The Biases We Bring: 

AI, Human Judgment, and Ethical Evaluation Practice

3 June 2026, 13:00-14:30 GMT

 

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When you use AI in evaluation, are you strengthening ethical practice — or automating distance, bias, and harm?

This Practice Lab is a live space for commissioners, evaluators, and researchers who want to examine the biases we bring into evaluation and the risks AI may deepen or help address. If you want to move beyond generic AI optimism and build evaluation practice that is more critical, relational, and ethically serious, this session is for you.

 

Benefits of joining this Practice Lab

Spot bias more clearly

Examine how both AI and evaluation practice can reproduce bias, flatten context, and distance decision-makers from the people most affected.

Strengthen judgment and care

Explore what it takes to use AI critically while centring human judgment, relational practice, and ethical responsibility in evaluation.

Build the confidence to change practice

Test real scenarios, surface tensions, and leave better equipped to make more thoughtful, relational, and accountable choices in your own evaluations.

Join The Practice Lab

If you are ready to move beyond generic AI optimism and take a more honest look at bias, care, and harm in evaluation, this Practice Lab is for you.

Frequently Asked Questions

Practice Lab Facilitators

Teia Rogers, Ph.D

Teia is the Executive Director of JRNY Consulting, a feminist research and learning firm that supports purpose-driven teams to build stronger, fairer approaches to evidence, accountability, and learning. 

With nearly 20 years in humanitarian and development work, she brings her reflections on what she’s seen again and again —about how power shapes what gets measured, believed, and acted on. 

Susanna Davies

Susanna is Head of Strategic Partnerships and Initiatives at JRNY Consulting, where she builds trusted relationships, shapes joint initiatives, and supports community-driven learning.

With 17 years in evaluation, learning, and humanitarian practice, she brings experience in localisation, partnership practice, participatory research, and protection and care — giving her a sharp perspective on what can be lost, or safeguarded, when AI enters evaluation.