In the midst of the 4th Industrial Revolution, generative AI has emerged as a transformative force. Research librarians, well-versed in technology, now find themselves at the crossroads—navigating this new landscape and guiding researchers toward the right tools. Learn from 27 research librarians about the emerging ways they are adopting and using generative AI tools. This blog post dives into three key use cases, providing insights into the practical application of AI in libraries.
Although in reality AI is nothing new, especially for librarians, researchers, and publishers, innovative generative AI platforms like ChatGPT, Microsoft’s Bing Chat, and Google’s Gemini (formerly Bard) are now everywhere and being used commonly by seemingly everyone. Research librarians are better versed than many on AI, as information technology is central to their work. Yet many find themselves struggling to grasp the continually emerging, evolving technologies and, most importantly, direct their researchers in their use of AI.
Interviews commissioned by Springer Nature with 27 research librarians from Europe, North America, and India showed diverse perspectives on AI usage. These librarians are taking a practical approach and highlighted three main ways they’re using generative AI tools in their work.
Spanning two months, librarians from India, Italy, Spain, Germany, Romania, and the United States of America were asked about their daily use of generative AI tools. While many libraries worldwide have embraced the ‘AI Tool Revolution’ and offer resources for researchers, a significant number of librarians remain uncertain about generative AI, with some seemingly waiting for the trend to subside.
Three librarians—one each from Italy, Romania, and the United States—expressed their perspectives respectively: “I don’t use AI tools in my work,” “I struggle to understand how these tools benefit me,” and “I’m confused about AI tools.”
Within institutions, tool adoption, comprehension, dissemination, and training vary widely, depending on how engaged librarians are themselves. A German librarian noted that they often feel overwhelmed by the rapid AI advancements, unsure which tools to recommend or use. Meanwhile, research librarians lag behind students in AI tool adoption.
AI is revolutionising the librarian’s daily work, making tasks more manageable, recommendations more informed, and literature reviews more efficient. Most librarians are embracing this technological shift, confident that AI will continue to enhance their impact in the academic world.
Dozens of new generative AI tools and solutions are popping up all the time across various fields and it’s becoming increasingly difficult for librarians to keep up or keep track. As AI continues to evolve, librarians, with their expertise in information literacy, are well-positioned to help educational communities integrate these tools responsibly into both professional and personal spheres. The rise of AI presents an opportunity for librarians to educate students on the use, critique, and modification of AI-generated information.
The big question is how much librarians will get involved in this change: While libraries have been careful with new tech in the past, they’re now tackling the rise of artificial intelligence with a proactive and intentional approach.
It is clear, however, that institutions and publishers also have a part to play to ensure that librarians are equipped with the appropriate skills to incorporate new AI tools in their everyday operations. Several librarians noted this, including one librarian from India who remarked that “publishers could provide much more information on how, and when, to utilise AI tools.”
More information is also needed to “update researchers about recent developments in AI, SaaS and other electronic products that could help us,” remarked Jai Prakash, a librarian from Agra University, India.
Curious about how Springer Nature is supporting the research community? Explore the strategies outlined in our Sustainable Business Report, showcasing our dedication to developing AI capabilities in a sustainable and ethical manner for research professionals everywhere.
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