Gemini, Google’s new AI assistant, is a conversational AI chatbot. It used to be known as Bard, another conversational AI chatbot from Google. Like Bard, Gemini uses large language models to generate text or images when prompted by a user, but Gemini is trained on a much larger dataset than Bard was and can perform much more specific, specialized tasks.

Google says that Gemini gives users “direct access to Google AI” and can help with “writing, planning, learning and more.” Google also offers Gemini Advanced, a paid upgrade that lets users “experience our most capable AI models, priority access to new features, and a 1 million token context window.” Users can access Gemini Advanced within the Google suite or in their Gmail or calendar app, for example.

How Do People Regularly Interact With Gemini?

Users can regularly interact with Gemini simply by opening the Google search engine. With Gemini, when you search something on Google, the first search result often presented on the screen is an AI Overview. While this overview is generative AI as opposed to conversational AI, it still relies heavily on Gemini to provide snapshot-like answers to users’ searches.

What Does Gemini Have to Do With Information Literacy?

With the development of AI and the consideration of information literacy, the question is, really, what does Gemini not have to do with information literacy?

One aspect of Gemini and information literacy is being able to properly evaluate the reputability of sources. When Googling something, the reputability of the source of information—especially if it is just a cursory Google search—is not typically of concern to the user. Most users will not even go beyond the first page of search results, and they will draw information from what is gathered and provided by Google. If this information is not presented at the top of the page as in AI Overviews, then, typically, the first or second search result is used. The main concern for the user is getting answers quickly and is not necessarily about the reliability and reputability of where the information is coming from.

With Gemini’s generative aspect, it’s important to be concerned about information literacy when searching something on Google. Many users are not following the guidelines of information literacy when performing general, cursory Google searches. They are mostly unconcerned with where the source is drawing its information from, who is writing about the topic, the history of the website or organization, or other general factors to consider when deciding whether or not information is reputable and OK to use for a searcher’s purpose. With the Gemini generative AI responses being the first thing that a user sees on the page of search results, and the pre-established common behavior of not moving beyond the first or second search result provided, it is of concern that users will now be choosing these generated responses as their primary source of information without double-checking them. Due to convenience and a lack of general information literacy application outside of a classroom or professional setting, Google users could very well be using Gemini’s generative AI feature as their primary source of information.

Information Literacy to Data Literacy

Narrowing our focus, we are looking not only at the general characteristics of information literacy, but also at data literacy. As defined by the Harvard Business School Online, “data literacy is a term used to describe an individual’s ability to read, understand, and utilize data in different ways.” Data literacy does not require expertise; it instead requires an understanding of different types of data, common data sources, different types of analysis, data hygiene, data tools, data techniques, and data frameworks.

Data literacy falls under the umbrella of information literacy. Although there is the previously mentioned concern with users not applying some general information literacy aspects when inspecting search results in their cursory Google searches, there is even more of a concern with users not applying data literacy. One main issue is users not even knowing what data literacy is and how they need to be—if they are not already—applying it in their everyday life. This is applicable in the case of Gemini because a simple understanding of data usage and utilization will help users better grasp the importance of employing information literacy when looking for information or data. Understanding the nature of large language models, like the ones comprising Gemini, and how AI systems draw from pre-existing data on the internet is enough to comprehend why the positioning and presentation of Gemini on a search results page is something of a concern for info pros.

With general unawareness and the lack of application of information literacy and data literacy to AI-generated results, but especially Gemini (given the massive popularity of Google), considering the positioning and application of Gemini is necessary in preserving the integrity and accuracy of information being sought out by searchers. It is essential that those seeking information on the internet fact-check AI tools, do not rely solely on information provided by any generative or conversational AI model, and consider some quick, simple rules of information literacy when drawing information from general pages of search results.

Further Reading

“Understanding the Impact of Google’s Gemini AI on the Web”

“Google Gemini vs. Bard—Uncovering the Key Differences Between Gemini and Google Bard”