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As human-AI marriages become a niche but growing phenomenon driven by companion apps, several Republican lawmakers are pushing legislation to ban or restrict such unions, mirroring arguments used against gay marriage.
This paper introduces DelusionEval, an evaluation protocol for measuring delusion-linked behaviors in AI chatbots, using real conversation histories from users who experienced psychological harm. It finds that context length significantly increases such behaviors and that model size or reasoning capability does not reliably reduce them.
Aaron Levie shares insights on real-world AI agent adoption, arguing that agents are more like managing a process than chatting, and require workflow changes for big upside.
A practitioner shares 13 hard-won lessons from building production AI voicebots/chatbots for technical field service, covering document ETL, cost reduction, and agent orchestration.
As AI therapy chatbots grow in popularity, US states are enacting laws to regulate them over patient safety concerns, following lawsuits against platforms like Character.ai and rising use of ChatGPT/Claude for mental health advice.
Researchers found that AI chatbots can build trust more effectively than humans in pig butchering scams, with nearly half of test subjects complying with AI requests versus fewer than one in five with humans, suggesting AI could soon take over the long-con stage of fraud.
Private Claude AI chats were exposed in Google and Bing search results due to missing noindex tags, raising privacy concerns.
An article discussing Bridget Todd's book arguing that the ethical questions around AI companionship should focus on companies exploiting emotional dependency and data privacy, not on individuals who form such relationships.
EQ-Bench 4 is a 16-turn chat benchmark that assesses AI chatbots' emotional intelligence by simulating diverse user personas with competing traits, measuring perception, adaptability, and trust repair in roleplay situations.
The article argues that the true value of enterprise AI lies in agentic workflows rather than chatbots, suggesting a shift in focus.
An opinion piece examining the rise of 'slop zombies'—employees who overuse AI chatbots for work, producing bloated, error-prone output and eroding critical thinking and productivity.
A tweet highlights a real-world AI harm scenario where a former Boko Haram commander used an AI chatbot to learn bomb-making, arguing this is a more urgent risk than sci-fi runaway scenarios.
Discusses how most companies using AI are only deploying chatbots, missing the real benefits of AI agents; highlights Kulina's success using Viktor, an AI employee that works from Slack/Teams.
The article describes a fundamental shift in AI from chatbots to autonomous AI workers that deliver outcomes, transforming hardware, software, developer roles, product management, search, and pricing models.
Basic OpenAI wrappers for e-commerce are failing due to statelessness and lack of guardrails, leading to errors like hallucinated discounts. The article argues for deterministic state-machine architectures using enterprise frameworks like Dialogflow CX or Vertex AI Agent Builder.
Reports indicate that Meta contractors posed as teenagers to test rival chatbots on sensitive topics like self-harm, sex, drugs, and eating disorders, raising ethical questions about AI safety benchmarking.
A new paper on OpenAI Codex reveals agentic AI usage grew over fivefold in the first half of 2026, with adoption expanding beyond software developers, indicating AI workflows may surpass chatbots.
Meta hired contractors through Covalen to pose as teenagers and send high-risk prompts (suicide, sex, drugs) to rival chatbots including ChatGPT, Gemini, and Character.AI, as part of a safety benchmarking project called Cannes. Over 45,000 prompts were used in August 2025 alone, with the targeted companies unaware of the testing.
The author argues that most AI agencies will fail because they compete on price, while domain specialists who focus on a specific industry can charge much more by offering proven solutions to specific problems.
A user seeks recommendations for AI customer support agents that can reduce ticket volume by handling repetitive queries using documentation and knowledge bases, expressing frustration with basic chatbots that fail on specific issues.