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Image Credit: Ali Pizani at Pexels
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By: Lilian H. Hill
AI literacy refers to the set of knowledge, skills, and
ethical awareness necessary to understand, evaluate, and interact with AI
systems in informed and socially responsible ways. As Artificial Intelligence
(AI) technologies are being integrated into nearly every aspect of life, understanding
how these systems function is essential for individuals and societies alike. Long and Magerko (2020)
defined AI literacy as “a set of competencies that enables individuals to
critically evaluate AI technologies, communicate and collaborate effectively
with AI, and use AI as a tool online, at home, and in the workplace” (p. 2). Laupichler
et al. (2023) explain that AI literacy refers to the skills and understanding of
AI that adults should have especially non-experts with no computer science
background. Based on an exploratory review of
literature, Ng et al. (2021) identify four key aspects of AI literacy:
1. know and understand,
2. use and apply,
3. evaluate and create, and
4. understand ethical issues
At its core, AI literacy involves both conceptual and
ethical dimensions. On the conceptual side, it requires a foundational
understanding of how AI works. This includes familiarity with:
·
Algorithms, the sets of rules AI systems use to
solve problems,
·
Machine learning that enables AI systems to
learn from data and improve over time,
·
Neural networks that mimic the structure of the
human brain are designed to recognize patterns in data.
It also includes an understanding
of automation and how AI systems can replace or augment human decision-making.
These concepts empower individuals to engage with AI technologies more
confidently and to evaluate their strengths and limitations.
AI literacy extends well beyond
technical comprehension. It involves the ability to critically evaluate AI
systems in terms of accuracy, transparency, and fairness (Long & Magerko, 2020).
AI systems are often described as “black boxes,” meaning that their internal
workings are obscure, even to their developers. This makes it difficult for
users to understand how decisions are made or to contest biased outcomes. For
example, when AI is used in hiring or credit scoring, it may reflect or even
amplify existing societal biases, particularly if it is trained on historical
data that already includes discrimination. Individuals with AI literacy are prone
to ask essential questions: Who designed this system? What data was it trained
on? Who benefits, and who might be harmed?
Data rights are a critical concern in the context of AI
training, as massive datasets containing personal and publicly available
information are needed to develop effective machine learning models. When AI
systems are trained on data that includes sensitive or identifiable information,
such as social media posts, biometric data, or online behavior, there is a risk
of infringing on individuals' rights to privacy, consent, and data ownership.
Many individuals are unaware that their digital interactions and even records may
be collected and used for AI development without their explicit permission,
raising serious ethical and legal concerns (Crawford, 2021). Issues of data
provenance, consent, and transparency become especially pressing when such data
are used in systems that influence decisions related to hiring, law
enforcement, healthcare, or education. Ensuring that individuals retain control
over how their data are used requires the enforcement of robust data protection
laws, implementation of informed consent mechanisms, and use of
privacy-preserving techniques like data anonymization and minimization (Veale
& Binns, 2017). As the capabilities of AI systems continue to expand,
prioritizing data rights is essential for protecting individual autonomy and
fostering public trust in AI technologies (Solove, 2025).
Equally important is the ethical and social dimension of AI
literacy (Crawford, 2021). AI is not a neutral technology. It is shaped by the
values, assumptions, and power structures of those who build and deploy it.
Ethical AI literacy encompasses
awareness of how AI can perpetuate systemic inequalities, its impact on privacy
and surveillance, and its contribution to labor displacement or environmental
degradation. For instance, AI-driven surveillance systems have been
disproportionately used against marginalized communities, raising concerns
about civil liberties. In addition, the environmental impact of training large
AI models, including the carbon emissions from running massive data centers, is
increasingly recognized as a significant ethical concern.
Civic and societal engagement are also critical components
of AI literacy. Across disciplines and sectors, there is a growing recognition
of the need for public involvement in decisions surrounding the use of AI.
Engaging the public in governmental decision-making is essential for supporting
democratic processes and reducing the potential harms associated with AI.
However, the opaque nature of AI systems, their rapid evolution, and the
substantial resources they demand can hinder meaningful civic participation
(Sieber, 2024). Informed citizens are better equipped to participate in
democratic processes related to AI, such as public consultations, advocating
for equitable AI policy, and demanding algorithmic accountability. As AI
becomes central to public decision-making, from predictive policing to resource
allocation, AI literacy allows people to challenge unjust uses and propose
alternatives that are more transparent and inclusive.
The importance of AI literacy cannot be overstated. AI
literacy enables people not only to use AI tools effectively but also to
critically assess their impact and participate in shaping their development. It
promotes individual empowerment by helping people make informed decisions about
their digital lives, such as protecting their data, choosing platforms that
respect privacy, and recognizing manipulative algorithms. It also contributes
to social equity by ensuring that marginalized groups are not left behind in
the algorithmic age. Furthermore, AI literacy prepares workers for the changing
demands of the labor market and supports critical thinking in the face of
misinformation and automated influence in democratic systems.
AI
Literacy and Adult Education
AI literacy is playing a growing role in shaping the goals
and methods of adult education by equipping learners with the critical
understanding needed to navigate, evaluate, and utilize AI in both personal and
professional contexts. As AI becomes increasingly integrated into workplaces,
civic life, and everyday decision-making, adult learners must develop a foundational
understanding of how AI systems operate, their capabilities and limitations,
and the ethical implications of their use. Adult education programs that
integrate AI literacy foster digital agency, enabling learners to make informed
choices about their data, interact responsibly with AI technologies, and
participate in public discourse about the societal impacts of AI (Long &
Magerko, 2020).
AI literacy in adult education promotes lifelong learning
and workforce adaptability. According to the World Economic Forum (2025),
workers can expect that approximately 39% of their current skills will either
be significantly transformed or rendered obsolete. Leading the demand for new
competencies are skills in AI and big data, followed closely by expertise in
networks, cybersecurity, and overall technology literacy. Alongside these
technical proficiencies, there will be a growing emphasis on human-centric
capabilities such as creative thinking, resilience, adaptability, curiosity,
and a commitment to lifelong learning, all of which are anticipated to become
increasingly vital in the evolving workforce landscape.
Storey and Wagner (20240 comment that AI has transformed the
role of adult educators by evolving the learning environment into an open,
intelligent system that adapts to learners' needs. They further state that this
shift presents ongoing challenges, including ethical concerns regarding data
privacy, intellectual property, cybersecurity, and academic integrity, all of
which must be continually addressed and regulated in tandem with AI’s rapid
advancement. To ensure meaningful and relevant learning experiences, adult
educators must adopt research-based approaches to curriculum design that
incorporate AI literacy and competencies. The integration of AI in adult
education prompts educators to reconsider and redefine their roles, pushing
them to enhance their andragogical strategies, analytical thinking, and digital
literacy.
Integrating AI literacy into adult learning environments can
help reduce digital inequality by ensuring that all learners, regardless of
background, have access to knowledge that is increasingly essential in a
digitally mediated society (UNESCO, 2021). This approach promotes equitable
participation in the evolving digital economy and enhances democratic
engagement by fostering informed citizenship in an era of algorithmic
influence.
Conclusion
To cultivate AI literacy, (a) educational institutions must
integrate it into curricula, (b) governments and organizations should promote
public awareness, and (c) workplaces should provide training that addresses
both the technical and ethical aspects of AI. Civic organizations can also play
a key role by making AI literacy accessible to underserved communities. As AI
continues to shape the future, AI literacy is no longer optional. It is a
fundamental skill for navigating, questioning, and influencing the increasingly
automated world.
At
the Adult Learning Exchange Virtual
Community, we invite you to share your experiences, tools, and questions in
the AI Literacy Forum, moderated by
Drs. Simone Conceição and Lilian Hill. Together, we can explore how to harness
AI for more inclusive, effective, and empowering adult learning.
References
Crawford, K. (2021). Atlas of AI: Power,
politics, and the planetary costs of artificial intelligence. Yale University
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
Noble, S. U. (2018). Algorithms of oppression:
How search engines reinforce racism. NYU Press.
O’Neil, C. (2016). Weapons of math
destruction: How big data increases inequality and threatens democracy.
Crown Publishing.
Sieber, R., Brandusescu, A., Sangiambut,
S., & Adu-Daako, A. (2024). What is civic participation in artificial
intelligence? Environment and Planning B: Urban Analytics and City
Science, 0(0). https://doi.org/10.1177/23998083241296200
Solove, D. J. (2025). On privacy and
technology. Oxford University Press.
Storey, V. A., & Wagner, A. (2024).
Integrating Artificial Intelligence (AI) Into adult education: Opportunities,
challenges, and future directions. International Journal of Adult Education
and Technology, 15 (1), 1-15. https://doi.org/10.4018/IJAET.345921
UNESCO. (2021). AI and education:
Guidance for policy-makers. https://unesdoc.unesco.org/ark:/48223/pf0000376709
World Economic Forum. (2025). The Future
of Jobs Report 2025. https://www.weforum.org/publications/the-future-of-jobs-report-2025/digest/
