AI Challenges How Society Values Knowledge

The essay published by Global Research on May 3, 2026 argues that AI and Big Data are transforming public epistemology by shifting emphasis from learning to querying. The piece quotes Roberto Calasso: "We will then be close to knowing almost everything we don't need to know," and uses that line to frame a broader warning that AI assistants such as Siri and Alexa will relieve people of the "burden of knowing anything except how to ask AI the answers to everything." The article also notes the Internet's historical roots in the Pentagon's ARPANET and presents surveillance-capable platforms, mainstream media, and intelligence-linked actors as consolidated sources of epistemic control as reported by the essay.

Industry-pattern observations: information overload and automated ranking systems shift value from raw data to curation, retrieval, and provenance. Systems optimized for engagement routinely surface content that maximizes attention rather than factuality; practitioners have increasingly focused on retrieval-augmentation, attribution, and factuality metrics to counter those incentives. Greater use of closed-source proprietary models and opaque ranking signals raises auditability and provenance challenges that are already active research and engineering problems.

Industry context: Opinion pieces like this synthesize cultural and political anxieties about AI, surveillance, and attention economy dynamics rather than releasing new empirical findings. For practitioners, the primary operational implications are not the essay's rhetorical claims but the persistent governance questions it highlights: how to instrument models for provenance, measure truthfulness, and design user interfaces that surface source context.

Indicators an observer can follow include deployment patterns for AI assistants and browser-integrated retrieval features, adoption of model and dataset provenance standards, regulatory moves that mandate explainability or provenance, and empirical work measuring the effects of query-first interactions on information retention and trust. The essay does not cite empirical studies quantifying cognitive change; it offers a cultural critique that signals where public debate and governance pressure may focus next.