If you’re interested in this training, please see TheInclusiveAILab.com or reach Emily (emily@technosocioadvisory.com).

Description: Grow your algorithmic literacy! If you are a non-technical practitioner, you are absolutely needed at the AI table! 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. This training assumes no understanding of algorithms and will use conceptual understandings, rather than statistical or data science approaches, to upskill you in this rapidly evolving technology. In this 6-day interactive online course, we will learn how machine learning algorithms operate, explore challenges around bias, ethics, and inclusion, and review development use cases. 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 understand, advocate for, and address ethical AI concerns broadly and gender equality, social inclusion, diversity, and equity concerns specifically. You will emerge with a greater ability to read and apply USAID guidance and constructively collaborate with coders/developers for successful machine learning for social impact projects.

Notes to participants:

(1) no statistics required! We will work from conceptual and layperson understandings,
(2) we will use examples from data-rich U.S. to understand ethical concerns before applying these to international development and social sector cases, and
(3) be sure to plan in prep time (approximately two hours per session, including videos and podcasts)

Click here to see the full training agenda

Trainer: Dr. Emily Springer is one of 100 Brilliant Women in AI Ethics™ in 2024 and serves as the emerging technologies consultant within the Gender and Human Rights technical division at UNFPA, specializing in ethical and feminist AI, and as the AI consultant with the Global Center for Gender Equality, providing technical gender assistance to Bill and Melinda Gates Foundation. Previously, Dr. Springer worked with Athena Infonomics as part of DAI’s Digital Frontiers on a digital inclusion toolkit, World Bank's IFC as a strategy consultant for digitalization of African higher education institutions, and worked at a Microsoft partner building relational database and automation solutions for enterprise clients. She is trained as an interdisciplinary sociologist and completed a postdoc at Arizona State University in the US where she taught undergraduates about how machine learning changes not only our everyday interactions but also global geopolitical landscapes, and has taught and mentored graduate students in Development Practice and Social Justice programs. She has served as a consultant to numerous development organizations including World Bank Africa Gender Innovation Lab, DAI, CARE, and others. She often works for USAID DC to improve global practices around gender integration and inclusive tech. She is excited to help build a network of critical practitioners to ensure machine learning works for women in all their intersectional experiences.