ai chatbot advertising influence answers a speech bubble pod with a rounded tail

Advertising Is Coming to AI Chatbots — and It Could Influence the Answers You Get

September 17, 2026
AI News
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On 16 September 2026 four marketing and management scholars published an analysis in The Conversation arguing that advertising inside AI assistants is structurally different from anything the web has done before, because the ad sits inside the generated answer rather than beside it. The piece opens with Brin and Page’s 1998 warning that advertising-funded search would be inherently biased toward advertisers. This article covers what OpenAI, Google and Perplexity have shipped, the four risks the underlying research identifies, why fact-checking and media literacy do not reach private ephemeral chats, and what a policy response would have to cover.

X Claims It Found a Chinese Bot Farm Posting Anti-AI Data Center Sentiments

August 28, 2026
Artificial Intelligence
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On 27 August 2026 X’s Global Government Affairs account said its Safety team had identified a Chinese bot farm of roughly 200,000 inauthentic accounts, and that 200 of them were posting comic strips and text claiming AI data centers raise household electricity bills and strain local grids. This breakdown covers exactly what X disclosed and in what words, how the artwork ties the accounts to the “Data Center Bandwagon” campaign OpenAI named and banned in June 2026, why 200 accounts are a rounding error next to a domestic backlash that has stalled roughly $130 billion of construction in a single quarter, what PJM capacity prices and Goldman Sachs forecasts say about electricity bills, and the methodology X has still not published.

Veracity Reveals the Sources Behind Its AI Fact Checks With 0-100% Reliability Scores

August 27, 2026
Artificial Intelligence
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Veracity is an open-source fact-checking system from Montreal’s Complex Data Lab that pairs a large language model with a web retrieval agent and refuses to answer without showing its evidence. Every claim comes back as a reliability score between 0% and 100%, a plain-English interpretation, a share recommendation gated at 60%, and a panel listing every source consulted along with its documented credibility. This breakdown covers the five-stage pipeline, the stack behind it, why the 60% cutoff is the most questionable decision in the design, what independent benchmarks say about the roughly 83% real-world accuracy ceiling for automated fact-checking, and how to evaluate any claim-scoring layer before you let it near a workflow.