What will I learn?
This rich and detailed course covers the necessary building blocks to understand inclusive AIÂ through three modules
(1) AI core concepts,
(2) the training process, and
(3) data and data bias.
And it does so, by interweaving social inclusion, responsible AI, and social impact throughout.
Why is this training important?
Future proof your career with "building blocks" that provide you with the foundational concepts and tools of AI, upon which all other trainings build. The goal is to train YOU how to think critically and carefully about AI, not merely provide tips and tricks.
Who is it for?Â
This introductory training is designed for non-coders, people who are interested in AI but not sure where to start. If you work in the social impact sector, are a backstopper, Chief of Party, project manager, social inclusion specialist, new business lead, and/or a technical specialist in something other than AI, this training is designed for you.
But make no mistake, this course is certainly technical. It is only when we truly understand the technical side of AI, that we can see how and where to successfully integrate social inclusion.
What does the training cover?
- What is AI and machine learning?
- What is the key innovation of AI?
- The OECD definition of an AI system
- What are the 4 types of training an AI model?
- How do you train a supervised AI model?
- How is success defined in AI?
- What are the differences between an algorithm and a model?
- Why is digital inclusion even more important now?
- How to understand AI datasets
- What are some unintended consequences of data for AI?
- Best practices for addressing data bias
- Three frameworks designed by Dr. Emily Springer to bring social inclusion to the foreground
- And more!
For more details, see the curriculum below. Consider this training the start, not the end, of your AI journey.
When is the training?
Learn at your own pace! Fully on-demand, remote training. This training is approximately 4 hours in total.
Am I able to earn a certificate?
Yes. By completing all videos and scoring 80% or more on each module quiz (re-takes allowed), you will receive a certificate of completion.
What will I be able to do when I finish?
After completing this training, you will:
- Understand AI from a concepts, not math, perspective that focuses on inclusion.
- Understand the training process, the important role of data, and data best practices.
- Begin to participate in organization discussions about inclusive AI.
- Have the foundation needed to read, process, and apply news about AI.
Detailed Curriculum
- Data and Data Bias Intro and PDF (0:59)
- The Global Digital Divide (11:15)
- Ask: Who is in the Data? (8:44)
- Ask: how are they in the data? (10:36)
- Ask: what are the politics of data? (11:29)
- Sociotechnical framework for train/test datasets (2:43)
- Unintended consequences of AI-driven data hunger (10:26)
- Best practice: Contextual datasets (14:20)
- Module quiz (10 questions)
Meet your trainer
Dr. Emily Springer is recognized as a Top 100 Brilliant Women in AI and serves as an expert through UNESCO's Women4Ethical AI platform.
Dr. Springer works on inclusive AI for Data2X, UNFPA, Athena Infonomics, and others. She is a sociologist with experience in AI, international development, and social inclusion. She has trained graduate students in Development Practice and Social Justice and taught Technology and Society at Arizona State University.
Since 2021 (that's even before ChatGPT made AI cool!), Dr. Springer has been training social impact professionals in ethical, feminist, and inclusive AI. She has trained professionals from USAID, FCDO, CanWaCH, UNFPA, Un Women, CARE, IREX, Social Impact, Wikimedia, and others.
Want to get a sneak peek at the material and training style?
Check out this free webinar recording on Inclusive AI!
Please note these testimonials come from a longer Inclusive AI bootcamp. The content in this 4 hour training tightly matches the first 4 hours of the bootcamp.
