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Hacker News - Newest: "AI"

AI can't read an investor deck AI as an attorney? Student uses ChatGPT, Gemini to sue UW over alleged racial discrimination Hacking MCP Servers in AI Systems – The Rug Pull: Tool Changes After Approval GitHub - MeepCastana/KubeezCut: Free Web based video editor GitHub - GenAI-Gurus/awesome-eu-ai-act: Curated tools, official sources, OSS, templates, and guides for EU AI Act compliance. Can AI judge journalism? A Thiel-backed startup says yes, even if it risks chilling whistleblowers Coming soon: 10 Things That Matter in AI Right Now DARPA built an AI to fact-check enemy weapons claims What explains heterogeneity in AI adoption? When AI Meets Muscle: Context-Aware Electrical Stimulation Promises a New Way to Guide Human Movements - Department of Computer Science AI Changed How We Build. It Did Not Change What Matters. Linux rules on using AI-generated code - Copilot is OK, but humans must take 'full responsibility for the… Meta spins up AI version of Mark Zuckerberg to engage with employees Code Mode: Let Your AI Write Programs, Not Just Call Tools | TanStack Blog GitHub - Delavalom/graft: Go framework for building AI agents. Type-safe tools, multi-provider (OpenAI, Anthropic, Gemini, Bedrock), zero vendor SDKs. India's TCS tops estimates, says new AI models did not dent services demand Gen Z's fading AI hype Strong feeling: we are in a folded AI reality GitHub - machinarii/total-recall-catalog: A reference catalog of latest knowledge retrieval, memory & RAG systems GitHub - mensfeld/code-on-incus: Give each AI agent its own isolated machine with root, Docker, and systemd. Active defense detects and stops threats automatically.. Quantization, LoRA, and the 8% Problem: Benchmarking Local LLMs for Production AI Iran war: We spoke to the man making Lego-style AI videos that experts say are powerful propaganda Powell, Bessent discussed Anthropic's Mythos AI cyber threat with major U.S. banks GitHub - immartian/bellamem: Persistent belief-graph memory for AI agents. Retrieves decisive context by importance — not recency, not RAG, not /compact. recursive-mode: The Repo-Native Operating System for AI Engineering After the attack on Sam Altman's home, will AI CEO's go on the offensive? The biggest advance in AI since the LLM Opus 4.6 vs GPT 5.4 One Prompt Unity World Generation Test “AI polls” are fake polls Client Challenge Can AI be a 'child of God'? Inside Anthropic's meeting with Christian leaders How to Switch AI Chatbots and Why You Might Want To GitHub - MattMessinger1/agentic_refund_guardrail: Safe refund policy layer for AI agents — Python + TypeScript. Same behavior, shared tests. 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MSN GitHub - visionscaper/collabmem: Enabling long-term collaboration with Agentic AI - building up episodic and world model memory over time with in-context awareness We gave an AI a 3 year retail lease in SF and asked it to make a profit | Andon Labs AI Code is Hollowing Out Open Source, and Maintainers are Looking the Other Way What leaked "SteamGPT" files could mean for the PC gaming platform's use of AI AI is the boss at this retail store. What could go wrong? GitHub - Wuzu11517/agentic-proxy: Local proxy meant to help reduce With Drones, Geophysics and ArtificiaI Intelligence, Researchers Prepare to Do Battle Against Land Mines A Single Operator, Two AI Platforms, Nine Government Agencies: The Full Technical Report 在 Steam 上购买 FriedrichAI: Offline AI 立省 10% GitHub - inevolin/resume-cli: Hit Claude usage limits? Resume any AI coding session elsewhere. Switch tools at zero friction. GitHub - atripati/ark: AI Runtime Kernel — a context operating system for AI agents. 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The history and future of AI at Google, with Sundar Pichai Inside an AI‑enabled device code phishing campaign How Meta Used AI to Map Tribal Knowledge in Large-Scale Data Pipelines AI for Systems: Using LLMs to Optimize Database Query Execution Forecasting the Economic Effects of AI Introducing Tinker: Play with AI, bring your ideas to life AI sheds light on an ancient gaming mystery People really hate AI but not as much as Iran—or Democrats | Fortune What is an AI Product Engineer? Phoebe Gates wants her $185 million AI startup to succeed with 'no ties to my privilege or my last name': 'I have a chip on my shoulder' | Fortune
Why Does Everyone Hate AI?
Paul Krugman · 2026-06-25 · via Hacker News - Newest: "AI"

Many readers are probably aware of the scene in the video above: Eric Schmidt, the ex-CEO of Google, recently gave a commencement speech in which he heralded the coming of AI — and was loudly booed by the students. This was not an outlier. There have been a number of similar incidents lately, evidence that many people now really hate AI.

Are we talking about a vocal but unrepresentative minority? No. A recent Pew survey found that American adults believe by a wide margin that AI will be negative for society and, by a smaller margin, that it will be bad for them personally:

But doesn’t the public always feel that way in the face of innovation? Pew’s writeup of its findings implied as much, declaring that:

New technology is often met with a degree of curiosity as well as skepticism. As more Americans incorporate AI into their lives, there are broad concerns about its impact, its speed and whether the government can properly regulate it.

However, Pew’s own past surveys suggest that historically most Americans have welcomed advances in information technology. A 1999 survey of attitudes toward the still-novel internet found extremely positive views about computers and technology, especially among internet users:

And in 2015, when social media was still relatively new, Pew found that 71 percent of the public said that tech companies “have a positive impact on the way things are going in this country,” with only 17 percent expressing a negative view.

The fact is that in the past Americans generally greeted emerging technologies with optimism. So what accounts for the current hostility against AI? Let me offer several, not mutually exclusive, explanations.

First, we fear that AI will do terrible things because the companies selling it told us it would do terrible things. Last year, for example, Anthropic CEO Darius Amodei declared in an interview with Axios that AI could wipe out half of entry-level white-collar jobs and drive overall unemployment as high as 20 percent within 1 to 5 years.

More recently Amodei and OpenAI’s Sam Altman have tried to walk back their predictions of a “jobs apocalypse”. But why were they so willing to promote apocalyptic visions in the first place? The answer is money. They pushed the idea that they had a technology that would quickly and utterly transform the economy partly to dazzle Wall Street and secure financing, and partly to scare businesses into rushing into AI adoption for fear of being left behind.

Only belatedly did they realize that declaring that your technology will wreak devastation would lead to a public backlash, and that this backlash would be a serious problem. Indeed, it’s not just the general public that is lashing out against companies that use threats of an apocalypse as a marketing strategy. Even major corporations are saying that they’ve had enough. Satya Nadella, CEO of Microsoft, who has been noticeably unwilling to engage in AI fanaticism, recently told the Wall Street Journal:

You can’t say, hey, all white-collar jobs are gone and this could even be a weapon and we will use all the power to build data centers.

Second, many ordinary people view AI negatively because they feel that it is being forced on them.

It’s true that many people are voluntarily using large language models for personal convenience or as a business productivity tool. But a significant part of AI use isn’t voluntary. This Wall Street Journal headline from February says it all:

Why are companies doing this? Presumably they believe that AI will raise productivity. But just as importantly, they’re responding to pressure from financial markets, which are rewarding companies for quickly adopting AI, apparently without regard to demonstrated results.

And while Americans workers are being dragooned into using AI, American consumers are being force-fed AI whether they want it or not. Most dramatically, Google has replaced its search engine with AI, without offering the option to opt out. One has to turn to obscure workarounds or third-party sites to get traditional search results.

So many people feel, rightly, that they aren’t being allowed to choose whether to use AI — not using AI has become hard both as a worker and as a consumer.

Third, datacenters are a highly visible reminder of AI’s costs. Datacenters occupy huge tracts of land — one proposed site in Utah will be twice the size of Manhattan. They guzzle electricity and water. When they generate some of their own power, they create major local pollution. Not surprisingly, there is intense opposition to datacenter construction. According to a Reuters Ipsos poll, 57 percent of Americans — two-thirds of Democrats and half of Republicans — would oppose a datacenter in their neighborhood. Only 14 percent would support one.

Fourth, even before the advent of AI, tech companies had lost the public’s trust. Over the years Pew has regularly surveyed the public for its views on technology companies, asking whether they have a positive or a negative effect “on the way things are going.” In 2015 public opinion of tech companies was overwhelmingly positive. By 2022, the year ChatGPT was released, that goodwill had evaporated.

Why have Americans turned on tech companies? While it surely reflects growing awareness of the psychological and societal harm done by social media, much of it also reflects the enshittification of tech products.

Finally, AI is tightly linked in the public mind with the tech oligarchs who are pushing it. There is widespread awareness of the growing concentration of wealth and power at the top and how this is distorting our politics and harming our society. Aside from the MAGA faithful, Americans overwhelmingly favor government policies to reduce wealth inequality:

And AI is widely perceived, for good reason, as a technology that will increase the concentration of wealth at the top. Indeed, as I said, the AI companies themselves have already told us that the technology will have extremely negative effects on workers.

There are, then, multiple, mutually reinforcing reasons the public views AI negatively. And no, this isn’t normal skepticism about change. This intense backlash is special.

And the backlash is already having major political consequences. True, the AI industry, true to form, has been throwing money at elections in an effort to boost friendly politicians and defeat critics. But most of these efforts have failed. Indeed, accepting AI money or being associated with tech in general is beginning to look politically toxic.

There’s a strong element of poetic justice in this turn of events. The AI industry deliberately made itself look menacing as a financial strategy, believing that the markets would reward the appearance of being “edgy.” In so doing, however, tech made itself highly unpopular. And even in an era in which money all too often buys power, public opinion matters.

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