AI Ethics Advocacy Network

Network Vision & Mission

Mobilize champions across the organization to advance ethical AI practices, dialogue, and accountability.

Strategic Partnerships & Communities

Define the network’s mission to advocate for ethical AI adoption, inclusive design, and stakeholder trust.

Set up regional chapters, working groups, and leadership councils to ensure reach and accountability.

live demo · related simulation● LIVE

Engagement Activities & Resources

Design events, ethics labs, listening sessions, and hackathons to keep stakeholders informed and involved.

Publish toolkits and micro-learning modules tailored to ambassador cohorts.

Communications & Storytelling

Develop compelling narratives and share insights through various channels to raise awareness and drive action.

Storytelling & Communications

Frequently asked questions

What is Partnerships & Communities?

Partnerships & Communities

What does it mean to Collaborate with academia, NGOs, industry consortia, and regulators to stay ahead of emerging standards?

Collaboration with academic institutions, non-governmental organizations (NGOs), industry consortia, and regulatory bodies is crucial for keeping abreast of the latest advancements in AI.

How can we Support community initiatives addressing digital literacy, equity, and inclusion in AI?

Supporting community programs focused on digital literacy, equitable access to AI technologies, and inclusive development practices within the AI field contributes significantly to broader societal benefits.

What metrics should we Track ambassador activity, training completions, sentiment scores, and policy adoption?

Monitoring ambassador engagement through activity tracking, training completion rates, sentiment analysis of discussions, and the adoption of relevant policies provides valuable insights into program effectiveness.

▶ Try it live

Everything above runs in your browser — open Gradient Descent Visualiser and change the parameters while it is running. Nothing is installed, nothing is uploaded, the whole model lives in one tab.

▶ Open Gradient Descent Visualiser simulation