--- title: "Who is responsible when AI gets it wrong?" description: "AI interpretation is reaching new users. Learn who is accountable for errors, what EU law says and how to prepare before you go live." image: https://www.interprefy.com/hubfs/Who%20is%20reponsible%20when%20AI%20gets%20it%20wrong.webp canonical: https://www.interprefy.com/resources/blog/who-is-responsible-when-ai-gets-it-wrong url: https://ai.interprefy.com/resources/blog/who-is-responsible-when-ai-gets-it-wrong.md last_converted: 2026-10-30T22:59:34.583Z --- ```json { "@context": "https://schema.org", "@graph": [ { "mainEntityOfPage": { "@type": "WebPage", "@id": "https://www.interprefy.com/resources/blog/who-is-responsible-when-ai-gets-it-wrong" }, "author": { "name": "Dayana Abuin Rios", "url": "https://www.interprefy.com/resources/blog/author/dayana-abuin-rios", "@type": "Person" }, "headline": "Who is responsible when AI gets it wrong?", "datePublished": "2026-10-30T21:58:37.000Z", "dateModified": "2026-10-30T21:58:48.544Z", "publisher": { "name": "Interprefy AG", "logo": { "url": "https://www.interprefy.com/hubfs/Interprefy%20Logo_Orange.png", "@type": "ImageObject" }, "@type": "Organization" }, "@type": "BlogPosting", "image": [ "https://www.interprefy.com/hubfs/Who%20is%20reponsible%20when%20AI%20gets%20it%20wrong.webp" ] }, { "@type": "VideoObject", "caption": { "@type": "MediaObject", "contentUrl": "https://www.interprefy.com/media-transcripts/159495977591/en.vtt", "inLanguage": "en", "name": "en Captions" }, "contentUrl": "https://6564114.fs1.hubspotusercontent-na1.net/hubfs/6564114/What%20Is%20Interprefy.mp4", "dateModified": "2025-09-16T13:30:13.207Z", "duration": "PT2M46.24S", "height": 2160, "name": "What Is Interprefy", "thumbnailUrl": "https://6564114.fs1.hubspotusercontent-na1.net/hubfs/6564114/What%20Is%20Interprefy.mp4/medium.jpg", "uploadDate": "2024-03-05T12:28:36.137Z", "width": 3840 }, { "@type": "BlogPosting", "@id": "https://www.interprefy.com/resources/blog/who-is-responsible-when-ai-interpretation-gets-it-wrong#article", "headline": "Who is responsible when AI gets it wrong?", "alternativeHeadline": "As AI interpretation becomes more accessible, the question of accountability is getting harder to ignore", "description": "AI interpretation is reaching new users. 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By [Dayana Abuin Rios](https://www.interprefy.com/resources/blog/author/dayana-abuin-rios) on October 30, 2026 ###### Topics: AI & Live Machine Translation Accessibility & Compliance ![Interprefy | Who is responsible when AI gets it wrong](https://www.interprefy.com/hs-fs/hubfs/Who%20is%20reponsible%20when%20AI%20gets%20it%20wrong.webp?width=1040&height=800&name=Who%20is%20reponsible%20when%20AI%20gets%20it%20wrong.webp) Who is responsible when AI gets it wrong?10:21 For most of its history, professional interpretation came with a safety net built in. The organisations that could afford interpreters usually also had people who knew how to work with them: event teams, language-services managers, conference organisers who knew to send the slides in advance and book the right specialists. Mistakes still happened, but there was expertise around the booth. [AI interpretation](https://www.interprefy.com/solutions/ai-speech-translation) is changing who uses interpretation. It costs a fraction of a human-interpreted session and can be set up at short notice, so it now reaches organisations that never had a budget for interpreters at all: regional offices of international organisations, associations, small and mid-sized companies, internal teams, and the live events they run. We see this in our own Interprefy figures. AI-only sessions on the Interprefy platform grew by almost a third between the first half of 2025 and the first half of 2026. That is good news. But many of these new users have no one whose job is language access. And it raises a question the language and events industry has not yet answered clearly: when AI interpretation gets something wrong, and it matters, who is responsible? It is a genuinely unresolved question, and no one in in the language industry has a complete answer yet. But we can all be much clearer about it than we are today. ## New users, new risks When an organisation books [professional interpreters](https://www.interprefy.com/solutions/remote-simultaneous-interpretation), much of the risk management happens without anyone noticing. Interpreters ask for preparation material, flag difficult terminology and say so when a session is outside their specialism. With AI, those checks do not happen by themselves. An organiser can switch on AI interpretation without anyone asking whether the audio will be clear, whether the speakers will use their native language, whether product names will come out right, or what happens if a figure is mistranslated. The technology is easy to use. Using it well is a different matter. The consequences of an error also vary widely. An awkward phrase in an internal webinar costs little. A mistranslated dosage in a medical briefing, a wrong figure in an investor update or a misunderstood instruction in a safety briefing is a different story. The same technology carries very different risks depending on where it is used. ## Where responsibility sits So who is responsible when something goes wrong: the organiser that chose the technology, the interpretation platform or the company behind the underlying AI model? The honest answer is all three, for different things. **The AI model provider** is responsible for the quality of the engine itself: how well it recognises speech, translates and speaks, and how openly its strengths and limitations are described. **The interpretation platform** is responsible for how that technology reaches people. At Interprefy, that means choosing and tuning engines, giving customers the tools to prepare, such as glossaries and lists of names and terms, protecting their data, marking AI output clearly and providing technical support if audio or connections fail. It also means being honest with customers when AI is not the right choice for a session. **The organiser** decides where and how AI is used. They know their speakers, their audience and what is at stake. Matching each session to the right solution is their call, ideally made with their provider's advice. Audiences are not responsible, but they should be able to judge what they hear. As Oddmund Braaten, CEO of Interprefy, puts it: > I tell our own people the same about any AI tool: it is a tool, and you still need to use your own judgement. - Oddmund Braaten, CEO, Interprefy That only works if listeners know they are hearing AI, which is why every AI channel on the Interprefy platform is marked "[AI](https://www.interprefy.com/resources/blog/eu-ai-act-ai-speech-translation-transparency)". What does not work is each party assuming another has it covered. Responsibilities should be written down: in contracts, in service descriptions and in the briefing for each event. | Party | Responsible for | | --- | --- | | AI model provider | The quality of the engine: how well it recognises speech, translates and speaks, and how openly its strengths and limitations are described. | | Interpretation platform | Choosing and tuning engines, glossaries, data protection, clear AI labelling, technical support and honest advice on when AI is not the right choice. | | Organiser | Deciding where and how AI is used, and matching each session to the right solution. | | Audience | Not responsible, but needs to know it is hearing AI so it can judge what it hears. | Who is responsible for what in AI interpretation. Source: Interprefy, 2026. ## What the law says, and what it doesn't Regulation is only beginning to answer the question, and only in part. The [EU AI Act](https://eur-lex.europa.eu/eli/reg/2024/1689/oj) sets rules for how AI is built and used, including that people must be told when they are dealing with AI, but it does not settle who is liable when someone is harmed. A separate EU law designed to do exactly that, the proposed [AI Liability Directive](https://www.europarl.europa.eu/legislative-train/theme-a-europe-fit-for-the-digital-age/file-ai-liability-directive), was withdrawn in October 2025. What remains is the EU's new [Product Liability Directive](https://eur-lex.europa.eu/eli/dir/2024/2853/oj/eng), which from 9 December 2026 treats software, including AI, as a product. It makes it easier for individuals to claim compensation when defective software causes certain kinds of harm, such as injury, damage to property or the loss of private data. None of this settles the everyday cases. A misunderstood decision in a meeting or a damaged relationship with a partner will mostly be dealt with through contracts, and through how carefully the technology was chosen and prepared. The best protection is not a legal clause after the fact. It is good decisions before the session starts. ## Prepare before you go live Most AI interpretation errors can be anticipated. The most effective step is also the simplest: [test the technology on a recording of a previous event](https://www.interprefy.com/contact-us) or a typical meeting before going live. It shows quickly how the system copes with the speakers, the subject and the audio, and where it struggles. This is how Interprefy starts with most new customers. We take a recording of one of their typical events, run it through the system and review the output together. Within minutes, it becomes clear which names, acronyms and expressions cause problems, and which terms they want left untranslated, such as brand and product names. Those go straight into a glossary for the event. The glossary is where most of the improvement comes from. Every organisation has words that matter to it and nowhere else: speaker and product names, acronyms, internal terms, and names and terms that should never be machine-translated. In sport, it might be scoring terms; in pharmaceuticals, drug names; in an association, the abbreviations everyone uses. Supplying these in advance is the single biggest improvement most organisers can make. Then check the conditions. Clear audio matters more than almost anything else, because speech recognition is the first link in the chain. AI also works best when people speak their native language; many speakers insist on English, and strong accents remain a challenge. And make sure technical support is on hand during the event. Even then, AI will never be perfect. Neither are human interpreters. The goal is not zero errors, but errors that are unlikely and, where they happen, not costly. ## Matching the technology to the stakes The most important decision comes before any of this: should this session use AI at all? A few questions help. **What happens if a sentence is misunderstood?** If the answer involves someone's health, safety, legal rights or job, professional interpreters are the right choice. **How structured is the speech?** AI handles presentations, updates and training well. It is not complexity that defeats it; machines can handle more complexity than we can. It is unstructured, ambiguous dialogue, such as negotiations or emotionally charged conversations, where humans still have the edge. **Can the audience check what they heard?** Slides, written summaries and follow-up materials reduce the impact of an error. **Do the conditions support it?** Good audio, preparation and a well-supported language combination all shift the balance towards AI. In practice, this leads to a sensible division of labour. AI handles volume, bringing interpretation to sessions and languages that would otherwise have none, while professional interpreters cover the sessions where an error would have serious consequences. ## Where this is heading Accountability will matter more, not less, as AI interpretation improves. The better the technology sounds, the more people will rely on it, and the less likely they are to question it. Speaking on the *Technology Unbox Podcast*, Oddmund Braaten, CEO of Interprefy, predicted: > I expect three things to become standard: contracts that spell out who is responsible for what, testing and preparation as a normal part of booking AI, and a growing role for linguists, not in the booth, but in preparing glossaries, reviewing results and tuning the systems for each customer. - Oddmund Braaten, CEO, Interprefy ## Accessibility needs accountability Making interpretation affordable is one of the most valuable things AI can do. Our aim has always been to democratise interpretation: to make it available and affordable, while keeping it secure and professional. But if accessibility comes without accountability, the first serious error will set the whole category back. That puts an obligation on providers like Interprefy to make the safe path the easy one: preparation tools, clear labelling, honest advice and support when it counts. And it asks organisers to treat choosing AI as a decision, not a default. When AI gets it wrong, the question of who is responsible should never be a surprise. The organisations that answer it before they go live will get the benefits of AI interpretation without the regrets. Before you go live Not sure if AI is right for your next session? Talk to our team about where AI fits in your events and how to prepare it before you go live. [Talk to an Expert](https://www.interprefy.com/contact-us?utm_source=blog&utm_medium=cta&utm_campaign=who-is-responsible-ai) ## Sources - [Directive (EU) 2024/2853 on liability for defective products](https://eur-lex.europa.eu/eli/dir/2024/2853/oj/eng), EUR-Lex - [AI liability directive (Legislative Train Schedule)](https://www.europarl.europa.eu/legislative-train/theme-a-europe-fit-for-the-digital-age/file-ai-liability-directive), European Parliament - [Regulation (EU) 2024/1689 (the EU AI Act)](https://eur-lex.europa.eu/eli/reg/2024/1689/oj), EUR-Lex - [Tweet](https://twitter.com/share) - - ![Dayana Abuin Rios](https://www.interprefy.com/hs-fs/hubfs/Dayana%20%CC%81s%20profile_Improved.jpg?width=100&height=100&name=Dayana%20%CC%81s%20profile_Improved.jpg) #### Written by Dayana Abuin Rios Learn about the latest developments at Interprefy by Dayana Abuin Rios, Global Content Manager at Interprefy. 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