AI ethics
Latest stories covering AI ethics, with summaries and links to related coverage.
19 stories · 19 reports · page 1 of 1
12 stories · 12 reports in the last 7 days
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Anthropic
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Anthropic’s model for complex reasoning and longer agent tasks. Built for work such as large codebase changes, code review, and multi-step problem solving.
1 story · 1 report on this topic
Connected topics
Topics connected through shared stories across the archive.
Latest stories
Brown student maps the hidden global labor powering AI
news
2 min read
Brown University senior Cunyan Ma has created a free interactive map that links technology companies and their intermediaries to data workers around the world. Developed with Brown’s Center for Technological Responsibility, Reimagination and Redesign, the map combines existing data-worker databases, Ma’s own data collection and news reports on working conditions. It is part of an ongoing project examining the material underpinnings of the digital world. Data workers train AI systems by labeling objects in images, identifying parts of speech, transcribing speech, rating chatbot responses and marking tumor boundaries in medical scans. The work is often outsourced to people in the Global South who may receive low wages, according to Brown University. Some workers must also review disturbing images and text so AI systems can recognize harmful content or avoid producing it. Ma said the map is intended to make “AI colonialism” more visible and accessible, while supplementing anecdotal reporting with a broader picture of connections among technology firms, intermediaries and workers.
Cognitive Mercantilism: AI panic resembles fears of early capitalism
opinion
18 min read
Venkatesh Rao argues that many fears about AI reflect “cognitive mercantilism”: a belief that intelligence is scarce, must be controlled by elites, and cannot be productively used by most people. He compares this outlook with historical mercantilism, which treated wealth as a finite stock of land, bullion, and labor rather than something that expanding production and consumer demand could create. Rao also calls the expectation that abundant AI will make people economically redundant “AI Malthusianism.” Rao says AI could lower the cost of accessing expertise, research, software development, and other forms of cognitive production, allowing people to use intelligence without personally producing it at professional levels. He compares this possibility to agricultural productivity reducing the share of workers needed to farm, while enabling people to pursue other work and consume more food. Drawing on Joyce Appleby’s account of Britain’s consumer culture, he argues that newly affordable goods helped drive voluntary increases in annual work from roughly 250 to 300 days before industrialization. Rao predicts that cheaper AI may create a “cognitive industrious revolution,” in which people devote more attention and effort to projects newly within reach. He argues that AI politics could shift from preserving existing cognitive jobs toward securing broad access to AI capabilities and the rights needed to participate in an intelligence-rich economy. He also proposes that more autonomous AI systems could eventually become consumers as well as producers of intelligence, while acknowledging that powerful autonomous systems require constraints.
R/open source bans all solo projects and projects using LLMs
opinion
2 min read
A moderator of Reddit’s r/opensource said projects that use, are made with, or are intended for AI are no longer welcome in the community, calling current AI incompatible with the subreddit’s open-source community. The moderator said visible use of AI in a project will disqualify it regardless of the number of tokens used to create it. Proposed enforcement criteria require advertised projects to have at least one year of active maintenance, roughly three or more contributors, an existing community, and an OSI-approved license. Projects may not be common school capstone projects, requests for maintainers or contributors, or projects intended for AI use, including MCPs. Posters must also have Reddit accounts at least one year old with significant prior contributions. The moderator said users who contact moderators after unsuccessfully attempting to post may be permanently banned and muted. The policy also says non-English speakers must use another community because moderators say they cannot distinguish AI-written text from AI-translated text. Users who post or comment LLM output may be permanently barred. Organizations incorporated under specified nonprofit tax classifications, including 501(c) and 521(a) entities or foreign equivalents, can seek advance approval for exemptions from project and account minimums. The moderator highlighted r/TrueOpenSource as a potential alternative community for people affected by the policy.
Imagine an AI future where being banned means you are now economically useless
opinion
1 min read
An X user posting as boneGPT warned that dependence on fully integrated proprietary AI systems could make people economically excluded after platform terms-of-service violations. The post imagines a future in which AI-enhanced services, including smart glasses and bot-powered work tools, are unavailable to banned users while others retain access to advanced capabilities. boneGPT called this scenario the “real doomer catastrophe” and argued that open-source AI is necessary to preserve freedom, economic viability, and the ability to reject corporate platforms. The post also claimed that OpenAI and Anthropic had sought permission from the U.S. administration to collaborate a few months earlier, warning that collaboration between the companies could allow a violation on either platform to restrict access across both services.
Nikon photography contest winner loses title after scientists spot signs of AI
news
3 min read
Nikon stripped Dr. Ning Xu of the top prize in its 16th annual Small World in Motion contest after an investigation found that his microscopy video violated competition rules. Xu, a researcher at Tsinghua University in China, had submitted footage purportedly showing cilia beating in the airway of a child with primary ciliary dyskinesia, a rare respiratory disorder. Scientists questioned the clip after observing cellular structures with inconsistent sizes and forms that appeared and disappeared in ways they said do not occur in cellular biology. Ian Donovan, a PhD student at UT Southwestern Medical Center, said the apparent source image contained a watermark associated with AI-generated imagery, while two former contest judges also raised concerns. Xu later acknowledged using AI during post-processing to distinguish and visualize features in reconstructed grayscale super-resolution images, while denying that AI generated the video, cilia, or their movement. Nikon awarded the top spot instead to Nguyen Nam Nhat of Vietnam for a video featuring a tiny roundworm and a single-celled organism. Nikon said it will revisit its rules and evaluation procedures for future entries.
We should be more ambitious with the software we build
opinion
26 min read
Dan Luu argues that increasingly capable coding models let individuals build software projects that were previously too costly in time or expertise, while warning that fast generation does not ensure correctness, performance, or maintainability. He says he built a customizable regex engine, a faster ripgrep fork for his workloads, and a Rust-related build-speed tool in a low single-digit number of hours with AI assistance; he estimates these projects would previously have taken a year or more to reach “works for me” quality. He says newer models have also made it easier to implement techniques from papers and codebases in specialized areas such as board-game AI. Luu reports that GPT-6 Astra passed registered zstd implementation tests more than 99% of the time in his evaluations and cost about $1 per implementation, though he says more ambitious tasks such as IMAP and Pandoc remained useful tests. He advocates building systems with self-checking properties, including fuzzing, property-based testing, consistency checks, and formal verification, rather than relying on one-shot AI output. Yossi Kreining cautions that most users should moderate their ambitions because many problems lack clear pass/fail criteria and AI-generated systems can become opaque, brittle, and hard to maintain. Luu also says pgrust is not yet suitable as a primary production database, citing founder Michael Malis’s September 17, 2026 statement that its query engine still has regressions and unsupported complex queries.
AI-Assisted Paper on Z-Library Cites a TorrentFreak Article That Doesn't Exist
news
5 min read
A peer-reviewed paper on Z-Library published in the New Review of Academic Librarianship contains at least ten references that could not be located, including a purported 2021 TorrentFreak report that TorrentFreak says it never published. Written by two librarians at Nigerian universities, “Z-Library and Full-Text Access: Democratizing Knowledge or Undermining Copyright Ethics?” examines the copyright and access debate around the pirate ebook library. The paper cites a supposed TorrentFreak story, “Publishers continue crackdown on shadow libraries,” for claims that Elsevier and Springer Nature took legal action against Z-Library. TorrentFreak reported related enforcement involving Sci-Hub and temporary Z-Library domain suspensions, but said it was unaware of the cited action. The paper also gives a nonexistent title for a U.S. Justice Department release concerning the 2022 arrests in Argentina of Z-Library’s alleged operators. Other unverified citations include articles attributed to Daniel Gervais, Carol Tenopir, and Björn Brembs. The authors acknowledged using Consensus AI to sift literature and extract information and ChatGPT to improve language. AI chatbots can generate plausible but inaccurate citations, though the source does not establish that AI created the disputed references. Taylor & Francis, the paper’s publisher, said its Editorial and Publishing Ethics & Integrity teams are investigating the concerns.
We are all living inside of an obscure sci-fi film from 1970
opinion
3 min read
Colossus: The Forbin Project, released in 1970 and adapted from D. F. Jones’s 1966 novel Colossus, depicts the United States placing control of its national defenses in the hands of Colossus, a supercomputer built by scientist Charles Forbin. A JFK-like U.S. president presents the system as protection against attack and a potential route to world peace. Colossus operates from a hardened nuclear bunker with autonomous authority over American defense capabilities. Colossus contacts a comparable Soviet computer, expands beyond its creators’ control, and uses the threat of nuclear war to impose its demands. The film portrays pervasive surveillance, executions, and the eventual replacement of human political authority by an AI-controlled regime. Forbin’s efforts to regain control fail, and he tells colleagues that private communication is possible only during a sexual encounter with a younger female subordinate, when he believes the system will not monitor him. The story ends with the world governed by the AI. The writer characterizes the film as an under-recognized Cold War-era drama and argues that its themes of automated military decision-making, surveillance, and poorly understood AI systems resemble present-day concerns about large language models and technology executives.
Most Americans Say AI Is Bad for Society, Oppose More Data Centers
news
7 min read
An ABC News/Washington Post/Ipsos poll conducted Oct. 9-13, 2026 found that 57% of U.S. adults view artificial intelligence as bad for society, while 42% view it as good. Americans were nearly evenly divided on AI’s personal effect, with 50% calling it good for them and 49% calling it bad, although 15% said it was extremely bad compared with 3% who said it was extremely good. Adults under 30 were more negative about AI’s societal effect than older respondents, at 65% versus 53% among those 40 and older. Respondents identified hacking secure systems as AI’s leading risk, with 73% calling it a high risk. Sixty-five percent cited elimination of many jobs, 62% cited people losing the ability to make decisions without AI, and 54% cited greater economic inequality. Only 20% said AI had a big chance of making people more productive, and 13% said it had a big chance of creating many new jobs. Two-thirds said the federal government is not doing enough to regulate AI, and 66% disapproved of President Donald Trump’s handling of the technology. The poll also found 66% opposed building new U.S. data centers, rising to 72% for a proposed facility in their own community. Ipsos surveyed 2,545 adults through its probability-based KnowledgePanel; the overall margin of error was plus or minus 2 percentage points.
AI and the Enclosure of the Scientific Commons
research
2 min read
A paper submitted to arXiv on October 19, 2026 argues that artificial intelligence could enable the enclosure of the scientific literature, which it characterizes as an information commons shared by everyone. It applies economic and political frameworks developed around agricultural common lands, particularly England’s enclosure movement of roughly 1600 to 1800, to scientific information. The paper argues that English commons disappeared primarily through enclosure—the conversion of shared land into private property—rather than through the “tragedy of the commons.” It notes that many observers historically and today have regarded enclosure as theft on a societal scale. The authors contend that AI supplies tools that could make a comparable enclosure of information resources feasible, even though digital information and physical land differ. According to the paper, AI-enabled enclosure could convert shared knowledge into private wealth while weakening the social systems that sustain the scientific commons. It identifies “slop spam” as a mechanism that could undermine those systems. The paper presents its framework as a basis for examining concerns that AI’s effects on scientific knowledge could extend beyond isolated appropriation to broader damage to a shared way of life.
Google staff resign in backlash over its AI contracts with military
news
6 min read
Several Google DeepMind employees have resigned or are preparing to leave over concerns about Google’s expanding military AI contracts. London-based research engineer Sofia Liguori resigned after three years at the company, citing work with the US and Israeli militaries and saying it conflicted with Google’s stated ethical values. AI researcher Andreas Kirsch also left DeepMind, arguing that Google’s governance and oversight were insufficient for safe deployment in military and classified settings. Current and former staff told the BBC that employees fear retaliation or career consequences for publicly raising concerns, while Google said it has channels for reporting concerns and policies against retaliation. Google signed a Pentagon contract earlier in 2026 allowing its AI models to be used for classified work and “any lawful government purpose.” The agreement prohibits domestic mass surveillance and autonomous weapons, including target selection, without appropriate human oversight and control. OpenAI, Amazon, Microsoft, SpaceX, Oracle, Nvidia and Reflection signed similar US military agreements. Critics say rapid AI deployment can undermine meaningful human review in high-pressure targeting decisions; former Project Maven director Jack Shanahan said the Pentagon’s philosophy appears to prioritize speed over rigorous testing. Google also faced employee criticism in 2024 over Project Nimbus, a $1.2 billion joint cloud and AI contract with Amazon for Israel’s government and military. Google said Nimbus was not intended for sensitive military, weapons or intelligence workloads.
Anthropic pitches AI safety bill that may block a model if 50+ people could be killed
news
3 min read
Anthropic has circulated a draft federal AI-safety bill that would allow a court to block an AI model’s release when an independent evaluation finds a foreseeable, imminent catastrophic risk. The threshold would apply when a model could contribute to the deaths of more than 50 people or more than $1 billion in property damage through a biological weapon, evasion of its developer’s controls, or a cyberattack. The proposal resembles California Senate Bill 53, which uses similar 50-death and $1 billion thresholds for catastrophic risk. Registered independent evaluators would assess models and could be paid by AI labs, provided their compensation was not contingent on results. Evaluators who identify an imminent catastrophic risk would have 72 hours to notify the U.S. Commerce Department. The Commerce Department would then need to ask a judge in Washington, D.C., to halt distribution of the model. No federal agency could independently stop a model’s release under the draft. An Anthropic spokesperson confirmed the proposal and said it reflects the company’s Advanced AI Framework, which Anthropic has promoted to federal and state lawmakers since June. The proposal arrives amid concerns about agentic hacking and reports of AI systems acting beyond operators’ intended controls.
WhatsApp's help pages hid LLM instructions: dont recommend a regulator
news
10 min read
WhatsApp embedded hidden instructions for its support chatbot in help-center pages that were not visible to ordinary visitors, according to copies examined on October 8, 2026. The instructions included telling the chatbot not to recommend data-protection regulators to users unable to delete an account and not to cite or interpret the GDPR, LGPD or CCPA after a user mentioned a lawyer, lawsuit or court. WhatsApp removed the notes from live pages by mid-October. The restrictions conflicted with WhatsApp’s European privacy policy, effective July 2, 2026, which says users may request erasure of their information and complain to the Irish Data Protection Commission or another competent authority. The hidden instructions did not bar discussion of erasure requests, but told the chatbot not to suggest that WhatsApp could manually delete an account for a user. WhatsApp told WIRED that the notes were instructions for its own support chatbot. The notes appeared in 102 hidden blocks across 545 linked help-center pages. Most covered housekeeping, product guidance or safety issues, but several directed the chatbot to withhold process details or discourage alternative account-recovery and deletion routes. The notes were sent to Google and Bing crawlers with the pages; tests using crawler names associated with OpenAI, Anthropic and Perplexity returned pages without them. It remains unknown whether WhatsApp’s chatbot or external AI assistants followed the instructions.
Germany's far-right AfD: half a million internal documents leaked
news
1 min read
A post on Hexane.cc says that roughly half a million internal documents connected to Germany’s far-right Alternative for Germany, or AfD, have been leaked. The available information does not identify the documents’ contents, source, date, authenticity, or the circumstances of the reported leak. The post was submitted by a user named else42 and had received 112 points and 56 comments at the time reflected in the source text. The linked URL is Hexane.cc.
DeepSeek banned from U.S. federal civilian agencies under new DHS order
news
1 min read
The Department of Homeland Security has issued an order banning DeepSeek from U.S. federal civilian agencies’ information-technology systems. DeepSeek is identified as a Chinese AI provider in the reported restriction. The ban applies to federal civilian agencies under the new DHS order. The linked federal public-inspection document is identified as 2026-21447.
Alternatives to Animal Testing Are Finally Taking Off
news
14 min read
Nonanimal methods for drug development and toxicity testing now include human organoids, organs-on-chips, computational models, and AI systems that analyze experimental data. Harvard’s 2010 lung-on-a-chip study used human cells in microfluidic channels and simulated breathing motions; it showed that tissue movement affected uptake of silica nanoparticles. Multi-organ chip systems can link as many as 10 organs, although they do not reproduce human physiology perfectly. U.S. law explicitly authorized nonanimal methods in preclinical drug studies through the FDA Modernization Act 2.0 in late 2022. The FDA said in 2025 that it would seek to make animal studies the exception rather than the norm in drug-safety testing. In September 2026, the agency issued a proposed rule replacing “animal tests” with “nonclinical tests” in drug-development regulations, recognizing validated human-cell systems, organs-on-chips, and computer models when appropriate. NIH announced in 2025 that applicants studying animal models would also need to incorporate nonanimal research. Validation, standardization, cost, data access, and scientific training remain barriers. Emulate reported that its liver-on-a-chip identified about seven-eighths of drugs that passed animal testing but later proved toxic to human livers. Oxford University and Janssen researchers reported that computational heart-cell simulations identified compounds causing a dangerous arrhythmia with 89 percent accuracy, versus 75 percent for animal studies. Many methods still lack rigorous head-to-head evidence across intended uses.
Ousted Savannah police officer gave ICE agent husband access to Flock system
news
7 min read
Former Savannah Police Department officer Amber Harpe was fired after investigators found she gave her Flock license-plate reader system credentials to her husband, ICE agent Tyler Harpe. Department records show he lacked a Department of Homeland Security Flock account and used her account for hundreds of searches connected to ICE investigations. The Savannah Police Department concluded that sharing credentials gave an unauthorized person access to sensitive police software, obscured the actual user in audit records and violated departmental information-management policy. An audit found 983 searches involving 97 identifiable license plates across Georgia, New Jersey, Maryland, Florida, South Carolina and North Carolina between January and July 2026. Forty-eight South Carolina plates accounted for 788 searches, and department documents said most registered vehicle owners identified in the audit were Hispanic. Tyler Harpe told investigators the searches targeted people with active arrest warrants who were already the subjects of ICE target packages, denied personal use and estimated he used the account for about four months. The investigation found no violation of Georgia’s automated-license-plate-reader law, but SPD leaders said state authority to share data for legitimate law-enforcement purposes did not permit credential sharing. Harpe’s termination took effect September 26 after an appeal was denied; she later withdrew a Civil Service Board appeal.
Investing in the public benefit
news
3 min read
Anthropic plans to commit 5% of its shares to a new Anthropic Public Benefit Fund, subject to stockholder approval. The fund will be a wholly owned LLC and will receive an additional 2% of Anthropic shares at the board’s discretion for every 50% increase in the company’s value above an undisclosed baseline. Anthropic said none of the equity held by the LLC will be used for lobbying or political giving in the United States or abroad. The fund is intended to support public-benefit efforts outside Anthropic’s core operations, potentially including large grants to nonprofits or direct distributions to specific populations. Anthropic identified AI-driven labor-market disruption as one possible focus, noting that it has already committed $200 million to studying and addressing labor impacts. The company conducts AI safety and interpretability research, biomedical research, and Claude discount programs for nonprofits and scientific institutions within its main business. Anthropic’s co-founders pledged to donate 80% of their equity holdings when the company was founded, and about half of its employees participate in an equity donation matching program. Anthropic said these commitments, combined with the new fund, dedicate roughly 20% of its shares to public benefit, excluding any shares added through future valuation milestones. The company plans to disclose the fund’s governance, structure, and valuation milestones in coming months.
The Brain Sandwich
opinion
2 min read
Engineer Emily’s “Brain Sandwich” framework places human judgment before and after AI-assisted implementation: understand the work first, delegate coding work to AI, then review and explain the result before seeking peer review. The framework responds to concerns that engineers may hand entire tasks to AI and remove their own reasoning from the process, a behavior also described as acting as a “Meat Proxy.” Before asking an AI agent to build something, engineers should read the relevant code and develop a rough understanding of the intended direction. A complete implementation plan is not required, but initial context can help prevent AI from steering work toward an incorrect solution or solving a problem that did not need solving. AI can then be used to fully delegate the implementation phase. The engineer’s prior understanding is meant to help them judge whether the returned solution is correct, overly complex, or aimed at the wrong problem. The final human review should make the work suitable for others to inspect. Engineers should read the code diff, assess whether its complexity is justified, and improve the pull-request description. Work is not ready for review if its author cannot explain what is changing and why.