹𝘆. #AI #Ethics #CourseCorrection #GlobalAI #AIStandards #EthicalAI #CosmosRevisits