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INFOLIT LAND
The World Is Flat After All, and It’s Not a Good Thing
by William Badke
Michael Flierl, AI Faculty Fellow at The Ohio State University, pointed out during a recent workshop that information literature’s cherished mantra, “Authority is constructed and contextual,” no longer works that well. Why not? Essentially, because the new AI reality makes it impossible for us to investigate the authorship of a large portion of open online information. Authorship evaluation is key to determining authority. What do we do when the “author” is unknown?
That, of course, has been the case ever since the web appeared in the late 1980s. We have become Google junkies, accessing “knowledge” that often arrives without a clear authorship statement. For a more recent trend, we now get an AI answer to our Google query, scarcely thinking that the answer was formulated by a mindless bot whose qualifications are impossible to determine.
Knowledge in the past was clearly variable in its levels of authority. A piece of gossipy news from your best friend Betsy was at the low end, devoid of evidence and possibly filled with self-interest. Everyone knows Betsy is always telling wild stories. At the other end was a rigorous study by a noted scientist, peer-reviewed and evidence-filled. In between was a long continuum, a mountainous terrain of information with varying levels but relatively identifiable authority.
Now we live on an information plain, where the authority of what we encounter is often undefined and undefinable. There is little perceived nuance, few hills and valleys. We trudge through this flat landscape, picking up what we need and generally paying little attention to evaluation. Information is information. Why wouldn’t I believe an AI answer coming out of a search engine? Why isn’t an “intelligent” social media post as good as a “scholarly” article from a scientist? Who trusts scientists anyway?
The Flat World
I have long taught my students that information belongs within contexts. If I use the word “rock,” for example, I can only really provide a sense of my meaning by putting the word into a sentence: “I like classic rock music,” or “Don’t trip over that rock in the path.” This makes our knowledge hierarchical, with upper-level broad categories cascading down into narrower subcategories until rock becomes classic rock in one context and a hard substance from the earth in another.
Similarly, the level of informational rigor varies from a scholarly article with 75 references, built on strong research and deep interaction in the scholarly conversation, to a social media post or a TikTok video. Is one better than the other? Probably yes, as elitist as that may seem, simply because of the level of work and expertise that went into the scholarly article. The social media post may be a useful primary source, but for most of us, it is ephemeral and in need of solid vetting.
Now, imagine a world where the distinctions are lost. People don’t pay attention to the scholarship of an academic article or to the possible flaws in a social media post. It’s all grist for the mill of our information processing. AI draws from the highest and lowest of our knowledge and makes its assertions in some sort of flat middle simply called “the answer to a prompt.”
I recently interacted with an adult student, himself accomplished in his field of work, who presented me with several means to evaluate information while never making a single reference to the author or the author’s qualifications. The evaluation process, for him, is always assessing the information itself but never considering the differences in the creation process or in the creator.
This is the flat world, where Google or generative AI becomes the world’s library catalog, delivering “knowledge” without the hierarchies of authorship, rigor of research, or niceties of a creation process. Sure, there may be heights and depths somewhere to explore, but who cares? If I need to know something, Gemini tells me what I need to know. Information in a flat world has no distinctions. It simply is what it is. Thus, the democratization of knowledge turns into an indistinguishable horizon of sameness.
Does It Matter?
Most people are not scholars. They are regular folk who live their lives without giving much thought to scholars doing research or experts devising new and better ways to address problems in their fields. They might read about a scientific breakthrough and say, “That’s interesting,” but they rarely see much nuance in levels of information quality. Is it so bad that AI answers their questions and gets things mostly right? Do we really need to read a journal article a day to remain intelligent?
The fact is that, for many of us, the flat information world is good enough. It’s not perfect. We’re not stupid, after all. But we believe most of what we encounter, and if some of it is faulty, that’s just life. Nothing’s perfect, but most of the information we encounter is good enough.
The Student Experience
Enter higher education, where we introduce students to nuance, to a terrain with mountains and valleys, lakes and deserts. This is the place of the great awakening, where those we teach leave the flat world behind and encounter information creation as a process and authority as constructed and contextual. What a glorious way to defeat the dreadful sameness of most people’s information encounter.
Except that it doesn’t work like that, at least not enough to make a significant difference. First, many of our students continue to prefer Google and AI, not really understanding how academic, well-researched knowledge can provide them with more reliable knowledge. Academic knowledge is a strange world loved by professors, though it’s not clear why. Second—and this is much more significant—we are doing precious little to introduce our students to this information landscape.
How so? Students, every day, encounter knowledge in our disciplines, hear our lectures, and even write research papers (if we’re not so afraid of AI cheating that we cancel such projects). We encourage critical thinking, while not overtly teaching it, and see some measure of growth by graduation time.
But it’s mostly a failure. If a college student feels justified asking, “Why can’t I just use Google?” that student is living in a flat world. To message back, “You can’t use Google because our databases are better” says almost nothing. Better in what ways? More difficult to use? Delivering resources that are harder to understand? Produced by scholars and scientists, who are superior to the rest of us?
The average student (and I have asked them repeatedly) has no clear idea why we assign them research projects for which the goal seems to be to deliver a product acceptable to the professor, even though the initial instructions are almost always unclear. What makes this process superior to simply querying a search engine or letting Gemini provide an answer?
We have not explained to our students that the information world is not flat (or it shouldn’t be), because author qualifications matter, as does rigorous process, the scholarly conversation that provides checks and balances, and the machinations of peer review. Scholarship is not merely elitist. It is the foundation of more reliable knowing. Google, AI, and their siblings are utterly dependent on that scholarship, even as they level it out on the plain.
Rising Above
We rejoiced when the web emerged in the early 1990s. The democratization of knowledge and the massive expansion of both the content of and access to information were a blessing. All good, right? Except that the web became a giant hand sweeping over our knowledge and flattening most of it into a plain in which gatekeeping and review became much less important than simply having the “knowledge” available. Now, AI slop serves as a massive puddle on the plain.
Don’t get me wrong. For all its challenges, I love the web. What I don’t love is the way we let it stand in for an information landscape, blinding its users to the value of expertise, authoritative research, and efforts to evaluate what we are encountering. Higher education had the opportunity to guide our students, but we haven’t. Not really.
Overcoming the Current Pattern
How do we go about overcoming the current pattern and rising above it?
- Teach the scholarly enterprise: what it is and why it matters. Here, the ACRL Framework for Information Literacy for Higher Education is a great tool. See, for example, my Prezi on the Framework entitled, “What Is Scholarship?” (prezi.com/view/1lKC4FNM5hhZVGCx2JQf). There are mountains and valleys, and they are important. Scholarship is not some elitist enterprise reserved only
for those who like that sort of thing. It is the driver of the knowledge we all rely upon.
- Teach the value of expertise. Crowdsourcing is well and good, but we need experts in every sphere of life, from designing a better toaster to treating Aunt Betsy’s cancer. This is the territory of mountains and valleys.
- Do disciplinary enculturation, which views disciplines as communities of practice, rather than a body of respected knowledge, a culture that gives a discipline its identity, and a set of methodologies trusted to produce reliable results. See my LibGuide: libguides.twu.ca/DisciplinaryEnculturation.
- Tell our students why we are giving them research projects (if we still give them, and we need to find a way to do so). Simply regurgitating existing data is what AI does and has no meaning or purpose. Doing a solid, problem-based project demands use of evidence-filled resources, scholarly conversation, and levels of argumentation that move us off the flat plain and into the hills.
What This Means for the Future
I am regularly reminded of the movie Idiocracy, in which a future society has become so stupid that it can only muddle through its existence, never seeing nuance nor making progress. We are in idiocracy territory right now, gulping down AI-generated answers to any question we may think of and assuming that our “information” is good enough. While the scholars are doing whatever they are doing, most of us are happy with a flat information world.
This is a recipe for degeneration. Our students are already finding it more and more difficult to read. They don’t understand scholarship or even see much value in expertise. As long as their tech feeds them a steady diet of whatever “information” and entertainment they want, they are content. And doomed. The world should not be flat. Let’s help our students find the mountains. |
