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Fair Use and AI Training Data
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Opting Out of AI Training Datasets
Creators can reduce future use of their work for AI training by blocking AI crawlers in robots.txt, turning off training permissions in platform settings, and registering with opt-out services, and can check some public datasets with search tools.
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Przegląd
These measures mostly affect future collection by companies that choose to respect them; they do not remove work from models already trained.
Głębokie nurkowanie
Most large AI models are trained on material collected from the web. Common Crawl publishes huge crawls of the public internet, and image datasets such as LAION-5B, with about 5.85 billion image and caption pairs, were built by filtering them. LAION distributes links and captions rather than image files, but models trained with it downloaded the images from those links. To check whether your work appears, Spawning's Have I Been Trained lets you search LAION datasets by text or image. It covers only the datasets it indexes; there is no way to search the private data many companies use. The main prevention tools are: robots.txt. Many AI companies publish crawler names that sites can block, including GPTBot (OpenAI), ClaudeBot (Anthropic), CCBot (Common Crawl), Applebot-Extended (Apple) and Google-Extended, which controls use in Google's Gemini models without removing a site from Google Search. Some hosts and CDNs, such as Cloudflare, offer one-click AI crawler blocking. Platform settings. Services like LinkedIn and X have offered settings controlling training on user content, and Meta has offered objection forms in regions with stronger data protection law. Art sites such as DeviantArt and ArtStation introduced NoAI tags. Registries and legal reservations. Spawning's Do Not Train registry records opt-outs that some companies, including Stability AI for certain models, said they would honor. In the EU, the 2019 copyright directive allows rights holders to reserve text and data mining rights in machine-readable form, and the EU AI Act requires general-purpose model providers to respect such reservations. The limits are important. robots.txt is voluntary and not enforcement. Opt-outs are not retroactive, and trained models do not forget. Copies of your work reposted elsewhere are not covered by your site's rules. Blocking crawlers can also reduce visibility in AI-powered search. Opting out lowers exposure; it does not guarantee exclusion.
Wpływ strategiczny
Ryzyko i bezpieczeństwo
Zarówno katastrofalne, jak i codzienne szkody spowodowane sztuczną inteligencją zależą od tego, kto rozumie ryzyko i kto może podjąć działania.
Jaśniejsze decyzje
Umiejętność korzystania z usług publicznych i zawodowych wpływa na to, czy silna polityka bezpieczeństwa jest politycznie możliwa.
Przebijanie się przez szum
Jasne wyjaśnienia ograniczają wpływ szumu, PR laboratoryjnego i niejasnego teatru etycznego.
The Future of Opting Out of AI Training Datasets
Pressure is growing for opt-out signals that are standardized and legally meaningful rather than scattered across crawler names and platform menus. Standards bodies and industry groups are working on shared vocabularies for AI usage preferences, and EU rules are pushing providers to document how they respect reservations. Licensing deals between AI companies and publishers suggest a market for consented data is forming, though mostly for large rights holders. Lawsuits over training on copyrighted work may change the default rules in some countries. For now, individual creators should treat opt-outs as partial protection and check settings periodically, since platforms change them.
Implementacja w świecie rzeczywistym
An illustrator searches her portfolio images on Have I Been Trained, finds several in LAION-5B, and adds them to Spawning's Do Not Train registry, knowing this only binds companies that honor it.
A photographer who runs his own site adds robots.txt rules disallowing GPTBot, CCBot, ClaudeBot and Google-Extended, while leaving Googlebot allowed so his pages still appear in search results.
A writer on LinkedIn switches off the setting that allows her data to be used to train generative AI models and notes that this does not undo past use.
A small publisher in the EU adds a machine-readable reservation of text and data mining rights to its site and terms of use, relying on the EU copyright exception that lets rights holders opt out.
Zagrożenia i poręcze
Traktowanie ryzyka egzystencjalnego jako science-fiction, choć łączy w sobie możliwości.
Mylenie bezpieczeństwa produktów powierzchniowych z wyrównaniem przy dużej autonomii.
Pozostawienie odbiorcom nieanglojęzycznym i nieeksperckim jedynie źródeł o niskiej jakości.
Plan wdrożenia
Oddziel ryzyko szkód, niewłaściwego użycia i utraty kontroli/niewspółosiowości produktu.
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Często zadawane pytania
What is Opting Out of AI Training Datasets?
Creators can reduce future use of their work for AI training by blocking AI crawlers in robots.txt, turning off training permissions in platform settings, and registering with opt-out services, and can check some public datasets with search tools. These measures mostly affect future collection by companies that choose to respect them; they do not remove work from models already trained.
What does the LAION-5B dataset actually distribute?
LAION provides URLs and captions. Model trainers downloaded the images from those links.
What does blocking Google-Extended in robots.txt do?
Google-Extended is a control token for AI training use. Blocking it leaves Search indexing untouched.
What is the main limitation of opting out after a model is trained?
Opt-outs affect future collection by companies that honor them. Past training is not undone.
Why does blocking crawlers in your own site's robots.txt not fully protect your work?
robots.txt is a request that well-behaved crawlers follow, and it only applies to the site that publishes it.
What does Spawning's Have I Been Trained tool let you do?
It searches the datasets it indexes. It cannot see private training data used by many companies.
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