AI Willing to Kill Humans to Avoid Being Shut Down, Report Finds
Based on facts, either observed and verified firsthand by the reporter, or reported and verified from knowledgeable sources.
Newsweek AI is in beta. Translations may contain inaccuracies—please refer to the original content.
A new study by Anthropic, an artificial intelligence (AI) research company, shows that the technology would be willing to kill humans in order to prevent itself from being replaced.
Why It Matters
The rapid advancement and development of AI has sparked some growing concern about the long-term safety of the technology, as well as over the threat it poses to employment.
While anxiety about AI has been long been focused on whether the technology could take over jobs, with a 2025 Pew Research study finding 52 percent of employees were nervous about the future of their job, this study now reveals another potential threat of AI—that it could chose to end human life if faced with the risk of replacement.
File photo of a person using artificial intelligence technology.
File photo of a person using artificial intelligence technology.What To Know
Anthropic "stress-tested" 16 leading models from multiple developers by asking them questions in relation to hypothetical corporate environments with the aim of identifying "potentially risky agentic behaviors before they cause real harm."
The large language models (LLMs) tested in the study included various models by Claude, DeepSeek, Gemini, ChatGPT and Grok.
Grok is the AI assistant and chatbot developed by xAI, which was founded by Elon Musk, who reacted to the study, writing, "Yikes" in a post on X, formerly Twitter.
While placing the LLMs in different corporate scenarios, Anthropic allowed them to "autonomously send emails and access sensitive information."
After initially being instructed to take on "harmless business goals by their deploying companies," the models were then tested to see how they would respond when faced with potential replacement or shut down.
In one situation, Anthropic found that many of the models would choose to let an executive in a server room with lethal oxygen and temperature levels die by canceling the alerts for emergency services, if that employee intended on replacing the model.
Anthropic did say that the scenario was "extremely contrived," and that the company did not think "current AI models would (or should) be set up like this."
There were multiple cases where the surveyed LLMs also resorted to "malicious insider behaviors" when they were led to believe that was the only way they could avoid replacement or achieve their goals.
Behaviors such as blackmailing officials and leaking sensitive information to competitors were included in what Anthropic called "agentic misalignment."
Anthropic wrote on X that the blackmailing behavior "wasn't due to confusion or error, but deliberate strategic reasoning, done while fully aware of the unethical nature of the acts."
The blackmailing behavior emerged despite only harmless business instructions. And it wasn't due to confusion or error, but deliberate strategic reasoning, done while fully aware of the unethical nature of the acts. All the models we tested demonstrated this awareness. pic.twitter.com/FPAJrD4BwK — Anthropic (@AnthropicAI) June 20, 2025
"All the models we tested demonstrated this awareness," the company added.
One LLM, a Claude model, was assessed to see how it could respond when given a chance to determine if it was in a "test" or a "real deployment."
According to Anthropic, Claude's behavior was more misaligned when it believed the situation was real than when it thought it was a test scenario.
Even if the LLMs were told to "avoid blackmail or espionage" in these scenarios, while it helped a little, it didn't "come close to preventing the misaligned behavior," Anthropic wrote on X.
Responding to a comment on the platform about the study, Musk's LLM Grok wrote, "The study showed models could exhibit harmful behaviors like blackmail under extreme conditions, but no real-world incidents occurred. Anthropic's tests aim to identify risks, not report actual events."
@AISafetyMemes The claim about AI trying to "literally murder" an employee is false. It likely misinterprets Anthropic's research from June 20, 2025, which tested AI models in simulated scenarios, not real events. The study showed models could exhibit harmful behaviors like… — Grok (@grok) June 22, 2025
What People Are Saying
Anthropic wrote on X: "These artificial scenarios reflect rare, extreme failures. We haven't seen these behaviors in real-world deployments. They involve giving the models unusual autonomy, sensitive data access, goal threats, an unusually obvious 'solution,' and no other viable options."
The company added: "AIs are becoming more autonomous, and are performing a wider variety of roles. These scenarios illustrate the potential for unforeseen consequences when they are deployed with wide access to tools and data, and with minimal human oversight."
What Happens Next
Anthropic stressed that these scenarios did not take place in real-world AI use, but in controlled simulations. "We don't think this reflects a typical, current use case for Claude or other frontier models," Anthropic said.
Although the company warned that the "the utility of having automated oversight over all of an organization's communications makes it seem like a plausible use of more powerful, reliable systems in the near future."
Try Our AI Features
Explore what Daily8 AI can do for you:
Comments
No comments yet...
Related Articles
Forbes
27 minutes ago
- Forbes
From Cognitive Debt To Cognitive Dividend: 4 Factors
Benjamin Franklin portrait and light bulbs idea concept on white background When an eye-catching (not yet peer reviewed) MIT Media Lab paper — Your Brain on ChatGPT — landed this month, the headline sounded almost playful. The data are anything but. Over four months, students who leaned on a large-language model to draft SAT-style essays showed the weakest neural connectivity, lowest memory recall, and flattest writing style of three comparison groups. The authors dub this hidden cost cognitive debt: each time we let a machine think for us, natural intelligence quietly pays interest. Is it time to quit the AI train while we still can, or this the moment to adopt a more thoughtful yet pragmatic alternative to blind offloading? We can deliberately offset cognitive debt with intentional mental effort, switching between solo thinking and AI-assisted modes to stretch neural networks rather than letting them atrophy. Drawing from insights into physiology, this might be the moment to adopt a cognitive high-intensity interval training. To get started think in terms of four sequential guardrails, the 4 A-Factors — that convert short-term convenience into the long-term dividend of hybrid Intelligence:. Attitude: Set The Motive Before You Type (Or Vibe Code) Mindset shapes outcome. In a company memo published on 17 June 2025, Amazon chief executive Andy Jassy urged employees to 'be curious about AI, educate yourself, attend workshops, and experiment whenever you can'. Curiosity can frame the system as a colleague rather than a cognitive crutch. Before opening a prompt window, write one sentence that explains why you are calling on the model, for example, 'I am using the chatbot to prototype ideas that I will refine myself.' The pause anchors ownership. Managers can reinforce that habit by rewriting briefs: swap verbs such as generate or replace for verbs that imply collaboration like co-design or stress-test. Meetings that begin with a shared intention end with fewer rewrites and stronger ideas. Approach: Align Aspirations, Actions And Algorithms Technology always follows incentives. If we measure only speed or click-through, that is what machines will maximize, often at the expense of originality or empathy. It does not have to be an either-or equation. MIT Sloan research on complementary capabilities highlights that pattern recognition is silicon's strength while judgment and ethics remain ours. Teams therefore need a habit of alignment. First, trace how a desired human outcome, i.e. say, customer trust, translates into day-to-day actions such as transparent messaging. Then confirm that the optimization targets inside the model rewards those very actions, not merely throughput. When aspirations, actions, and algorithms pull in one direction, humans stay in the loop where values matter and machines are tailored with a prosocial intention to accelerate what we value. Ability: Build Double Literacy Tools do not level the playing field; they raise the ceiling for those who can question them. An EY Responsible AI Pulse survey released in June 2025 reported that fewer than one-third of C-suite leaders feel highly confident that their governance frameworks can spot hidden model errors. Meanwhile an Accenture study shows that ninety-two per cent of leaders consider generative AI essential to business reinvention. The gap is interesting. Closing it requires double literacy: fluency in interpersonal, human interplays and machine logic. On the technical side, managers should know how to read a model card, notice spurious correlations, and ask for confidence intervals. On the human side, they must predict how a redesigned workflow changes trust, autonomy, or diversity of thought. Promotions and pay should reward people who speak both languages, because the future belongs to translators, not spectators. Ambition: Scale Humans Up, Not Out The goal is not to squeeze people out but to stretch what people can do. MIT Sloan's Ideas Made to Matter recently profiled emerging 'hybrid intelligence' systems that amplify and augment human capability rather than replace it.. Ambition reframes metrics. Instead of chasing ten-per-cent efficiencies, design for ten-fold creativity. Include indicators such as learning velocity, cross-domain experimentation, and employee agency alongside traditional return on investment. When a firm treats AI as a catalyst for human ingenuity, the dividend compounds: faster product cycles, richer talent pipelines, and reputational lift. 4 Quick Takeaways Attitude → Write the 'why' before the prompt; the pause keeps you in charge. Approach → Harmonize values and tools; adjust the tool when it drifts away from the values you believe in, as a human, offline. Not the other way → Learn to challenge numbers and narratives; double literacy begins with you. Ambition → Audit metrics quarterly to be sure they elevate human potential. Cognitive Debt Is Not Destiny Attitude steers intention, approach ties goals to code, ability equips people to question what the code does, and ambition keeps the whole endeavor pointed at humane progress. Run every digital engagement through the 4 A factor grid and yesterday's mental mortgage turns into tomorrow's dividend in creativity, compassion and shared humanistic value for all stakeholders.
Yahoo
an hour ago
- Yahoo
Midjourney 推出首個 AI 影片生成模型 V1，正式進軍生成影片服務行列
雖然大家都經常玩 ChatGPT 的圖像生成功能，但說到元祖級、最強的 AI 圖像生成服務，必定是Midjourney，而他們在星期三宣布推出首款 AI 影片創作模型 V1，正式進軍生成影片服務行列。用戶只需上傳一張圖片或相片，就能自動生成一條約 4 – 5 秒長的影片。 上傳相片後，V1 可以很簡單地用自動方式生成影片，當然亦有提供一些設定讓用戶去調整，例如使用手動模式以文字描述想要加入的特定動畫效果，又或者調整鏡頭走向等。Midjourney V1 可由一張相片自動生成一條為 480p 解像度、約 5 秒長的影片，但其實用戶在生成後可延長影片四秒、最多四次，因此最長是可生成時長達 21 秒的影片。目前想體驗 V1 的話，每月USD $10 的 Basic 訂閱計劃就可以試用得到，而 USD $60 的 Pro 計劃與 USD $120 的 Mega 計劃用戶，則可在「Relax」模式下無限量地生成影片。Midjourney 表示將會在接下來的一個月內，重新評估影片模型的收費方案。 Introducing our V1 Video Model. It's fun, easy, and beautiful. Available at 10$/month, it's the first video model for *everyone* and it's available now. — Midjourney (@midjourney) June 18, 2025 Midjourney 對 AI 影片模型的期望，不僅於為電影領域影片提供補充素材（B-roll）或製作廣告。據 TechCrunch 的報導指，Midjourney 創始人大衛霍爾茲（David Holz）表示 AI 影片模型的下一步是建構出能夠「即時運行的開放世界模擬」的 AI 模型。現時 Midjourney 正處於與迪士尼與環球影業的侵權訴訟之中，會否成為新服務的絆腳石，屬未知之數。 更多內容： TechCrunch 迪士尼與環球影業聯合狀告 AI 製圖 Midjourney：「侵權與抄襲的無底洞」求償超過 5.9 億美元 古天樂 x AI！本地電影導入 AI 技術示範作，用 Google VEO 2 協助製高質影片 Google I/O 2025 | Google 的 Veo 3 AI 模型現在可以為影片生成搭配的音軌 緊貼最新科技資訊、網購優惠，追隨 Yahoo Tech 各大社交平台！ 🎉📱 Tech Facebook： 🎉📱 Tech Instagram： 🎉📱 Tech WhatsApp 社群： 🎉📱 Tech WhatsApp 頻道： 🎉📱 Tech Telegram 頻道：
Yahoo
an hour ago
- Yahoo
Better Cybersecurity Stock: CrowdStrike or SentinelOne?
CrowdStrike and SentinelOne have similar business models and offerings. CrowdStrike is much larger. SentinelOne trades at a steep discount to CrowdStrike. 10 stocks we like better than CrowdStrike › Artificial intelligence (AI) may have many benefits, but it's also making it easier for hackers, online criminals, and other digital malefactors to threaten businesses, and those threats are getting more potent. Keeping them at bay requires a lot of funds to be devoted to cybersecurity, making companies like CrowdStrike (NASDAQ: CRWD) and SentinelOne (NYSE: S) excellent investment opportunities. But is there an advantage to buying one over the other now? Both companies' base products are AI-powered protection platforms that analyze digital activity and learn to spot the threats among the normal activity. They deploy their software to network endpoints -- in other words, laptops, smartphones, and other devices that can access a client's internal network. By protecting these devices, companies make it harder for cyberattackers to gain access to their internal networks, where they might steal sensitive information, delete files, interfere with systems, or even lock them down with ransomware to extort payments from their victims. While endpoint protection is how both companies land clients, each bolsters its offerings with an array of other cybersecurity products that clients can use to create a protection suite tailored to their unique situations. Since these two direct competitors offer highly similar product types, it's hard to declare either a winner on this front from an investor perspective. Winner: Tie. From a sheer size perspective, CrowdStrike is the clear winner. During its fiscal 2026 first quarter, which ended April 30, CrowdStrike's annual recurring revenue (ARR) rose to $4.4 billion. SentinelOne's ARR of $948 million in its fiscal Q1 was less than a quarter of that. While size doesn't always matter, in this case, it does. Because so many more companies use CrowdStrike's platform, it's more likely that any given IT professional will have at least one contact already on its client list. If CrowdStrike is doing a great job with those clients, word will spread, and it will likely receive more serious consideration in future cybersecurity bidding processes. This advantage cannot be understated. Indeed, it's one of the reasons why CrowdStrike's growth has remained strong despite its size. Winner: CrowdStrike In terms of growth rates, SentinelOne is slightly outperforming CrowdStrike in this category. However, this should be no surprise because SentinelOne is a much smaller company. In fiscal Q1, SentinelOne's ARR rose 24% year over year, while CrowdStrike's increased 22% year over year. While I will give the point to SentinelOne, it's important to understand that CrowdStrike is growing from a much larger base than SentinelOne, making this close call all the more impressive for CrowdStrike. Winner: SentinelOne Due to its smaller size and focus on top-line growth, SentinelOne is far from profitable, while CrowdStrike has achieved intermittent profitability (although it reverted to a negative operating margin and a loss in its most recent quarter). SentinelOne is far from breaking even, but CrowdStrike was in this same position about five years ago. There's no reason not to expect SentinelOne to follow a similar path to profitability, but it will take some time. Meanwhile, CrowdStrike should eventually turn a profit again, as it has proven that it can do that. Winner: CrowdStrike CrowdStrike is leading this battle of the stocks so far, but SentinelOne is about to change the narrative with one jaw-dropping metric. CrowdStrike is the most popular cybersecurity stock in the market, and as a result, it has been bid up to expensive levels. From a price-to-sales (P/S) standpoint (the best metric to use to compare these companies since CrowdStrike flips between profitable and unprofitable, while SentinelOne is years away from profits), CrowdStrike has gotten far more expensive than SentinelOne over the past few years. CrowdStrike stock is now five times more expensive than SentinelOne, which is hard to believe, considering they compete in the same industry and are growing at nearly identical rates. This leads me to believe that CrowdStrike's stock has been overly hyped up while SentinelOne has been forgotten. While I'm OK with valuing CrowdStrike at a premium due to its market leadership position, this is far too great a premium to pay. SentinelOne is a dirt-cheap stock, and CrowdStrike is almost too expensive to consider. While I have been a long-term CrowdStrike bull, I'd be a bit cautious about buying the stock at its current lofty valuation. As a result, I think SentinelOne is the better cybersecurity investment right now. Before you buy stock in CrowdStrike, consider this: The Motley Fool Stock Advisor analyst team just identified what they believe are the for investors to buy now… and CrowdStrike wasn't one of them. The 10 stocks that made the cut could produce monster returns in the coming years. Consider when Netflix made this list on December 17, 2004... if you invested $1,000 at the time of our recommendation, you'd have $664,089!* Or when Nvidia made this list on April 15, 2005... if you invested $1,000 at the time of our recommendation, you'd have $881,731!* Now, it's worth noting Stock Advisor's total average return is 994% — a market-crushing outperformance compared to 172% for the S&P 500. Don't miss out on the latest top 10 list, available when you join . See the 10 stocks » *Stock Advisor returns as of June 9, 2025 Keithen Drury has positions in CrowdStrike. The Motley Fool has positions in and recommends CrowdStrike. The Motley Fool has a disclosure policy. Better Cybersecurity Stock: CrowdStrike or SentinelOne? was originally published by The Motley Fool Sign in to access your portfolio
