IDH and WSAF Publication of ToolKit
Tashi Dendup Blog
David Wand - Podcast Reviewing Somalia SRH GBV project Performance Measurement Framework
Public Health Journal - December, 2024
Please get in touch with Steven Ariss (s.ariss@sheffield.ac.uk) if you’re keen to learn more or would like more FAIRSTEPS related resources.
ORACLE NEWS DAILY - Article by George S. Tengbeh
IEG & World Bank Publication - October, 2024
Getaneh Gobezie - Two Blogs
EVALSDGs Insight Dialogue - October 23rd 2024
Quick tips to assess the risks of AI applications in Monitoring and Evaluation
recording here, and the Evaluation Insight here.
Value for Women Publication 2024
March 4, 2025 at 6pm to March 6, 2025 at 7pm – Europe
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Time: May 15, 2023 at 6pm to May 24, 2023 at 7pm
Location: Online
Website or Map: https://cynara.co/trainingsto…
Event Type: training, (fee-based, with, limited, scholarships, available)
Organized By: Emily Springer
Latest Activity: May 11, 2023
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Hi everyone! I'm running my ethical (i.e. feminist!) AI training again in case anyone is interested! This is specifically for professionals who work in gender and social inclusion and want an introduction to machine learning and social inequalities!
Learn the basics, gain skills, and build confidence to engage in social impact projects with machine learning components. If you work in gender & social inclusion support, proposal development, program design, backstopping, and other non-technical areas, this training is for you. In this 5-day interactive online course, we will learn how machine learning algorithms operate, review development use cases, and explore challenges around bias, ethics, and inclusion. We will finish with best practices and examples of harnessing the power of machine learning for gender equity and social inclusion. This course will empower you to represent gender equality, social inclusion, diversity, and equity concerns and propose solutions in machine learning discussions in your organization.
Check out the full details at Cynara Ethical AI!
Session 1: Intro to AI, inequalities, and machine learning models
Session 2: The digital divide and data inequalities
Session 3: Fairness and bias metrics and ethics statements
Session 4: Moving to practice
Session 5: Toward Ethical AI in Practice
Note to participants: (1) no statistics required! We will work from conceptual and layperson understandings and (2) we will use examples from data-rich U.S. to understand ethical concerns before applying these to international development and social sector cases.
I really appreciate this great initiative and I would like to participate in.
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