Ongoing Ethics Review Procedures

Navigating the Research Engagement Process Conducting health research is not just about designing a study and collecting data. Behind the scenes lies a critical process that ensures credibility, compliance, and trust: the research ethics and engagement pathway. As a Research Program Manager, I’ve seen firsthand that without a clear roadmap for ethics approvals and stakeholder engagement, studies risk delays, rejection, or even loss of community trust. Below, I outline the step-by-step process typically required when conducting health research in Kenya, a process that safeguards participants while strengthening research impact. 1️⃣ Obtain Research Ethics Approval Begin by submitting your protocol to a recognised research ethics body. For lab-related studies, this could be the KEMRI SERU Board. ⏳ Timeline: Allow at least 6–8 weeks for review. 2️⃣ Apply for NACOSTI Research Permit With your ethics approval letter, apply to the National Commission for Science, Technology, and Innovation (NACOSTI) for a research permit. ⏳ Timeline: ~2 weeks. 3️⃣ Secure an Institutional Introductory Letter Your institution should issue a formal letter introducing your study and confirming affiliation. 4️⃣ Notify the Ministry of Health Submit your ethics approval, NACOSTI permit, proposal summary, and introductory letter to the relevant Ministry of Health department for national-level clearance. 5️⃣ Engage County Governments Upon Ministry approval, you’ll be directed to approach the counties where your study will take place. Each county has its own research department for review and approval. 6️⃣ Seek Facility-Level Approvals At the health facility level, you may need additional clearance. For example, Kenyatta National Hospital has its own internal ethics review board. 7️⃣ Engage Participants at Facility Level Before recruitment, engage potential participants to explain the study, answer questions, and build trust. This step reinforces ethical principles of respect and informed consent. 8️⃣ Begin Recruitment Only after all approvals and engagements are complete should recruitment and data collection begin. The research engagement process may feel long and layered, but every step serves a purpose: protecting participants, ensuring compliance, and building trust with communities and institutions. It's key to remember that your success will highly depend on navigating power and trust in the engagement process. In my experience, investing time upfront in ethics and engagement leads to smoother implementation, stronger collaborations, and findings that are more likely to inform policy and practice. 👉 To fellow researchers: What’s been your biggest challenge (or lesson learned) in navigating the ethics and engagement process? #ResearchLeadership #EthicsInResearch #StakeholderEngagement #HealthResearch

✳ 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.

📢 BREAKING – China Issues Draft #AI #Ethics Rules for Public Consultation 🚀 Yesterday 22 August, China’s Ministry of Industry and Information Technology (MIIT), along with Ministry of Science and Technology (MOST), CAC and several other national regulators, released the draft Measures for the Administration of Ethics for AI Technological Activities. The consultation will end on 22 Sept. 🤖 The draft Measures apply to all AI R&D and technological services in China that may affect human health and safety, personal reputation, environmental protection, public order, or sustainability, covering businesses across industries, healthcare institutions, research organizations, and academics engaged in AI-related activities. The Measures set out ethical requirements for AI R&D and services, including • Developing technology for the public good • Respecting life, health, and reputation • Upholding justice, fairness, and accountability • Managing risks responsibly • Ensuring compliance with existing laws and regulations Entities are encouraged to establish an Ethics Commission responsible for ethics review. For organizations without an internal body, local authorities will create Ethics Service Centres to provide review services. AI technological activities within scope must undergo ethics review, either by an internal Ethics Commission or a local Ethics Service Centre. Reviews will focus on: • Fairness, risk control, trust, transparency, and explainability • Accountability and liability tracing • Qualifications of personnel involved • Risk–benefit balance and social value of the AI activity Reviews should conclude within 30 days, with outcomes being: approval, rectification and resubmission, or rejection. A simplified review is available for low-risk AI activities, such as those comparable to normal daily scenarios or involving immaterial updates to previously approved projects. MIIT and MOST will publish a list of AI activities requiring expert second review for high-risk activities, such as algorithm models capable of mobilizing public opinions and automated decision-making systems with significant implications for human safety and health. A streamlined review process is available for public emergencies. ❓ What’s Next? 💡 This Ethics Measures reflect China’s pragmatic and agile approach to AI governance. Instead of a sweeping AI law, Chinese regulators are targeting high-risk areas such as #algorithms, #deepfakes, #generativeAI, and AI #labeling. With the Ethics Measures now open for feedback, ethical compliance is expected to be a formal requirement for corporations and institutions operating in China. 🔀 Organizations should closely monitor these developments and adapt their AI strategies and risk management frameworks accordingly. #AI #AIgovernance #China #law #ethics #data #privacy #riskmanagement #regulatory #compliance #enforcement #digitaltrust #digitalgoverance picture credit to Freepik.

🎉 It's finally here! AI Human Subjects Research (#AIHSR) Desktop Procedures are HERE! 🎉 We are thrilled to release comprehensive #IRBoperations guidance that brings clarity to one of research ethics' biggest challenges. The Problem: AI research doesn't fit traditional IRB workflows. How do you review it? When is it safe to let AI influence real-world decisions? What even counts as "AI human subjects research"? The Solution: Our Desktop Procedures framework leverages the 3-Stage AI HSR Framework (Eto, Lifson, & Vidal, 2024): ✅ Stage 1: Discovery and Ideation (Algorithm development) ✅ Stage 2: Analytical and Clinical Validation (performance verification) ✅ Stage 3: Real-world evaluation Why Bother? → Risk-calibrated review that matches oversight to project maturity (think "FASTER TURNAROUND TIMES! EASIER REVIEWS!) → Clear requirements (no more ambiguity!) → Staged approval language that prevents premature deployment (think safer, responsible AI) → Works across ALL domains: clinical, educational, social behavioral, and public health) → Maintains full regulatory compliance (45 CFR 46, 21 CFR 50/56/812, HIPAA) https://lnkd.in/g5hvFFKz #ResearchEthics #IRB #HRPP #ArtificialIntelligence #AIEthics #ResponsibleAI #HumanSubjectsResearch #AIHSR #HRPP #Innovation #ResearchCompliance #ResearchAdministration

China issues new measures on AI ethics review and compliance systems ▶ China’s Ministry of Industry and Information Technology and nine agencies issued new Administrative Measures for AI ethics review and services (trial) ▶ The framework introduces a dual-track system combining algorithm filing with mandatory ethical evaluation for AI projects ▶ Organizations must establish internal ethics committees or use external service centers, with government-led expert review required for high-risk systems ▶ AI activities must undergo pre-approval ethics assessments, including risk analysis, data sources, and contingency planning, with decisions issued within 30 days ▶ Ongoing monitoring, follow-up reviews, and potential suspension or termination of projects are required based on evolving risk conditions ▶ The measures expand governance to include labor protections, algorithm auditing, and requirements for controllability, transparency, accountability, and privacy Source : https://lnkd.in/gvrDsUwF 📚 The AI Policy Newsletter: https://lnkd.in/eS8bHrvG 🦋 Follow me on Bluesky: https://lnkd.in/enpH3UjQ