Teaching AI Literacy in Workforce and Community Education Programs

 

By Lilian H. Hill

Artificial intelligence (AI) is increasingly embedded in systems that shape work, learning, and civic life.  To fully participate in the workforce, the next generation of workers and community members must be AI-literate and possess the technological skills required. From résumé screening and performance analytics to scheduling software and generative writing tools, AI now influences how adults access opportunities, make decisions, and engage with institutions. As a result, AI literacy has emerged as a critical educational priority in workforce and community education programs serving adult learners navigating rapid technological change.

 

Why AI Literacy Matters for Adult Learners

AI is often encountered not as an abstract technology but as a gatekeeper. Algorithmic systems influence hiring, promotion, credit access, healthcare decisions, and the information people see online. Without a foundational understanding of how these systems operate, adults may experience AI as opaque, uncontestable, or inevitable (Eubanks, 2018).

 

AI literacy equips learners to interpret, question, and respond to these systems. In workforce contexts, it supports adaptability and employability by helping learners understand how AI tools are used in their fields and how to collaborate effectively with automated systems rather than defer to them uncritically (OECD, 2021). In community education settings, AI literacy supports informed citizenship, privacy protection, and collective agency in the face of expanding algorithmic governance.

 

In August 2025, the U.S. Departments of Labor, Commerce, and Education released America’s Talent Strategy: Building the Workforce for the Golden Age. The document is aspirational and contains a vision statement that prioritizes investing in American workers by strengthening a workforce development system, delivering job-ready talent to employers, and ensuring accountability in preparing workers for the jobs critical to the nation’s economic future. The report articulates five pillars of strategic actions, including industry-driven strategies, worker mobility, integrated systems, accountability, flexibility, and innovation. The latter strategy aims to create new models of workforce innovation built to match the speed and scale of AI-driven economic transformation. The Talent Strategy is expected to shape how Workforce Innovation and Opportunity Act (WIOA) programs are funded, evaluated, and administered.

 

Federal funding priorities are likely to reflect the Talent Strategy’s objectives, and states, workforce boards, and partner organizations that align their programs accordingly may be better positioned in future funding and accountability processes. Unfortunately, these initiatives may reduce funding for community literacy programs that teach reading and print literacy. Yet, national and international literacy assessments have consistently shown that approximately 30% of American adults are low literate, and another 20% have only basic skills. That means that almost half of American adults struggle with the reading needed to function well in daily life. The most recent Programme for Assessment of Adult Competencies (PIAAC) survey in 2023 indicates that U.S. adults’ literacy skills may have decreased.

 

Defining AI Literacy in Adult, Community, and Workforce Education

AI literacy includes the knowledge, skills, and dispositions needed to understand how AI systems function, how they influence decisions, and how humans can exercise judgment and responsibility in relation to them (Ng et al., 2021). For adult learners, AI literacy integrates practical application with critical reflection, ethical awareness, and contextual understanding.

 

Across adult, community, and workforce education settings, AI literacy is most effective when grounded in real-world contexts. Learners regularly encounter AI through employment systems, digital services, educational platforms, and workplace technologies. Instruction should therefore emphasize recognizing AI use, understanding its impacts on access and opportunity, and developing the ability to question automated outcomes.

 

These educational contexts also share a focus on equity, participation, and agency. Adult and community programs often support learners navigating structural barriers, while workforce education emphasizes informed and responsible use of AI in professional roles. In all settings, AI literacy should frame AI as a human-designed system shaped by social values, enabling learners to engage with technology thoughtfully, ethically, and with confidence.

 

Core Dimensions of AI Literacy Instruction

The core dimensions of AI literacy provide a framework for helping adult learners develop the knowledge, skills, and dispositions needed to engage with artificial intelligence thoughtfully, ethically, and effectively. Rather than focusing on technical mastery, these dimensions emphasize understanding how AI works, critically evaluating its impacts, protecting personal data, and maintaining human judgment and agency in real-world contexts where AI increasingly shapes decisions and opportunities.

 

1.             Foundational Understanding
Adult learners benefit from clear, accessible explanations of what artificial intelligence is—and what it is not—because public discourse around AI often alternates between alarmist narratives and unrealistic promises. Foundational AI literacy instruction should introduce core concepts such as algorithms, training data, automation, and generative systems using plain language and concrete, everyday examples rather than technical abstractions (Long & Magerko, 2020). Emphasizing that AI systems do not possess consciousness, intent, or understanding, but instead operate by identifying patterns within large datasets, helps learners develop realistic expectations about AI’s capabilities and limitations (Russell & Norvig, 2021). This demystification is especially important for adult learners who may feel intimidated by highly technical explanations or unsettled by rapid technological change. By grounding AI concepts in familiar tools such as recommendation systems, spell-checkers, or scheduling software, educators can reduce fear, prevent overreliance, and support informed, confident engagement with AI technologies.

 

2.             Critical Evaluation and Bias Awareness
AI systems are not neutral or objective; they reflect the social, cultural, and institutional assumptions embedded in their design and training data. Effective AI literacy instruction must therefore help learners critically evaluate AI outputs rather than accepting them as authoritative or unbiased. This includes understanding how biased, incomplete, or historically unequal data can reproduce and amplify discrimination, particularly for marginalized populations (Benjamin, 2019; Noble, 2018). Adult learners should be taught to question how AI-generated information is produced, whose interests it serves, and what perspectives may be absent, and to verify outputs using independent and credible sources. These skills are especially critical in employment, education, healthcare, and public services, where AI-informed decisions can significantly affect access to opportunities and resources. Developing critical evaluation skills empowers learners to engage with AI thoughtfully and ethically, rather than passively or distrustfully.

 

3.             Data Privacy and Ethical Use
Protecting personal data in the age of AI is important because personal information has become a powerful resource—or currency— that shapes how individuals are represented, evaluated, and treated across education, employment, healthcare, finance, and public services. AI systems rely on large-scale data to make predictions and recommendations, and when that data is inaccurate or taken out of context, it can lead to misclassification, unfair decision-making, and long-term consequences that are difficult for individuals to see or contest (Eubanks, 2018). AI literacy must address how personal data are collected, stored, and reused. Adult learners need to understand that inputs into generative AI systems may be retained or used to train models, requiring caution when sharing sensitive or identifiable information. Ethical literacy supports safer participation and informed consent in digital environments (Zuboff, 2019).

 

4.             Human Judgment and Agency
Rather than positioning AI as a replacement for human expertise, adult education should emphasize human oversight, responsibility, and ethical decision-making. AI literacy instruction should reinforce that while AI systems can support human work by increasing efficiency or identifying patterns, they cannot account for lived experience, contextual nuance, moral reasoning, or accountability (Nissenbaum, 2010). Learners benefit from explicit discussion of the limits of automation and the continuing need for human judgment in interpreting results, making final decisions, and addressing unintended consequences. Framing AI as a tool rather than an authority helps preserve learner agency and counters narratives that portray technological systems as inevitable or uncontestable. This emphasis is particularly important in workforce contexts, where fears of automation and displacement can undermine confidence and obscure opportunities for meaningful use of AI tools (Eubanks, 2018).

 

Implications for Workforce and Community Education Programs
Workforce and community education programs are well-positioned to support AI literacy because they are grounded in practical application, real-world challenges, and adult learners’ lived experiences. Integrating AI literacy into existing curricula, such as career readiness, digital skills development, professional writing, or civic education, allows learners to connect abstract concepts to the tasks and decisions they encounter in daily life. Research suggests that participatory, discussion-based approaches are especially effective for adult learners navigating complex technologies, as they validate prior knowledge and encourage collective sense-making (Brookfield, 2013). AI literacy instruction in these settings should therefore be dialogic and reflective, inviting learners to share concerns, ask critical questions, and examine how AI systems shape their workplaces and communities. By centering discussion, ethical reflection, and agency, workforce and community education programs can foster not only technical understanding but also confidence, critical awareness, and responsible engagement with AI.

 

Conclusion

As AI systems continue to shape access to opportunity and participation in society, AI literacy must be treated as a core component of adult education. Workforce and community education programs play a crucial role in helping learners develop not only technical familiarity with AI, but also the critical judgment, ethical awareness, and agency needed to navigate an increasingly algorithmic world.

 

References

Benjamin, R. (2019). Race after technology: Abolitionist tools for the new Jim Code. Polity Press.

Brookfield, S. D. (2013). Powerful techniques for teaching adults. Jossey-Bass.

Eubanks, V. (2018). Automating inequality: How high-tech tools profile, police, and punish the poor. St. Martin’s Press.

Long, D., & Magerko, B. (2020). What is AI literacy? Competencies and design considerations. Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems, 1–16. https://doi.org/10.1145/3313831.3376727

Ng, D. T. K., Leung, J. K. L., Chu, S. K. W., & Qiao, M. S. (2021). AI literacy: Definition, teaching, evaluation and ethical issues. Proceedings of the Association for Information Science and Technology, 58(1), 504–509.

Nissenbaum, H. (2010). Privacy in context: Technology, policy, and the integrity of social life. Stanford University Press.

Noble, S. U. (2018). Algorithms of oppression: How search engines reinforce racism. New York University Press.

OECD. (2021). Artificial intelligence, skills and work. OECD Publishing.

Russell, S., & Norvig, P. (2021). Artificial intelligence: A modern approach (4th ed.). Pearson.

Zuboff, S. (2019). The age of surveillance capitalism: The fight for a human future at the new frontier of power. PublicAffairs.