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Have you fallen down the rabbit hole of AI-generated citations? It can seem like a bottomless pit. It’s our job as quality content producers to trace each citation to the original source and vet that source.<\/p>\n
getty<\/p>\n
There\u2019s a moment I keep returning to. I\u2019m looking at a list of citations in a commissioned research report that a client gave me\u2014work created with the help of generative AI. I click one link. Then another. And another. And I keep falling down rabbit holes.<\/p>\n
On the surface, the research I received looked robust. It had links to the sources and was technical in nature. <\/p>\n
But as I dug, the floor kept falling away. Sources included blogs of uncertain origin and articles, even on reputable websites, that didn\u2019t cite their sources.<\/p>\n
Some of the source materials that did have attribution for their cases and data points provided references that were vague. <\/p>\n
I knew that the commissioned research I received had been written by a machine, but how much of what the research pulled together was also written by a machine? <\/p>\n
This is the paradox we now face. <\/p>\n
The act of citation\u2014once the reliable compass of journalists, academics, and credible creators\u2014is simultaneously easier and more treacherous than ever.<\/p>\n
With AI Citations, The Old Rules No Longer Apply<\/p>\n
As a journalist trained to pursue editorial rigor, I was taught to follow the citation trail to its source<\/a>. Editors drilled it into us: \u201cGet the original. If you can\u2019t, find a credible institution that has.\u201d We had a healthy skepticism for statements that began with \u201csources say.\u201d We looked for names, numbers, and the paper trail to the facts.<\/p>\n But now, AI can generate its own footnotes and citations, not to mention reports. We are flooded with references that seem solid. <\/p>\n But citations are no longer a guarantee of veracity. Instead, they are part of a new terrain we must navigate: Where does human knowledge end and machine-generated synthesis begin?<\/p>\n Even before generative AI, there was a creeping erosion of rigor. <\/a><\/p>\n I remember reading reports where a subject-matter expert (SME) at a consulting company would cite a figure to \u201cindustry sources.\u201d Journalists would pick it up, and then it would appear in the press as \u201caccording to XYZ Consulting.\u201d Suddenly, the number became legitimate by virtue of repetition, not investigation.<\/p>\n Now, magnify this with generative AI. We\u2019re a few missteps away from becoming a society of parrots quoting parrots quoting machines.<\/p>\n Thought Leadership Demands Rigor With AI Citations<\/p>\n As someone who works in thought leadership, I feel this tension acutely. My clients rely on me to help them elevate their ideas\u2014and to ensure their content stands on a foundation of facts. <\/p>\n That means doing the grunt work: tracing sources, verifying data, and reading original papers. It\u2019s not glamorous. It\u2019s often tedious. But it\u2019s essential. Otherwise, thought leadership collapses into something without integrity. <\/p>\n The thought leadership world is actively working to address this and other challenges. The Global Thought Leadership Institute (GTLI)<\/a>, where I serve as a board member, is establishing standards for high-quality content<\/a>\u2014including sourcing practices. We understand that we need shared norms for quality and trustworthy thought leadership. And that\u2019s what we\u2019re working toward.<\/p>\n The New Psychology Behind Citations<\/p>\n There\u2019s a cognitive shift going on around citations that we must acknowledge. Clicking a citation today no longer gives us an actual answer or source. It gives us options\u2014often too many. You may discover something solid, but you may also be thrown into an infinite regress of interpretations, summaries, and machine-generated variants. Each one may be subtly different, causing you to think it\u2019s a new or different source. Each one will beg the question: Where\u2019s the actual original source?<\/p>\n We are left with citation fatigue, creeping distrust and the potential for intellectual paralysis. <\/p>\n Who has the time to vet every source in a 40-page deck created by generative AI? <\/p>\n And yet, how can we not? <\/p>\n In the past, the process of research was linear: read, evaluate, cite. Now, it\u2019s uncertain. It feels like swimming in a pool where you\u2019re never sure if the bottom is two feet down or two hundred.<\/p>\n Journalists Were Trained To Run Down Sources. Most People Weren\u2019t.<\/p>\n This is where my journalistic roots are both a curse and a compass. I was trained to sniff out the weak link in a source chain. But many people writing for publication today weren\u2019t.<\/p>\n They may be brilliant thinkers. But they haven\u2019t necessarily been taught to distrust that seemingly credible post. Or to reverse-image search that graph or image. Or to ask: \u201cWas this blog post paraphrased from a machine output?\u201d<\/p>\n We are living through a disruption in knowledge at many levels.<\/p>\n