FEATURE
How Libraries Can Teach Deepfake Evaluation
by Susan McClellan

---

By documenting instructional strategies, assessment results, and community feedback, libraries can help build a body of knowledge about what works in deepfake education.

Media landscapes have shifted more rapidly than ever, and one of the most challenging developments is the rise of deepfake technology. A deepfake is a type of synthetic media created by AI that can convincingly mimic real people and real events. These digital creations can affect public perception, political discourse, and even personal lives. As a result, it is essential for people to gain the skills needed to recognize and evaluate deepfakes. Libraries are uniquely positioned to take a leading role in this work to help individuals navigate a world in which truth and fabrication are more tightly intertwined than ever before.

This article explores why deepfake evaluation matters, describes how libraries can design effective instruction, and provides examples of practical programs. The goal is to show that libraries are not just repositories of content—they are education hubs for media literacy and critical evaluation in the face of today’s digital environment.

Why Deepfake Evaluation Matters

Deepfake technology originated when large datasets and advanced neural networks made it possible for AI to transform photos, videos, and audio clips in ways that were previously unimaginable. At first, deepfakes attracted attention because they offered humorous or novel entertainment, but now they raise serious ethical concerns. Manipulated videos of politicians, fabricated speeches by public figures, and synthetic endorsements by celebrities have all appeared online. The lines between what is real and what is generated have become increasingly blurred.

Deepfake evaluation is about truth. People who cannot distinguish manipulated content from authentic material can be misled, which can influence elections, erode trust in institutions, and damage the reputations of private individuals. Conventional cues that once helped observers detect misinformation do not work as deepfakes get more sophisticated. Librarians and educators face the challenge of teaching people to identify false information as well as how to understand the broader context in which that information appears. The ability to evaluate information is a fundamental life skill. It is part of media literacy, information literacy, and digital literacy. These are not niche competencies. They are essential knowledge for anyone who engages with online content, participates in civic life, or makes decisions based on what they see and hear.

The Role of Libraries in Media and Information Literacy

Libraries have evolved significantly over the past few decades. Once primarily places to store and lend books, they are now community hubs for learning, research, and cultural exchange. In public, school, and academic libraries, instruction on evaluating sources and discerning credible information has become a core part of service. Teaching deepfake evaluation is a natural extension of existing library instruction in media and information literacy. These programs typically include helping patrons learn how to determine the credibility of news articles, check facts, recognize bias, and use search tools effectively. Deepfakes present a new frontier in this work that is directly tied to the rise of AI.

Libraries have numerous advantages that make them particularly well-suited to teach deepfake evaluation. They are trusted institutions with a history of teaching people how to think critically. Patrons already view libraries as places of learning and discovery. They serve diverse populations, reaching students, adults, seniors, and underserved groups who might not otherwise have access to formal media literacy training.

Designing Effective Deepfake Evaluation Instruction

Good instruction begins with clear goals. Libraries that want to teach deepfake evaluation should first consider what outcomes they hope to achieve. On a basic level, participants should gain familiarity with what deepfakes are and why they matter. They should learn strategies for examining content for signs of manipulation. They should understand how deepfakes are created and how technology continues to evolve. Some libraries may offer standalone workshops dedicated specifically to deepfakes, while others might integrate deepfake evaluation modules into broader media literacy courses or digital literacy initiatives. The key is to ensure that deepfake instruction is accessible, engaging, and relevant to participants.

Instruction should be designed with active learning in mind. Rather than simply lecturing, librarians can incorporate guided practice, group discussions, and case studies. For example, participants could be shown a series of videos and asked to work in small groups to determine whether they are authentic or manipulated. Afterward, they could share their reasoning and reflect on what cues were helpful or misleading. Libraries that partner with local schools, universities, or community organizations can expand the reach of their programs. Collaboration with teachers and professors can help align deepfake evaluation instruction with existing curricula. Partnering with technology centers can bring additional expertise and resources into the library environment.

Core Instructional Strategies for Deepfake Evaluation

Teaching deepfake evaluation is about helping learners develop skills that they can apply in real-world situations. Several instructional strategies are particularly effective in this context. 

First, teaching context matters. Deepfakes do not appear in isolation. They are shared on social networks, embedded in news stories, and circulated through messaging platforms. Learners need to understand the broader ecosystem in which media appears. This means looking at sources, cross-referencing information, and considering who created and shared a piece of content. Teaching people to ask questions about context can help them move beyond surface-level impressions.

Read more: FEATURE – How Libraries Can Teach Deepfake Evaluation – Information Today – Computers in Libraries (July/August 2026)

Source: FEATURE – How Libraries Can Teach Deepfake Evaluation