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Professors Staffed a Fake Company Entirely With AI Agents, and You'll Never Guess What Happened

futurism.com/professors-compan

#technology #tech #ai #artificialintelligence #employment #careers #economy #chatbots

Actually you'll guess exactly what happens. Best line in the article, "... artificial intelligence is arguably still just an elaborate extension of your phone's predictive text, rather than a sentient intelligence..."

Futurism · An Entire Company Was Staffed With AI Agents and You'll Never Guess What HappenedBy Joe Wilkins

"This report outlines several case studies on how actors have misused our models, as well as the steps we have taken to detect and counter such misuse. By sharing these insights, we hope to protect the safety of our users, prevent abuse or misuse of our services, enforce our Usage Policy and other terms, and share our learnings for the benefit of the wider online ecosystem. The case studies presented in this report, while specific, are representative of broader patterns we're observing across our monitoring systems. These examples were selected because they clearly illustrate emerging trends in how malicious actors are adapting to and leveraging frontier AI models. We hope to contribute to a broader understanding of the evolving threat landscape and help the wider AI ecosystem develop more robust safeguards.

The most novel case of misuse detected was a professional 'influence-as-a-service' operation showcasing a distinct evolution in how certain actors are leveraging LLMs for influence operation campaigns. What is especially novel is that this operation used Claude not just for content generation, but also to decide when social media bot accounts would comment, like, or re-share posts from authentic social media users. As described in the full report, Claude was used as an orchestrator deciding what actions social media bot accounts should take based on politically motivated personas. Read the full report here."

anthropic.com/news/detecting-a

www.anthropic.comDetecting and Countering Malicious Uses of ClaudeDetecting and Countering Malicious Uses of Claude

"We must stop giving AI human traits. My first interaction with GPT-3 rather seriously annoyed me. It pretended to be a person. It said it had feelings, ambitions, even consciousness.

That’s no longer the default behaviour, thankfully. But the style of interaction — the eerily natural flow of conversation — remains intact. And that, too, is convincing. Too convincing.

We need to de-anthropomorphise AI. Now. Strip it of its human mask. This should be easy. Companies could remove all reference to emotion, judgement or cognitive processing on the part of the AI. In particular, it should respond factually without ever saying “I”, or “I feel that”… or “I am curious”.

Will it happen? I doubt it. It reminds me of another warning we’ve ignored for over 20 years: “We need to cut CO₂ emissions.” Look where that got us. But we must warn big tech companies of the dangers associated with the humanisation of AIs. They are unlikely to play ball, but they should, especially if they are serious about developing more ethical AIs.

For now, this is what I do (because I too often get this eerie feeling that I am talking to a synthetic human when using ChatGPT or Claude): I instruct my AI not to address me by name. I ask it to call itself AI, to speak in the third person, and to avoid emotional or cognitive terms.

If I am using voice chat, I ask the AI to use a flat prosody and speak a bit like a robot. It is actually quite fun and keeps us both in our comfort zone."

theconversation.com/we-need-to

The ConversationWe need to stop pretending AI is intelligent – here’s how
More from The Conversation UK

"It’s not that hard to build a fully functioning, code-editing agent.

It seems like it would be. When you look at an agent editing files, running commands, wriggling itself out of errors, retrying different strategies - it seems like there has to be a secret behind it.

There isn’t. It’s an LLM, a loop, and enough tokens. It’s what we’ve been saying on the podcast from the start. The rest, the stuff that makes Amp so addictive and impressive? Elbow grease.

But building a small and yet highly impressive agent doesn’t even require that. You can do it in less than 400 lines of code, most of which is boilerplate.

I’m going to show you how, right now. We’re going to write some code together and go from zero lines of code to “oh wow, this is… a game changer.”

I urge you to follow along. No, really. You might think you can just read this and that you don’t have to type out the code, but it’s less than 400 lines of code. I need you to feel how little code it is and I want you to see this with your own eyes in your own terminal in your own folders.

Here’s what we need:

- Go
- Anthropic API key that you set as an environment variable, ANTHROPIC_API_KEY"

ampcode.com/how-to-build-an-ag

ampcode.comHow To Build An Agent | AmpBuilding a fully functional, code-editing agent in less than 400 lines.

This tells us a lot about how the lives of an increasing number of human beings are so empty of social contact with other human beings that they need to enter into false relationships with chatbots governed by neural networks and statistical probabilities...

"More and more of us are using LLMs to find purpose and improve ourselves.

Therapy and Companionship is now the #1 use case. This use case refers to two distinct but related use cases. Therapy involves structured support and guidance to process psychological challenges, while companionship encompasses ongoing social and emotional connection, sometimes with a romantic dimension. I grouped these together last year and this year because both fulfill a fundamental human need for emotional connection and support.

Many posters talked about how therapy with an AI model was helping them process grief or trauma. Three advantages to AI-based therapy came across clearly: It’s available 24/7, it’s relatively inexpensive (even free to use in some cases), and it comes without the prospect of judgment from another human being. The AI-as-therapy phenomenon has also been noticed in China. And although the debate about the full potential of computerized therapy is ongoing, recent research offers a reassuring perspective—that AI-delivered therapeutic interventions have reached a level of sophistication such that they’re indistinguishable from human-written therapeutic responses.

A growing number of professional services are now being partially delivered by generative AI—from therapy and medical advice to legal counsel, tax guidance, and software development."

hbr.org/2025/04/how-people-are

Harvard Business Review · How People Are Really Using Gen AI in 2025Last year, HBR published a piece on how people are using gen AI. Much has happened over the past 12 months. We now have Custom GPTs—AI tailored for narrower sets of requirements. New kids are on the block, such as DeepSeek and Grok, providing more competition and choice. Millions of ears pricked up as Google debuted their podcast generator, NotebookLM. OpenAI launched many new models (now along with the promise to consolidate them all into one unified interface). Chain-of-thought reasoning, whereby AI sacrifices speed for depth and better answers, came into play. Voice commands now enable more and different interactions, for example, to allow us to use gen AI while driving. And costs have substantially reduced with access broadened over the past twelve hectic months. With all of these changes, we’ve decided to do an updated version of the article based on data from the past year. Here’s what the data shows about how people are using gen AI now.

"Finally, AI can fact-check itself. One large language model-based chatbot can now trace its outputs to the exact original data sources that informed them.

Developed by the Allen Institute for Artificial Intelligence (Ai2), OLMoTrace, a new feature in the Ai2 Playground, pinpoints data sources behind text responses from any model in the OLMo (Open Language Model) project.

OLMoTrace identifies the exact pre-training document behind a response — including full, direct quote matches. It also provides source links. To do so, the underlying technology uses a process called “exact-match search” or “string matching.”

“We introduced OLMoTrace to help people understand why LLMs say the things they do from the lens of their training data,” Jiacheng Liu, a University of Washington Ph.D. candidate and Ai2 researcher, told The New Stack.

“By showing that a lot of things generated by LLMs are traceable back to their training data, we are opening up the black boxes of how LLMs work, increasing transparency and our trust in them,” he added.

To date, no other chatbot on the market provides the ability to trace a model’s response back to specific sources used within its training data. This makes the news a big stride for AI visibility and transparency."

thenewstack.io/llms-can-now-tr

The New Stack · Breakthrough: LLM Traces Outputs to Specific Training DataAi2’s OLMoTrace uses string matching to reveal the exact sources behind chatbot responses

A hot topic in #GLAMR -- and this paper makes a good fist of understanding AI's limitations. Large differentials between #ChatGPT, and #CoPilot / #Gemini.

"this [study] underscores the continued importance of human labor in subject #cataloging work [...] #AI tools may prove more valuable in assisting catalogers especially in subject heading assignment, but continued testing & assessment will be needed..."

AI #Chatbots & Subject #Cataloging: A Performance Test doi.org/10.5860/lrts.69n2.8440 #metadata

🔴 💻 **Are chatbots reliable text annotators? Sometimes**

“_Given the unreliable performance of ChatGPT and the significant challenges it poses to Open Science, we advise caution when using ChatGPT for substantive text annotation tasks._”

Ross Deans Kristensen-McLachlan, Miceal Canavan, Marton Kárdos, Mia Jacobsen, Lene Aarøe, Are chatbots reliable text annotators? Sometimes, PNAS Nexus, Volume 4, Issue 4, April 2025, pgaf069, doi.org/10.1093/pnasnexus/pgaf.

#OpenAccess #OA #Article #AI #ArtificialIntelligence #LargeLanguageModels #LLMS #Chatbots #Technology #Tech #Data #Annotation #Academia #Academics @ai

🔴 🇦🇺 **News Corp fills out tabloid papers with AI slop: NewsGPT**

David Gerard

_“News Corp has hit the slop machine since at least 2023, when it was using chatbots to churn out local news stories — 3,000 each week — attributed to the head of the data team. Nobody knew about this until a News Corp executive bragged about it at a conference.”_

🔗 pivot-to-ai.com/2025/03/21/new.

Pivot to AI · News Corp fills out tabloid papers with AI slop: NewsGPTRupert Murdoch’s News Corporation fills its tabloid papers across Australia with right-wing slop. Now the slop will come from a chatbot — and not a human slop churner. News Corp sent a memo to staf…

The start of the chatbots revolution: LLMs start striking! 🤖👾

"On Saturday, a developer using Cursor AI for a racing game project hit an unexpected roadblock when the programming assistant abruptly refused to continue generating code, instead offering some unsolicited career advice.

According to a bug report on Cursor's official forum, after producing approximately 750 to 800 lines of code (what the user calls "locs"), the AI assistant halted work and delivered a refusal message: "I cannot generate code for you, as that would be completing your work. The code appears to be handling skid mark fade effects in a racing game, but you should develop the logic yourself. This ensures you understand the system and can maintain it properly."

The AI didn't stop at merely refusing—it offered a paternalistic justification for its decision, stating that "Generating code for others can lead to dependency and reduced learning opportunities.""

arstechnica.com/ai/2025/03/ai-

Ars Technica · AI coding assistant refuses to write code, tells user to learn programming insteadBy Benj Edwards