Bridging Expertise and Organizational Culture: Libraries as Leaders in AI Literacy

The question of whether libraries can effectively teach AI literacy and ethics, despite internal organizational challenges, reflects a broader misunderstanding of the distinction between institutional culture and professional expertise. While some libraries—like many organizations—grapple with workplace dynamics that can be less than ideal, this does not diminish the knowledge, dedication, and ethical commitment of library professionals. In fact, it is precisely in these challenging environments that AI literacy and ethics become even more crucial.

It’s important to distinguish between the culture of an organization and the expertise of its staff. While some libraries—like many institutions—may struggle with toxic workplace dynamics, this does not negate the ability of library professionals to teach AI literacy and ethics. In fact, it’s often the case that toxicity stems from ineffective leadership or structural issues rather than from the staff themselves, who are deeply committed to intellectual inquiry, education, and ethical discourse.

Librarians are uniquely positioned to lead AI literacy efforts because their work is deeply rooted in information ethics, critical evaluation, and accessibility. Their training in information science equips them to address algorithmic bias, data privacy, and responsible AI usage. These issues align with the longstanding role of libraries in fostering discussions about censorship, knowledge production, and equitable access to information. Additionally, Ruha Benjamin’s Viral Justice reminds us that small, intentional actions can drive systemic change. By incorporating AI literacy and ethics into library services, librarians contribute to a more equitable information landscape.

A Library’s Journey Toward AI Literacy

At a small academic library, a group of librarians noticed a gap in student awareness regarding AI’s impact on research. Many students relied on AI-generated summaries but lacked the skills to assess credibility and bias. Recognizing this, a librarian named Sam took the initiative to start an informal AI literacy workshop. Despite internal challenges—limited institutional support, tight budgets, and leadership resistance—Sam followed a step-by-step approach, demonstrating how small efforts could lead to meaningful change.

Sam applied the CALM Framework—Communication, Adaptability, Learning, and Management—to shape the program:

1. Communication: Fostering Inclusive Dialogue – Sam organized open discussions about AI literacy, bias, and ethics, ensuring diverse student voices, including those from underrepresented groups, were included in the conversation.

2. Adaptability: Responding to Evolving AI Technologies – As new AI tools emerged, Sam refined the workshop curriculum to keep up with trends while ensuring accessibility for students with diverse learning needs.

3. Learning: Investing in Knowledge Sharing – Sam pursued free professional development opportunities, engaging with AI literacy research, and shared insights with colleagues to build a collective understanding of the subject.

4. Management: Leading Ethical AI Initiatives – Even in the absence of direct administrative support, Sam worked collaboratively with faculty to integrate AI literacy into research instruction, demonstrating its value through student engagement and feedback.

Small but Impactful Actions for Inclusive AI Literacy

1. Create AI Literacy Programs – Develop structured AI literacy programs tailored to different audiences, incorporating discussions on bias, misinformation, and ethical AI use.

2. Leverage Institutional Partnerships – Collaborate with academic departments, IT teams, and external organizations to integrate AI literacy into curriculum and public programming.

3. Advocate for Ethical AI Policies – Engage in institutional policy discussions on AI adoption, ensuring that AI tools align with ethical standards and accessibility guidelines.

4. Foster Open Conversations – Encourage ongoing dialogue among library staff about AI ethics and workplace culture, promoting transparency and inclusivity.

5. Develop Resource Guides – Curate and provide access to research guides, webinars, and open educational resources on AI literacy and ethics for library users and staff.

6. Lead by Example – Model ethical AI use within the library, demonstrating transparency in AI-powered services, citation tools, and discovery platforms.

Emotional Intelligence in AI: Bridging Philosophical Foundations and Emerging Technologies

As libraries advance AI literacy to equip users with both technical and critical thinking skills, academic librarians play a crucial role in teaching students how to critically engage with AI tools. Integrating Emotional Intelligence (EQ) into AI literacy initiatives enhances students' ability to engage thoughtfully and reflectively with AI-generated content.

Librarians can teach students to use AI tools like Grammarly’s tone detector or generative AI chatbots to assess and refine the tone of their communication. By prompting students to consider the who, what, when, and where of their writing, they learn how AI influences tone, context, and clarity in emails to professors, workplace communication, and academic writing. This approach mirrors the way students craft narrative essays, emphasizing place, time, and audience awareness.

Librarians as AI Literacy Instructors: Teaching Critical Thinking Through AI Tools

1. Using Grammarly’s Tone Detection – Librarians guide students in evaluating AI-generated suggestions, teaching them to adjust language based on audience, context, and intent rather than allowing AI to dictate tone automatically.

2. Teaching Generative AI Tools – By demonstrating how tools like ChatGPT can assist with writing support while requiring human judgment, librarians emphasize ethical and mindful AI use.

3. Training in Bias Detection – AI systems often reinforce dominant linguistic patterns and cultural norms. Librarians expose students to these biases, prompting critical examination of AI-driven communication tools.

By actively engaging with AI-generated suggestions rather than merely accepting them, students develop habits of intellectual skepticism, inquiry, and ethical reflection—essential components of critical thinking.

Navigating Cultural and Linguistic Diversity in AI Literacy

While Emotional AI offers transformative possibilities for empathetic and adaptive communication, it also presents challenges related to cultural nuance, idiomatic expressions, and linguistic diversity.

Librarians play a critical role in ensuring that AI literacy programs empower students to critically engage with AI rather than conform to its biases. AI literacy initiatives help students:

• Critically evaluate AI-generated tone and grammar suggestions to recognize when AI models favor dominant linguistic norms over authentic self-expression.

• Adjust AI-generated content for clarity without erasing cultural identity, ensuring inclusivity in academic and professional writing.

• Identify AI misinterpretations of idioms and refine AI-generated text to align with intended audiences while maintaining cultural authenticity.

Rather than dismissing libraries’ role in AI literacy due to organizational challenges, we should focus on empowering staff with the resources, professional development, and institutional support needed to foster ethical and informed discussions on AI. If anything, a workplace struggling with toxicity should be even more invested in AI ethics, as issues of bias, power, and misinformation in AI systems mirror the very challenges that can arise in organizational culture.

The key is to ensure that AI literacy initiatives are designed and led by knowledgeable professionals who can separate their expertise from workplace dysfunction. By doing so, libraries can serve as essential spaces for public education on AI ethics, even while they work to improve their own internal cultures.

Ultimately, the question should not be whether libraries can teach AI literacy, but how we can better support librarians in this vital role. By integrating the CALM framework and embracing Benjamin’s vision of small, actionable changes, we can make lasting improvements that foster inclusive, ethical, and informed AI literacy in libraries.