More than 60 percent of Google searches in the United States now conclude without users clicking on any links, a shift largely driven by artificial intelligence tools that deliver summarized answers directly in response to queries. Products like Google’s AI features, ChatGPT, Claude, and newer competitors such as Perplexity condense information into immediate responses, effectively shortening what was once a more exploratory journey through web content.

While this streamlined approach may appear beneficial to users seeking quick answers, experts warn it could undermine curiosity and the broader learning process. Anne-Laure Le Cunff, a researcher at the Institute of Psychiatry, Psychology and Neuroscience at King’s College London, highlights concerns based on neuroscience research indicating that curiosity is more than a simple desire for facts. It is a biological state that enhances memory and learning, triggered by the gap between what is known and unknown.

Studies show that when individuals await answers to intriguing questions, their brains engage reward circuits and activate the hippocampus, preparing the mind to absorb new information more effectively. This heightened state extends beyond the specific question and promotes incidental learning—absorbing related or unrelated material encountered during the learning process. Such learning often occurs during undirected exploration, which is now diminished by the immediacy of AI-generated responses.

Le Cunff points to historic examples, such as the discovery of cosmic microwave background radiation by physicists Arno Penzias and Robert Wilson in 1964, which resulted from sustained inquiry beyond initial findings rather than quick retrieval of known facts. She argues that the current digital environment, which eliminates the space between query and answer, risks turning questions into dead ends rather than starting points for deeper understanding and serendipitous discovery.

This evolution in search behavior may reduce opportunities for unexpected insights, as the default design of AI tools favors efficiency over exploration. While users retain the ability to browse manually and follow diverse links, the prevailing interface architecture discourages such engagement. This shift may foster a generation better at extracting ready-made answers than synthesizing new ideas from complex information.

Le Cunff suggests that AI developers could counteract these effects by designing tools that prioritize visibility of source materials, present competing explanations, and incorporate alternative search modes that encourage exploration rather than speed. She urges technology companies, including Google and others in the AI sector, to adopt practices that preserve the value in the “space between a question and an answer.” Without such measures, the capacity for discovery and innovation that thrives on curiosity and open-ended inquiry may steadily erode.