{"id":418,"date":"2026-09-18T08:09:06","date_gmt":"2026-09-18T00:09:06","guid":{"rendered":"https:\/\/aidashxp.com\/microsoft-exec-ai-scraping-theft\/"},"modified":"2026-09-18T08:09:06","modified_gmt":"2026-09-18T00:09:06","slug":"microsoft-exec-ai-scraping-theft","status":"publish","type":"post","link":"https:\/\/aidashxp.com\/en\/microsoft-exec-ai-scraping-theft\/","title":{"rendered":"Microsoft executive calls AI scraping \u201cunprecedented theft\u201d: Key evidence emerges in NYT copyright case"},"content":{"rendered":"

In the New York Times (NYT) copyright lawsuit against Microsoft and OpenAI, newly unsealed court documents revealed a sharp internal comment from a Microsoft executive: Microsoft\u2019s Director of Applied Sciences Brent Hecht<\/strong> stated that using large models to \u201cscrape\u201d content from across the web for AI training constitutes\u201cunprecedented theft\u201d<\/strong>This criticism from within the industry has subtly shifted public opinion in the copyright litigation.<\/p>\n\n\n\n

The exposed key statement<\/h2>\n\n\n\n

According to court documents unsealed on Thursday, The New York Times\u2019 lawyers cited a statement by Hecht: \u201cHundreds of millions of people worldwide will soon view large models\u2019 \u2018sucking dry\u2019 of all their works as \u2018an unprecedented theft\u2019\u2014\u2018almost no one wants their creative content used this way, and no one is compensated for it.\u2019\u201d Plaintiffs regard this internal remark as strong evidence undermining the legality of Microsoft\u2019s and OpenAI\u2019s model training practices.<\/p>\n\n\n\n

How Microsoft responded<\/h2>\n\n\n\n

The Orlando Sentinel, also a plaintiff in this case, reported that Microsoft portrayed Hecht in a filing as \u201csomeone hired to play contrarian<\/strong>\u201d (someone on the payroll to play a contrarian), attempting to diminish the weight of this internal statement. Yet regardless, an active Microsoft executive publicly questioning the copyright foundation of his own company\u2019s technology dealt a significant blow to Microsoft\u2019s and OpenAI\u2019s defense.<\/p>\n\n\n\n

Case background: A lawsuit defining industry boundaries<\/h2>\n\n\n\n

The New York Times sued OpenAI and Microsoft in late 2023, accusing them of unauthorized use of its articles to train ChatGPT<\/a>models, constituting copyright infringement. This litigation has drawn intense attention because its ruling could set a precedent for the entire generative AI industry: if the court determines that scraping content from the public internet without authorization constitutes infringement, nearly all large-model companies relying on such data for training would face substantial compliance costs and legal risks.<\/p>\n\n\n\n

What this means for the AI industry<\/h2>\n\n\n\n

As more internal documents emerge through litigation, AI companies\u2019 \u201cuse-first-ask-later\u201d training approach is facing mounting pressure. For practitioners and users alike, the trajectory of this case warrants ongoing attention\u2014it may directly affect future AI products\u2019 training data sources, licensing costs, and even the viability of certain free features.<\/p>\n\n\n\n

Summarize<\/h2>\n\n\n\n

An internal executive\u2019s single word\u2014\u201ctheft\u201d\u2014adds industry-insider corroboration to the AI copyright debate. When even Microsoft\u2019s own personnel question scrape-based training, AI companies\u2019 reliance on \u201cfair use\u201d as a defense is likely to grow increasingly untenable.<\/p>\n\n\n\n

AI Dash<\/a> \u2014 Discover the best AI tools<\/p>","protected":false},"excerpt":{"rendered":"

\u5728\u7ebd\u7ea6\u65f6\u62a5\uff08NYT\uff09\u8d77\u8bc9\u5fae\u8f6f\u548c Open […]<\/p>\n","protected":false},"author":0,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"site-sidebar-layout":"default","site-content-layout":"","ast-site-content-layout":"default","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","ast-disable-related-posts":"","theme-transparent-header-meta":"","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"default","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"ast-content-background-meta":{"desktop":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"footnotes":""},"categories":[1],"tags":[],"class_list":["post-418","post","type-post","status-publish","format-standard","hentry","category-uncategorized"],"_links":{"self":[{"href":"https:\/\/aidashxp.com\/en\/wp-json\/wp\/v2\/posts\/418","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/aidashxp.com\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/aidashxp.com\/en\/wp-json\/wp\/v2\/types\/post"}],"replies":[{"embeddable":true,"href":"https:\/\/aidashxp.com\/en\/wp-json\/wp\/v2\/comments?post=418"}],"version-history":[{"count":0,"href":"https:\/\/aidashxp.com\/en\/wp-json\/wp\/v2\/posts\/418\/revisions"}],"wp:attachment":[{"href":"https:\/\/aidashxp.com\/en\/wp-json\/wp\/v2\/media?parent=418"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/aidashxp.com\/en\/wp-json\/wp\/v2\/categories?post=418"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/aidashxp.com\/en\/wp-json\/wp\/v2\/tags?post=418"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}