Newsar
Back to News

Signs of psychosis seen in Australian users’ interactions with AI chatbots, expert warns

The Guardian - World NewsCenter-LeftEN 1 min read 100% complete by Josh Taylor Technology reporterFebruary 25, 2026 at 02:00 AM
Signs of psychosis seen in Australian users’ interactions with AI chatbots, expert warns
Read Original Article

AI Summary

short article 1 min

Toby Walsh, an AI expert from the University of New South Wales, warned that some Australians are exhibiting signs of psychosis or mania in their interactions with AI chatbots. Speaking at the National Press Club on Wednesday, Walsh criticized Silicon Valley's "careless" approach to AI development, driven by profit motives. He expressed concern over the Australian government's lack of AI regulation. Walsh believes the rapid advancement of AI will bring both benefits and negative consequences, describing it as a period of "boom and doom." His warning highlights potential mental health risks associated with unregulated AI chatbot use.

Key Entities & Roles

Key Player Opposition Context
Artificial Intelligence ×230% Silicon Valley 40% National Press Club 50% University of New South Wales 60% Australian Government 70% Australia ×280% Toby Walsh ×290%

Keywords

ai chatbots 100% artificial intelligence 90% psychosis 80% mania 70% regulation 60% silicon valley 50% toby walsh 50% profit 40%

Sentiment Analysis

Negative
Score: -0.40

Source Transparency

Source
The Guardian - World News
Political Lean
Center-Left (-0.40)
Far LeftCenterFar Right
Classification Confidence
85%

This article was automatically classified using rule-based analysis. The political bias score ranges from -1 (far left) to +1 (far right).

Topic Connections

Explore how the topics in this article connect to other news stories

Network visualization showing 13 related topics
View Full Graph
ai chatbotsartificial intelligencepsychosismaniaregulationsilicon valleytoby walshprofit
Explore Full Topic Graph

Find Similar Articles

AI-Powered

Discover articles with similar content using semantic similarity analysis.