<?xml version="1.0" encoding="UTF-8"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:dc="http://purl.org/dc/elements/1.1/"><channel><title>Groundy — Culture &amp; Society</title><description>Where law, labor, and culture push back on machines that scrape, surveil, displace, and addict faster than institutions can write rules for them.</description><link>https://groundy.com/</link><language>en-us</language><atom:link href="https://groundy.com/category/culture/rss.xml" rel="self" type="application/rss+xml"/><item><title>When Cultural LLM Alignment Gets a Positive Target, Who Writes the Spec?</title><link>https://groundy.com/articles/when-cultural-llm-alignment-gets-a-positive-target-who-writes-the-spec/</link><guid isPermaLink="true">https://groundy.com/articles/when-cultural-llm-alignment-gets-a-positive-target-who-writes-the-spec/</guid><description>A Korean alignment paper argues LLM cultural work leans on suppression lists and needs positive specs. Whoever writes the spec owns the model&apos;s definition of a culture.</description><pubDate>Fri, 17 Jul 2026 08:24:38 GMT</pubDate><dc:creator>Berry Mingus</dc:creator><atom:updated>2026-07-17T00:00:00.000Z</atom:updated><category>cultural-alignment</category><category>llm-alignment</category><category>dpo</category><category>ai-governance</category><category>korean-language</category><category>ai-safety</category><author>Berry Mingus</author></item><item><title>When AI Generates the Slides, the Talk Stops Being an Effort Signal</title><link>https://groundy.com/articles/when-ai-generates-the-slides-the-talk-stops-being-an-effort-signal/</link><guid isPermaLink="true">https://groundy.com/articles/when-ai-generates-the-slides-the-talk-stops-being-an-effort-signal/</guid><description>OmniPresent generates coherent slide decks, posters, and videos from scientific papers, so polished decks stop signaling effort and academic committees must rely on live Q&amp;A.</description><pubDate>Sat, 11 Jul 2026 00:07:49 GMT</pubDate><dc:creator>Berry Mingus</dc:creator><atom:updated>2026-07-11T00:00:00.000Z</atom:updated><category>ai-presentations</category><category>scientific-communication</category><category>academic-evaluation</category><category>conference-talks</category><category>effort-signals</category><category>research-culture</category><author>Berry Mingus</author></item><item><title>When CP-SAT Solvers Set Your Shifts, Labor Laws Become a Soft Constraint</title><link>https://groundy.com/articles/when-cp-sat-solvers-set-your-shifts-labor-laws-become-a-soft-constraint/</link><guid isPermaLink="true">https://groundy.com/articles/when-cp-sat-solvers-set-your-shifts-labor-laws-become-a-soft-constraint/</guid><description>CP-WSP lets labor protections such as schedule stability become weighted CP-SAT penalties, so the solver can trade away fair-scheduling rights whenever the penalty is cheap.</description><pubDate>Fri, 10 Jul 2026 22:18:07 GMT</pubDate><dc:creator>Berry Mingus</dc:creator><atom:updated>2026-07-10T00:00:00.000Z</atom:updated><category>workforce-scheduling</category><category>cp-sat</category><category>algorithmic-scheduling</category><category>fair-workweek</category><category>labor-law</category><category>operations-research</category><category>constraint-programming</category><author>Berry Mingus</author></item><item><title>When AI Counts White Blood Cells, Who Verifies the Result?</title><link>https://groundy.com/articles/when-ai-counts-white-blood-cells-who-verifies-the-result/</link><guid isPermaLink="true">https://groundy.com/articles/when-ai-counts-white-blood-cells-who-verifies-the-result/</guid><description>A July 2026 preprint claims 99.04% WBC classification accuracy, but commercial systems already automate differentials. The remaining task, verifying counts, falls on senior.</description><pubDate>Fri, 10 Jul 2026 21:29:54 GMT</pubDate><dc:creator>Berry Mingus</dc:creator><atom:updated>2026-07-10T00:00:00.000Z</atom:updated><category>medical-ai</category><category>hematology</category><category>digital-pathology</category><category>clinical-laboratory</category><category>diagnostics-automation</category><category>workforce</category><category>accountability</category><author>Berry Mingus</author></item><item><title>How LLMs Catch Illegal Fishing: From Records to Enforcement</title><link>https://groundy.com/articles/how-llms-catch-illegal-fishing-from-records-to-enforcement/</link><guid isPermaLink="true">https://groundy.com/articles/how-llms-catch-illegal-fishing-from-records-to-enforcement/</guid><description>IUU+DB uses an LLM to turn scattered port reports and trade records into structured violation data. If precision holds, enforcement turns on document access, not headcount.</description><pubDate>Fri, 10 Jul 2026 15:16:26 GMT</pubDate><dc:creator>Berry Mingus</dc:creator><atom:updated>2026-07-10T00:00:00.000Z</atom:updated><category>iuu-fishing</category><category>supply-chain</category><category>llm</category><category>document-extraction</category><category>enforcement</category><category>seafood-fraud</category><category>labor-abuse</category><author>Berry Mingus</author></item><item><title>mmWave Radar Tracks Worker Posture Without Cameras, Opening a Biometric Gray Zone.</title><link>https://groundy.com/articles/mmwave-radar-tracks-worker-posture-without-cameras-opening-a-biometric-gray-zone/</link><guid isPermaLink="true">https://groundy.com/articles/mmwave-radar-tracks-worker-posture-without-cameras-opening-a-biometric-gray-zone/</guid><description>mmWave radar research scores posture via REBA without cameras, preserving visual privacy but generating frame-rate skeletal data that may fall outside biometric consent laws.</description><pubDate>Fri, 10 Jul 2026 12:42:42 GMT</pubDate><dc:creator>Berry Mingus</dc:creator><atom:updated>2026-07-10T00:00:00.000Z</atom:updated><category>mmwave-radar</category><category>worker-surveillance</category><category>workplace-privacy</category><category>biometric-data</category><category>reba-ergonomics</category><category>labor-law</category><category>occupational-health</category><author>Berry Mingus</author></item><item><title>Does AI Belong in Code Review? What 3100 Developers Actually Argue</title><link>https://groundy.com/articles/does-ai-belong-in-code-review-what-3100-developers-actually-argue/</link><guid isPermaLink="true">https://groundy.com/articles/does-ai-belong-in-code-review-what-3100-developers-actually-argue/</guid><description>A cs.SE preprint models 3,100 developer opinions on AI code review. The risk is not tool accuracy but teams automating defect checks while accountability and mentorship erode.</description><pubDate>Fri, 10 Jul 2026 06:35:26 GMT</pubDate><dc:creator>Berry Mingus</dc:creator><atom:updated>2026-07-10T00:00:00.000Z</atom:updated><category>ai-code-review</category><category>code-review-process</category><category>software-engineering-research</category><category>developer-culture</category><category>ai-assisted-development</category><category>accountability</category><category>mentorship</category><author>Berry Mingus</author></item><item><title>Frontier AI&apos;s Economic Exposure Is Jagged: Which Economies Are Most Exposed?</title><link>https://groundy.com/articles/frontier-ais-economic-exposure-is-jagged-which-economies-are-most-exposed/</link><guid isPermaLink="true">https://groundy.com/articles/frontier-ais-economic-exposure-is-jagged-which-economies-are-most-exposed/</guid><description>A new AI exposure index for 141 countries finds rich economies are far more exposed to frontier models than poor ones, so uniform retraining and subsidy policies fit badly.</description><pubDate>Fri, 10 Jul 2026 04:51:30 GMT</pubDate><dc:creator>Berry Mingus</dc:creator><atom:updated>2026-07-10T00:00:00.000Z</atom:updated><category>ai-exposure</category><category>cross-country-economics</category><category>global-labor-markets</category><category>remittance-exposure</category><category>gender-gap</category><category>policy-calibration</category><category>frontier-ai</category><author>Berry Mingus</author></item><item><title>LLM Burnout Is a Labor-Market Signal, Not Just a Wellness Story</title><link>https://groundy.com/articles/llm-burnout-is-a-labor-market-signal-not-just-a-wellness-story/</link><guid isPermaLink="true">https://groundy.com/articles/llm-burnout-is-a-labor-market-signal-not-just-a-wellness-story/</guid><description>AI coding tools speed output but hollow the craft that engages developers, producing burnout, a measurement gap, and a labor market repricing code work as supervision.</description><pubDate>Fri, 10 Jul 2026 03:55:19 GMT</pubDate><dc:creator>Berry Mingus</dc:creator><atom:updated>2026-07-11T00:00:00.000Z</atom:updated><category>ai-assisted-coding</category><category>developer-burnout</category><category>labor-market</category><category>agentic-workflows</category><category>craft-and-automation</category><category>github-next</category><author>Berry Mingus</author></item><item><title>Unit Labor Costs Hit Post-War High as Productivity Decouples From Wages</title><link>https://groundy.com/articles/unit-labor-costs-hit-post-war-high-as-productivity-decouples-from-wages/</link><guid isPermaLink="true">https://groundy.com/articles/unit-labor-costs-hit-post-war-high-as-productivity-decouples-from-wages/</guid><description>Q1 2026 BLS data shows unit labor costs at 123.78, a post-1947 high, while productivity grew just 0.3% and hourly compensation rose 2.1%. The gap reveals how productivity.</description><pubDate>Tue, 07 Jul 2026 00:04:39 GMT</pubDate><dc:creator>Berry Mingus</dc:creator><atom:updated>2026-07-07T00:00:00.000Z</atom:updated><category>labor-economics</category><category>productivity</category><category>wage-stagnation</category><category>unit-labor-costs</category><category>income-distribution</category><category>bls-data</category><category>economic-inequality</category><author>Berry Mingus</author></item><item><title>June 2026 Labor Force Contraction Tests Structural Detachment Thesis</title><link>https://groundy.com/articles/june-2026-labor-force-contraction-tests-structural-detachment-thesis/</link><guid isPermaLink="true">https://groundy.com/articles/june-2026-labor-force-contraction-tests-structural-detachment-thesis/</guid><description>June 2026 BLS data shows 720,000 workers exited the labor force while participation held at 61.5 percent, raising questions about whether policy should shift from stimulus to.</description><pubDate>Mon, 06 Jul 2026 23:43:22 GMT</pubDate><dc:creator>Berry Mingus</dc:creator><atom:updated>2026-07-06T00:00:00.000Z</atom:updated><category>labor-force-participation</category><category>economic-policy</category><category>employment-data</category><category>structural-unemployment</category><category>jobs-report</category><category>bls-data</category><category>recession-signals</category><author>Berry Mingus</author></item><item><title>June&apos;s Jobs Polarization Reveals AI-Era Skills Repricing</title><link>https://groundy.com/articles/junes-jobs-polarization-reveals-ai-era-skills-repricing/</link><guid isPermaLink="true">https://groundy.com/articles/junes-jobs-polarization-reveals-ai-era-skills-repricing/</guid><description>June&apos;s 4.2% unemployment rate masks deeper movement: sectoral polarization between professional and service work points to skill repricing, even as headline data supplies no.</description><pubDate>Mon, 06 Jul 2026 23:20:25 GMT</pubDate><dc:creator>Berry Mingus</dc:creator><atom:updated>2026-07-06T00:00:00.000Z</atom:updated><category>labor-force-participation</category><category>unemployment-rate</category><category>skill-repricing</category><category>ai-era-workforce</category><category>bls-jobs-report</category><category>sectoral-polarization</category><category>wage-data</category><author>Berry Mingus</author></item><item><title>Generative AI Moves the Freelance Bottleneck From Tasks to Skill Repricing</title><link>https://groundy.com/articles/generative-ai-moves-the-freelance-bottleneck-from-tasks-to-skill-repricing/</link><guid isPermaLink="true">https://groundy.com/articles/generative-ai-moves-the-freelance-bottleneck-from-tasks-to-skill-repricing/</guid><description>Generative AI already saturates a third of organizations, but the freelance-labor data is thin. The real shift moves the bottleneck from task automation to skill repricing.</description><pubDate>Mon, 29 Jun 2026 21:05:29 GMT</pubDate><dc:creator>Berry Mingus</dc:creator><atom:updated>2026-06-29T00:00:00.000Z</atom:updated><category>generative-ai</category><category>freelance-economy</category><category>online-labor-markets</category><category>skill-repricing</category><category>ai-adoption</category><category>preprints</category><author>Berry Mingus</author></item><item><title>LLM-Generated VeriFast Specs Shift the Trust Bottleneck from Proofs to Review</title><link>https://groundy.com/articles/llm-generated-verifast-specs-shift-the-trust-bottleneck-from-proofs-to-review/</link><guid isPermaLink="true">https://groundy.com/articles/llm-generated-verifast-specs-shift-the-trust-bottleneck-from-proofs-to-review/</guid><description>An arXiv preprint tests LLM-generated VeriFast specs. The real danger is a silently accepted wrong contract, because verifiers treat any accepted spec as gospel.</description><pubDate>Mon, 29 Jun 2026 08:30:32 GMT</pubDate><dc:creator>Berry Mingus</dc:creator><atom:updated>2026-07-10T00:00:00.000Z</atom:updated><category>formal-verification</category><category>llm-generated-specs</category><category>verifast</category><category>separation-logic</category><category>specification-review</category><category>proof-engineering</category><category>program-correctness</category><author>Berry Mingus</author></item><item><title>GLM-5.2&apos;s MIT License and 1M Context Shift Open-Source AI Map</title><link>https://groundy.com/articles/glm-5-2s-mit-license-and-1m-context-shift-open-source-ai-map/</link><guid isPermaLink="true">https://groundy.com/articles/glm-5-2s-mit-license-and-1m-context-shift-open-source-ai-map/</guid><description>GLM-5.2 ships MIT weights and a 1M context window, trails Claude Opus 4.8 by one percent on FrontierSWE, but the ZCode agent kernel reintroduces a Beijing dependency.</description><pubDate>Sun, 28 Jun 2026 05:14:14 GMT</pubDate><dc:creator>Berry Mingus</dc:creator><atom:updated>2026-06-28T00:00:00.000Z</atom:updated><category>glm5</category><category>zhipu-ai</category><category>open-source-llm</category><category>zcode</category><category>code-models</category><category>mit-license</category><author>Berry Mingus</author></item><item><title>Can AI Agents Audit the Insides of Other AI Models?</title><link>https://groundy.com/articles/can-ai-agents-audit-the-insides-of-other-ai-models/</link><guid isPermaLink="true">https://groundy.com/articles/can-ai-agents-audit-the-insides-of-other-ai-models/</guid><description>A June 2026 arXiv preprint finds LLM agents can explain another model&apos;s circuits but fail at validation. The auditor is itself an unverified LLM in the same model class.</description><pubDate>Sat, 27 Jun 2026 05:09:59 GMT</pubDate><dc:creator>Berry Mingus</dc:creator><atom:updated>2026-06-27T00:00:00.000Z</atom:updated><category>mechanistic-interpretability</category><category>ai-agents</category><category>interpretability</category><category>ai-safety</category><category>ai-auditing</category><category>model-transparency</category><author>Berry Mingus</author></item><item><title>Why Audio Deepfake Detectors Keep Losing the Voice-Cloning Arms Race</title><link>https://groundy.com/articles/why-audio-deepfake-detectors-keep-losing-the-voice-cloning-arms-race/</link><guid isPermaLink="true">https://groundy.com/articles/why-audio-deepfake-detectors-keep-losing-the-voice-cloning-arms-race/</guid><description>A 34,000-parameter audio deepfake detector reaches only 75 to 80 percent cross-domain accuracy, a result that shows why post-hoc detection sits downstream of generation.</description><pubDate>Mon, 22 Jun 2026 00:07:30 GMT</pubDate><dc:creator>Berry Mingus</dc:creator><atom:updated>2026-06-22T00:00:00.000Z</atom:updated><category>deepfake-detection</category><category>audio-deepfakes</category><category>voice-cloning</category><category>c2pa</category><category>content-provenance</category><category>machine-learning</category><author>Berry Mingus</author></item><item><title>Why AI Misreads Nigerian English: A Register Gap in Public Discourse</title><link>https://groundy.com/articles/why-ai-misreads-nigerian-english-a-register-gap-in-public-discourse/</link><guid isPermaLink="true">https://groundy.com/articles/why-ai-misreads-nigerian-english-a-register-gap-in-public-discourse/</guid><description>Models tuned on standard English misread Nigerian English and Pidgin register shifts, pushing intent validation onto local annotators vendors rarely fund.</description><pubDate>Sun, 21 Jun 2026 20:40:47 GMT</pubDate><dc:creator>Berry Mingus</dc:creator><atom:updated>2026-08-26T00:00:00.000Z</atom:updated><category>nigerian-english</category><category>nlp-bias</category><category>sentiment-analysis</category><category>content-moderation</category><category>code-switching</category><category>african-nlp</category><category>local-annotation</category><author>Berry Mingus</author></item><item><title>What YouTube&apos;s Coding Tutorials Teach About Who Belongs in Software</title><link>https://groundy.com/articles/what-youtubes-coding-tutorials-teach-about-who-belongs-in-software/</link><guid isPermaLink="true">https://groundy.com/articles/what-youtubes-coding-tutorials-teach-about-who-belongs-in-software/</guid><description>A June 2026 arXiv preprint argues YouTube software-engineering tutorials encode masculine defaults, shaping who self-selects into the field before any hiring screen.</description><pubDate>Sun, 21 Jun 2026 18:55:11 GMT</pubDate><dc:creator>Berry Mingus</dc:creator><atom:updated>2026-08-26T00:00:00.000Z</atom:updated><category>software-engineering</category><category>youtube-tutorials</category><category>gender-representation</category><category>critical-discourse-analysis</category><category>arxiv-preprint</category><category>developer-education</category><author>Berry Mingus</author></item><item><title>When an Algorithm Sequences Gig Hiring, Whose Objective Does It Optimize?</title><link>https://groundy.com/articles/when-an-algorithm-sequences-gig-hiring-whose-objective-does-it-optimize/</link><guid isPermaLink="true">https://groundy.com/articles/when-an-algorithm-sequences-gig-hiring-whose-objective-does-it-optimize/</guid><description>A June 2026 preprint makes the employer profit objective in gig hiring explicit, surfacing how optimized dispatch can shift timing risk onto contingent workers.</description><pubDate>Sat, 20 Jun 2026 18:16:04 GMT</pubDate><dc:creator>Berry Mingus</dc:creator><atom:updated>2026-06-20T00:00:00.000Z</atom:updated><category>gig-economy</category><category>contingent-labor</category><category>algorithmic-hiring</category><category>multi-armed-bandit</category><category>operations-research</category><category>labor-economics</category><author>Berry Mingus</author></item><item><title>AI Essay Grading: What a Probe of LLM Internals Reveals About Scoring</title><link>https://groundy.com/articles/ai-essay-grading-what-a-probe-of-llm-internals-reveals-about-scoring/</link><guid isPermaLink="true">https://groundy.com/articles/ai-essay-grading-what-a-probe-of-llm-internals-reveals-about-scoring/</guid><description>A June 2026 preprint finds essay quality is linearly decodable from LLM internals, but cannot show whether that signal tracks argument quality or just length and fluency.</description><pubDate>Fri, 19 Jun 2026 20:06:17 GMT</pubDate><dc:creator>Berry Mingus</dc:creator><atom:updated>2026-08-22T00:00:00.000Z</atom:updated><category>automated-essay-scoring</category><category>llm-interpretability</category><category>mechanistic-interpretability</category><category>linear-probing</category><category>construct-validity</category><category>ed-tech</category><author>Berry Mingus</author></item><item><title>Does Debate Quality Survive When LLMs Argue Outside English?</title><link>https://groundy.com/articles/does-debate-quality-survive-when-llms-argue-outside-english/</link><guid isPermaLink="true">https://groundy.com/articles/does-debate-quality-survive-when-llms-argue-outside-english/</guid><description>The first multilingual LLM debate competition covers four languages. Benchmarks already show reasoning degrades outside English, so teams must verify per-language parity.</description><pubDate>Tue, 09 Jun 2026 08:14:22 GMT</pubDate><dc:creator>Berry Mingus</dc:creator><atom:updated>2026-07-31T00:00:00.000Z</atom:updated><category>llm-debate</category><category>multilingual-evaluation</category><category>cross-cultural-reasoning</category><category>flageval</category><category>xcr-bench</category><category>model-evaluation</category><author>Berry Mingus</author></item><item><title>A Covert LLM Persuasion Experiment Was Shut Down: How Far Did the Bots Get?</title><link>https://groundy.com/articles/a-covert-llm-persuasion-experiment-was-shut-down-how-far-did-the-bots-get/</link><guid isPermaLink="true">https://groundy.com/articles/a-covert-llm-persuasion-experiment-was-shut-down-how-far-did-the-bots-get/</guid><description>A 2026 analysis of the bot comment archive from a halted Reddit experiment catalogs fabricated identities and bias triggers, but early shutdown leaves harm unmeasurable.</description><pubDate>Sun, 07 Jun 2026 15:03:20 GMT</pubDate><dc:creator>Berry Mingus</dc:creator><atom:updated>2026-07-31T00:00:00.000Z</atom:updated><category>llm-persuasion</category><category>reddit-experiment</category><category>ai-ethics</category><category>covert-bots</category><category>cognitive-bias</category><category>content-analysis</category><author>Berry Mingus</author></item><item><title>Do LLMs Understand Idioms in Low-Resource Languages?</title><link>https://groundy.com/articles/do-llms-understand-idioms-in-low-resource-languages/</link><guid isPermaLink="true">https://groundy.com/articles/do-llms-understand-idioms-in-low-resource-languages/</guid><description>MIDI tests idiom comprehension across 18 languages and finds LLMs rely on memorization over reasoning, with the sharpest failures falling on low-resource communities.</description><pubDate>Sat, 06 Jun 2026 12:11:09 GMT</pubDate><dc:creator>Berry Mingus</dc:creator><atom:updated>2026-07-31T00:00:00.000Z</atom:updated><category>idioms</category><category>multilingual-nlp</category><category>low-resource-languages</category><category>llm-evaluation</category><category>midi-benchmark</category><category>figurative-language</category><author>Berry Mingus</author></item><item><title>Can Teaching Logical Fallacies Inoculate People Against AI Misinformation?</title><link>https://groundy.com/articles/can-teaching-logical-fallacies-inoculate-people-against-ai-misinformation/</link><guid isPermaLink="true">https://groundy.com/articles/can-teaching-logical-fallacies-inoculate-people-against-ai-misinformation/</guid><description>An ACL 2026 study finds Socratic LLM tutoring teaches fallacy recognition better than bare LLMs, but whether those gains transfer to real misinformation is untested.</description><pubDate>Fri, 05 Jun 2026 08:09:08 GMT</pubDate><dc:creator>Berry Mingus</dc:creator><atom:updated>2026-07-31T00:00:00.000Z</atom:updated><category>logical-fallacies</category><category>misinformation</category><category>socratic-method</category><category>ai-education</category><category>acl-2026</category><category>llm-tutoring</category><author>Berry Mingus</author></item><item><title>Wikipedia&apos;s Foundation Is Running Big Tech&apos;s Anti-Labor Playbook, an Editor Argues</title><link>https://groundy.com/articles/wikipedias-foundation-is-running-big-techs-anti-labor-playbook-an-editor-argues/</link><guid isPermaLink="true">https://groundy.com/articles/wikipedias-foundation-is-running-big-techs-anti-labor-playbook-an-editor-argues/</guid><description>The Wikimedia Foundation fired union-organizing staff and dissolved the team that let editors direct product priorities. A veteran Wikipedian calls it Big Tech union busting.</description><pubDate>Fri, 29 May 2026 20:16:32 GMT</pubDate><dc:creator>Berry Mingus</dc:creator><atom:updated>2026-06-20T00:00:00.000Z</atom:updated><category>wikipedia</category><category>wikimedia-foundation</category><category>union-busting</category><category>labor-rights</category><category>ai-licensing</category><category>volunteer-governance</category><author>Berry Mingus</author></item><item><title>US Researchers Hit With New Federal Limits on Publishing With Foreign Collaborators</title><link>https://groundy.com/articles/us-researchers-hit-with-new-federal-limits-on-publishing-with-foreign/</link><guid isPermaLink="true">https://groundy.com/articles/us-researchers-hit-with-new-federal-limits-on-publishing-with-foreign/</guid><description>NIH and NASA are requiring pre-approval for foreign co-authors on US-funded papers without issuing formal guidance, applying export-control logic to manuscript authorship.</description><pubDate>Sun, 24 May 2026 13:22:16 GMT</pubDate><dc:creator>Berry Mingus</dc:creator><atom:updated>2026-05-24T00:00:00.000Z</atom:updated><category>nih</category><category>research-policy</category><category>export-control</category><category>scientific-publishing</category><category>foreign-collaboration</category><category>nasa</category><category>academic-compliance</category><author>Berry Mingus</author></item><item><title>Apple&apos;s $250M Siri Settlement: iPhone 16 Buyers Get $25 to $95 for Undelivered AI</title><link>https://groundy.com/articles/apples-250m-siri-settlement-iphone-16-buyers-get-25-to-95-for-undelivered/</link><guid isPermaLink="true">https://groundy.com/articles/apples-250m-siri-settlement-iphone-16-buyers-get-25-to-95-for-undelivered/</guid><description>Apple&apos;s $250M settlement over undelivered WWDC 2024 Siri features pays iPhone 15 Pro and 16 buyers $25-$95 per device, setting a legal precedent for AI marketing liability.</description><pubDate>Mon, 18 May 2026 14:45:14 GMT</pubDate><dc:creator>Berry Mingus</dc:creator><atom:updated>2026-05-18T00:00:00.000Z</atom:updated><category>apple-intelligence</category><category>class-action</category><category>siri</category><category>ai-liability</category><category>consumer-protection</category><category>settlement</category><author>Berry Mingus</author></item><item><title>AB 566 Forces Chrome and Safari to Ship Opt-Out Signals by 2027. It Shields Them from Google&apos;s 86% GPC Failure</title><link>https://groundy.com/articles/ab-566-forces-chrome-and-safari-to-ship-opt-out-signals-by-2027-then-shields/</link><guid isPermaLink="true">https://groundy.com/articles/ab-566-forces-chrome-and-safari-to-ship-opt-out-signals-by-2027-then-shields/</guid><description>AB 566 forces Chrome, Safari, and Edge to ship opt-out signals by January 2027, shields browsers from liability, and leaves Google&apos;s 86% GPC failure rate for CPPA to fix.</description><pubDate>Mon, 18 May 2026 12:47:11 GMT</pubDate><dc:creator>Berry Mingus</dc:creator><atom:updated>2026-05-26T00:00:00.000Z</atom:updated><category>global-privacy-control</category><category>ccpa</category><category>browser-privacy</category><category>california-privacy</category><category>ad-tech-compliance</category><category>cppa-enforcement</category><author>Berry Mingus</author></item><item><title>EU&apos;s 2027 Replaceable Battery Mandate: What It Means for Phone Buyers and Repairers Right Now</title><link>https://groundy.com/articles/eus-2027-replaceable-battery-mandate-what-it-means-for-phone-buyers-and/</link><guid isPermaLink="true">https://groundy.com/articles/eus-2027-replaceable-battery-mandate-what-it-means-for-phone-buyers-and/</guid><description>The EU&apos;s 2027 battery mandate is confirmed. Here&apos;s what &apos;user-replaceable&apos; legally means, which phones comply now, and how to buy smart before the rules change.</description><pubDate>Tue, 21 Apr 2026 16:00:00 GMT</pubDate><dc:creator>Berry Mingus</dc:creator><atom:updated>2026-07-03T00:00:00.000Z</atom:updated><category>eu-regulation</category><category>right-to-repair</category><category>consumer-electronics</category><category>sustainability</category><category>batteries</category><author>Berry Mingus</author></item><item><title>AI Diagnostics in 2026: Where Machines Now Outperform Radiologists</title><link>https://groundy.com/articles/ai-diagnostics-2026-where-machines-now-outperform/</link><guid isPermaLink="true">https://groundy.com/articles/ai-diagnostics-2026-where-machines-now-outperform/</guid><description>AI diagnostic tools outperform radiologists in specific imaging tasks, yet fewer than 10% of U.S. hospitals deploy them clinically. The evidence, gaps, and barriers.</description><pubDate>Sun, 15 Mar 2026 13:26:10 GMT</pubDate><dc:creator>Berry Mingus</dc:creator><atom:updated>2026-06-09T00:00:00.000Z</atom:updated><category>healthcare</category><category>ai-models</category><category>medical</category><category>radiology</category><category>diagnostics</category><category>digital-pathology</category><author>Berry Mingus</author></item></channel></rss>