NDIA contracted with MassHire Metro North Workforce Board, the organization that leads the Digital JEDI Consortium in Massachusetts on training and support for their digital navigator program. In thinking through the topic of our last professional development training together, one topic kept coming up again and again: artificial intelligence. However, it quickly became apparent that people wanted not just some basic knowledge about AI – i.e., what do we mean by “artificial intelligence,” and what are some common AI tools that people can use – but also guidance on how to approach the field as digital inclusion practitioners.
I was privileged to be given a lot of freedom by the MassHire team to explore some big questions. How do we talk about bias and misinformation in AI systems? How do we equip our community with sufficient knowledge to decide how and whether to engage with AI tools? How do we talk about how AI is being both used by and on our communities? I wanted to share a couple of themes that surfaced from the research, development, and delivery of the AI training:
Understanding how something is made opens up deeper discussions on its impacts
This is something we experience every day as technology teachers: lifting up the hood and explaining the parts lets learners draw new connections. This is even more crucial given the fog created by the current wave of AI hype.
We did an exercise from A People’s Guide to Tech’s excellent A People’s Guide to AI that asked us to develop an algorithm to tell if someone is over 38. Doing so was both funny (discovering people’s beliefs about age is fascinating) and illuminating. What biases did we carry with us into making the algorithm? How confident are we in the accuracy of the results? How different is it then to make an algorithm that decides if you get a mortgage or probation?
The section on algorithms was part of giving people a simplified model to work from (AI = data->model->outputs) that let them open the perceived black box of AI enough to understand how biases and errors can find their way into outputs, and – perhaps more importantly – to feel empowered enough to think through the bigger questions they had about the technology.
Practitioners are hungry for conversations about the impacts of AI on individuals and society
From the first exercise (“introduce yourself with one question you have about AI”), it was obvious that practitioners are looking for a bigger perspective than “how to write an effective prompt.” Here’s a small sample of the questions people wanted to discuss:
- How do I encourage students not to use AI as a replacement for critical thinking?
- What are the environmental impacts of using AI when it comes to data center construction, energy, and water?
- How do I know if something is real? What does that mean for teaching people about finding good quality information?
People come to digital equity and inclusion work because they believe in equity and inclusion and center it in their work. This means that a new technology that has impacts on the environment, society, and individual mental health, which we are only beginning to understand, shouldn’t be introduced as “well, it’s unavoidable, better adapt.”
What practitioners – both in this training and in conversations with the larger NDIA community – seem to be asking is: how do I prepare my community so they can interact with this technology on their own terms? How do I empower my community to choose how they use these technologies?
We already have many of the tools we need
Breathlessness around AI’s potential impacts can also lead practitioners to think they need to completely restructure their approach to community education. However, as NDIA’s AI pilot projects with practitioners have already demonstrated, existing tech curricula already have multiple integration points, allowing people to add AI literacy to their offerings. The techniques we teach community members already around digital privacy and security have immediate application to interacting with AI tools.
The best practices for teaching media literacy that have been developed for decades also serve to help equip community members to navigate AI-created misinformation and disinformation. In the same way we encourage community members to reflect on source, credibility, and emotional reaction in looking at scam emails or suspect news, we can hone those skills by analyzing content produced with AI.
Do practitioners need to familiarize themselves with AI enough to talk meaningfully about it? Of course! But it can be approached as another technology we’re adding to our toolbox instead of an entirely new set of tools – something to fold into existing instruction rather than creating entirely new curricula.
Looking ahead
If your organization finds the training outline, slides (Part One and Part Two), and resource document useful, they are available for reuse or adaptation under Creative Commons (BY-NC-SA 4.0) licensing, just like everything else we produce at NDIA. Our AI Working Group is also exploring discussions like this – we invite you to become an Affiliate+ member and join the conversation.
To learn more about the JEDI Consortium, check out the blog post Scaling Digital Equity in Massachusetts: A Workforce-Centered Approach to Digital Navigation. If you’re interested in hiring NDIA for training on AI or other digital inclusion topics, please visit our Hire Us page.