A reliable and effective natural language search option has been a long time coming. Although this functionality has existed for a while, many library and information professionals have stuck with the traditional boolean search. What can I say? We like to be in control of our searches and understand why a database or search engine returns the results they do.
Therefore, what do the latest developments in GenAI as a research tool mean to us as information people? The rise of GenAI and the evolving functionalities of search engines like Google and Bing are reshaping how we access and interrogate information. These tools offer natural language processing capabilities, making information access more intuitive but also raising concerns about accuracy and reliability.
This blog post explores these changes and their implications for library and information professionals - and explores a couple of interesting articles that have appeared recently.
This post was inspired by the blog post by RIPS Law Librarian. It raises some interesting issues about the diminishing effectiveness of Google search, especially in the context of legal research. It highlights a study which suggests that the prevalence of affiliate marketing and SEO-driven content in search engine results, is obscuring useful and unbiased information. How do we overcome this?
By being sceptical about everything you find online. Some things never change! In the above post, one of their recommendations to end users is to bypass the search engines and start with a trusted website and I agree. Firms, organisations, and institutions spend a lot of money on paywalled information resources so you want those to be the springboard for everyone’s research.
However, these specialist databases - for the most part - require the end user to have search expertise. Wouldn’t it be great if people could get what they needed by simply having a conversation with a database? ChatGPT and other forms of GenAI allow us to do just that. We can start with a question and then refine our responses until we get the information we need.
We want our end users to find reliable and relevant information. We have already seen exciting functionality being rolled out by large legal publishers (Lexis+AI and vLex’s Vincent AI to name just two). Vable has been exploring GenAI options and we are looking forward to sharing more about this when we are ready. There are many reasons why we should be excited:
Once you are aware of a particular issue, for example, the use of GenAI in legal research, you start seeing articles everywhere! Happily for me, the well-researched and timely article, "Is ChatGPT Any Good at Legal Research – and Should We be Wary or Supportive of it?" appeared in my current awareness today. Greg Bennett's article critically examines ChatGPT's effectiveness in legal research.
Taking advantage of the premium version of ChatGPT with the 'KeyMate.AI Search' plugin, he tests its capabilities on various legal research tasks, including interpreting legislation and referencing in OSCOLA format. He concludes that while ChatGPT demonstrates proficiency in some areas, such as accurately detailing legislative amendments, it struggles with complex legal queries and precise referencing. This is a well-known limitation.
The article also addresses ChatGPT's "hallucinations," where it generates plausible but incorrect information, and its potential to access content behind paywalls, raising concerns about the future of legal research and the role of law librarians. The discussion mirrors concerns raised in the RIPS post about the declining usefulness of Google search for legal research, emphasising the need for critical evaluation of AI tools and the continued importance of human expertise in legal information management.
GenAI is an intermediary between search engine content and the human interrogator. The problem remains that we need the quality of information to be right from the start - I hope that we have learned to be critically aware of search engine results and will continue to apply this scepticism to these emerging intermediaries! Why not think of this tech as an opportunity for professional development.
Let’s keep the following in mind:
While GenAI tools offer an interactive way of accessing and engaging with information, they are intermediaries that reflect the strengths and weaknesses of their source data. The quality of the output is contingent on the quality of the input, and this relationship highlights the ongoing need for improvements in data quality and reliability across digital information sources. They also require end users to be knowledgeable, critical, and aware of the pitfalls.