How cognitive elaboration fosters knowledge acquisition on social media—a field experiment
Abstract. Social media technologies have been criticized as ineffective sources of information because users seem to increase their subjective but not thei
Experimental evidence of the effects of large language models versus web search on depth of learning
Abstract The effects of using large language models (LLMs) versus traditional web search on depth of learning are explored. A theory is proposed that when individuals learn about a topic from LLM syntheses, they risk developing shallower knowledge than when they learn through standard web search, even when the core facts in the results are the same. This shallower knowledge accrues from an inherent feature of LLMs—the presentation of results as summaries of vast arrays of information rather than individual search links—which inhibits users from actively discovering and synthesizing information sources themselves, as in traditional web search. Thus, when subsequently forming advice on the topic based on their search, those who learn from LLM syntheses (vs. traditional web links) feel less invested in forming their advice, and, more importantly, create advice that is sparser, less original, and ultimately less likely to be adopted by recipients. Results from seven online and laboratory experiments (n = 10,462) lend support for these predictions, and confirm, for example, that participants reported developing shallower knowledge from LLM summaries even when the results were augmented by real-time web links. Implications of the findings for recent research on the benefits and risks of LLMs, as well as limitations of the work, are discussed.
The Interplay of Knowledge Overestimation, Social Media Use, and Populist Ideas: Cross-Sectional and Experimental Evidence From Germany and Taiwan - Niels G. Mede, Adrian Rauchfleisch, Julia Metag, Mike S. Schäfer, 2024
Social media expose users to an abundance of information about various issues. But they also make it difficult for users to assess the quality of this informati...
The rise of community-curated knowledge networks
The Internet put thousands of years of human thought at our fingertips, and enabled billions of people to create content. At least 2.5…
Illusion of knowledge through Facebook news? Effects of snack news in a news feed on perceived knowledge, attitude strength, and willingness for discussions
Research indicates that using social network sites as a source for news increases perceived knowledge even if, objectively, people fail to acquire knowledge. This might result from the frequent repetition of topics in news posts caused by multiple news outlets posting about the same news topics and the algorithm that favors similar postings. These repeated encounters can have a positive effect on the perception of knowing more, even if actual learning hardly occurs. An experiment (N = 810, representative of German Internet users) tested these assumptions. Participants were assigned to one of four groups and received a news feed with no information, few news posts, many news posts, or a full-length news article. Results indicate that many news posts increased perceived knowledge that is not paralleled by a gain in factual knowledge. Perceived knowledge mediates effects of reading many news posts on more extreme attitudes and the willingness for discussions. Even if participants who read the news article gained factual knowledge, they did not feel more knowledgeable than participants who were exposed to a news feed containing news posts. The results emphasize the meaning of engaging with full news articles, both for learning facts and for more accurate knowledge assessments.
What matters in the age of AI is taste
the case for why a curated personal knowledge base has never mattered more
Knowledge Collapse
AI companies are racing to mechanize mathematics. Where does that leave human understanding?
Valerio Capraro on Twitter / X
Our new paper shows that AI destroys the wisdom of uncertainty.The willingness to say “I don’t know” collapses from 44% to 3%.This happens even when the AI’s advice is wrong. Consequently, correct answers fall from 27% to 9%.Yes: some people who would otherwise answer… pic.twitter.com/l0YZ75IFHn— Valerio Capraro (@ValerioCapraro) August 10, 2026
Notion’s Knowledge Board
Evaluating how models perform across a range of knowledge work tasks, using live anonymized traffic and judged by models from Anthropic, OpenAI, and Google. An ongoing experiment.
The Extended Internet Universe
The Internet is now a very complicated place
What Was the Internet?
As AI overtakes the web, five writers reflect on how far it’s fallen and what comes next.
What Was the Internet?
As AI overtakes the web, five writers reflect on how far it’s fallen and what comes next.
See what you think
Allegra A. Beal Cohen's blog about knowledge curation, new interfaces, and large-scale qualitative data.
The internet has evolved to foster a fatal expectation: that the things we depend on every day are free. They aren't, but we're allowed to pretend they are with the help of ad-driven business models. The real cost is substantial, and can be measured in time, money, relationships, health, and more.
Fund Your Internet
fundyourinternet.org