GNI Annual Learning Forum 2026: Bridging AI, Governance, & Human Rights

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October 29, 2026  |  Events

The Global Network Initiative (GNI) is pleased to announce our 2026 Annual Learning Forum, Bridging AI, Governance, & Human Rights, taking place on Tuesday, November 17 and Wednesday, November 18 from 10-11 am ET / 3-4 pm UTC each day virtually. 

This year’s Forum aims to bridge two critical perspectives, of the people and processes designing, developing, and deploying AI models and services, with the individuals and organizations working to understand and advocate about AI’s impacts on communities and rights. 

Across two hour long sessions, we will feature a series of lightning talks exploring various aspects of the technical designs of AI systems, followed by panel discussions on the intersections of human rights and AI. See more below about the agenda, which will continue to be updated in the runup to the event.

Please reach out to GNI at info[at]globalnetworkinitiative.org for registration information.

GNI’s Annual Learning Forum is a flagship event in our broader learning agenda. Additionally, this year, the event is part of programming for GNI and the Centre for Communication Governance’s Multistakeholder Approaches to Participation in AI Governance (MAP-AI) initiative, which seeks to foster meaningful and effective multistakeholder engagement across a range of critical AI governance-focused convenings, processes, and initiatives, with a particular focus on elevating underrepresented voices and perspectives. 

Agenda for November 17

Introduction

GNI

Lightning Talks: Unpacking AI Infrastructure, Architecture, & Model Types

  1. Kat Duffy, Council on Foreign Relations on Tracing and Pacing: Understanding The Physical Underpinnings of AI for Rights-Respecting Governance. 
  2. Matt O’Shaughnessy, CDT on AI, Machine Learning, & Model Designs. 
  3. Agentic AI and Privacy: Technical Architectural Choices. 

Panel: Integrating Human Rights into the AI Stack 

As AI rapidly evolves from traditional machine learning to generative and agentic systems, understanding the underlying technical stack is essential for effective rights-focused governance. This panel explores how decisions at key levels of AI systems – such as infrastructure, protocols, model design, product development, deployment, and user choices – shape human rights outcomes. The session will examine the rights and governance implications of upstream technical infrastructure like critical minerals, GPUs, and data centers; technical architecture choices surrounding AI agents; model design choices such as open versus closed systems; and product decisions. Attendees will gain actionable insights on where to direct advocacy and governance interventions across the AI stack to effectively support rights-respecting AI implementation.

  • Moderator: Jhalak Kakkar, Centre for Communication Governance at the National Law University of Delhi

Closing remarks

GNI

Agenda for November 18

Introduction

GNI

Lightning talks: Unpacking AI Training, Alignment, and Evaluation 

  1. Nancy Adossi, Masakhane Hub on Pre-Training AI Safety Techniques.
  2. AI Alignment and Post-Training Safety Techniques. 
  3. Elham Tabassi, Brookings Institution on Enabling Independent AI Evaluations. 

Panel: How Should Human Rights Inform AI Safety Efforts?

This session aims to both demystify how AI safety efforts currently work and explore what those efforts might learn from rights based approaches. Speakers will examine how pre-training, post-training, and evaluation techniques overlap and reinforce each other; the efficacy, gaps, and opportunities of those current technical safety methods; and how those techniques could draw on a wider set of rights-based perspectives. For example, how might approaches grounded in international human rights frameworks might be more effectively applied to technical pre-training, alignment, and post-training choices? Ultimately, the session seeks to bridge digital rights advocates, AI safety researchers, standards experts, and independent evaluators to drive more informed, rights-respecting AI governance recommendations and decisions.

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