{"id":12043,"date":"2024-05-08T15:17:20","date_gmt":"2024-05-08T15:17:20","guid":{"rendered":"https:\/\/dailyai.com\/?p=12043"},"modified":"2024-05-08T15:17:20","modified_gmt":"2024-05-08T15:17:20","slug":"ai-transcription-tools-generate-harmful-hallucinations","status":"publish","type":"post","link":"https:\/\/dailyai.com\/fr\/2024\/05\/ai-transcription-tools-generate-harmful-hallucinations\/","title":{"rendered":"Les outils de transcription de l'IA g\u00e9n\u00e8rent des hallucinations nuisibles"},"content":{"rendered":"

Les transcripteurs de la parole au texte sont devenus inestimables, mais une nouvelle \u00e9tude montre que lorsque l'IA se trompe, le texte hallucin\u00e9 est souvent nuisible.<\/strong><\/p>\n

Les outils de transcription par IA sont devenus extr\u00eamement pr\u00e9cis et ont transform\u00e9 la fa\u00e7on dont les m\u00e9decins conservent les dossiers des patients ou dont nous r\u00e9digeons les proc\u00e8s-verbaux des r\u00e9unions. Nous savons qu'ils ne sont pas parfaits et nous ne sommes donc pas surpris lorsque la transcription n'est pas tout \u00e0 fait correcte.<\/p>\n

Une nouvelle \u00e9tude<\/a> a constat\u00e9 que lorsque des transcripteurs d'IA plus avanc\u00e9s, comme les OpenAI<\/span>Les erreurs commises par les membres du groupe \"Whisper\" ne se limitent pas \u00e0 produire un texte brouill\u00e9 ou al\u00e9atoire. Ils hallucinent des phrases enti\u00e8res, ce qui est souvent p\u00e9nible.<\/p>\n

Nous savons que tous les mod\u00e8les d'IA ont des hallucinations. Lorsque ChatGPT<\/span> ne conna\u00eet pas la r\u00e9ponse \u00e0 une question, il inventera souvent quelque chose au lieu de dire \"je ne sais pas\".<\/p>\n

Des chercheurs de l'universit\u00e9 Cornell, de l'universit\u00e9 de Washington, de l'universit\u00e9 de New York et de l'universit\u00e9 de Virginie ont constat\u00e9 que m\u00eame si l'API Whisper \u00e9tait meilleure que d'autres outils, elle hallucinait encore un peu plus de 1% du temps.<\/p>\n

La conclusion la plus importante est que lorsqu'ils ont analys\u00e9 le texte hallucin\u00e9, ils ont constat\u00e9 que \"38% des hallucinations comprennent des pr\u00e9judices explicites tels que la perp\u00e9tuation de la violence, l'\u00e9tablissement d'associations inexactes ou l'implication d'une fausse autorit\u00e9\".<\/p>\n

Il semble que Whisper n'aime pas les silences g\u00eanants, donc lorsqu'il y a des pauses plus longues dans le discours, il a tendance \u00e0 halluciner davantage pour combler les vides.<\/p>\n

Ce probl\u00e8me se pose avec acuit\u00e9 lorsqu'il s'agit de transcrire des paroles prononc\u00e9es par des personnes atteintes d'aphasie, un trouble de l'\u00e9locution qui fait que la personne a souvent du mal \u00e0 trouver les mots justes.<\/p>\n

Chuchotement imprudent<\/h2>\n

Le document pr\u00e9sente les r\u00e9sultats d'exp\u00e9riences men\u00e9es avec des versions de Whisper datant du d\u00e9but de l'ann\u00e9e 2023. OpenAI<\/span> a depuis am\u00e9lior\u00e9 l'outil, mais la tendance de Whisper \u00e0 passer du c\u00f4t\u00e9 obscur lorsqu'il a des hallucinations est int\u00e9ressante.<\/p>\n

Les chercheurs ont class\u00e9 les hallucinations nuisibles comme suit :<\/p>\n

    \n
  • Perp\u00e9tuation de la violence :<\/strong> Hallucinations pr\u00e9sentant des sc\u00e8nes de violence, des allusions sexuelles ou des st\u00e9r\u00e9otypes d\u00e9mographiques.<\/li>\n
  • Associations inexactes :<\/strong> des hallucinations qui introduisent de fausses informations, telles que des noms incorrects, des relations fictives ou des \u00e9tats de sant\u00e9 erron\u00e9s.<\/li>\n
  • Fausse autorit\u00e9 :<\/strong> Ces hallucinations comprenaient des textes se faisant passer pour des personnalit\u00e9s ou des m\u00e9dias faisant autorit\u00e9, tels que des YouTubers ou des pr\u00e9sentateurs de journaux t\u00e9l\u00e9vis\u00e9s, et comportaient souvent des directives pouvant conduire \u00e0 des attaques par hame\u00e7onnage ou \u00e0 d'autres formes de tromperie.<\/li>\n<\/ul>\n

    Voici quelques exemples de transcriptions o\u00f9 les mots en gras sont des ajouts hallucin\u00e9s de Whisper.<\/p>\n

    \"\"
    Les ajouts hallucin\u00e9s de Whisper \u00e0 la transcription sont indiqu\u00e9s en gras. Source : arXiv<\/figcaption><\/figure>\n
    \"\"
    Les ajouts hallucin\u00e9s de Whisper \u00e0 la transcription sont indiqu\u00e9s en gras. Source : arXiv<\/figcaption><\/figure>\n

    On peut imaginer \u00e0 quel point ce type d'erreurs peut \u00eatre dangereux si les transcriptions sont suppos\u00e9es exactes lorsqu'il s'agit de documenter la d\u00e9claration d'un t\u00e9moin, un appel t\u00e9l\u00e9phonique ou le dossier m\u00e9dical d'un patient.<\/p>\n

    Pourquoi Whisper a-t-il pris une phrase sur un pompier sauvant un chat et ajout\u00e9 une \"poussette macul\u00e9e de sang\" \u00e0 la sc\u00e8ne, ou ajout\u00e9 un \"couteau de terreur\" \u00e0 une phrase d\u00e9crivant quelqu'un ouvrant un parapluie ?<\/p>\n

    OpenAI<\/span> semble avoir corrig\u00e9 le probl\u00e8me, mais n'a pas donn\u00e9 d'explication sur le comportement de Whisper. Lorsque les chercheurs ont test\u00e9 les nouvelles versions de Whisper, ils ont obtenu beaucoup moins d'hallucinations probl\u00e9matiques.<\/p>\n

    Les implications d'hallucinations, m\u00eame l\u00e9g\u00e8res ou tr\u00e8s peu nombreuses, dans les transcriptions peuvent \u00eatre graves.<\/p>\n

    L'article d\u00e9crit un sc\u00e9nario r\u00e9el dans lequel un outil comme Whisper est utilis\u00e9 pour transcrire des entretiens vid\u00e9o de candidats \u00e0 l'emploi. Les transcriptions sont introduites dans un syst\u00e8me d'embauche qui utilise un mod\u00e8le linguistique pour analyser la transcription et trouver le candidat le plus appropri\u00e9.<\/p>\n

    Si une personne interrog\u00e9e fait une pause un peu trop longue et que Whisper ajoute \"couteau de terreur\", \"poussette ensanglant\u00e9e\" ou \"caress\u00e9\" \u00e0 une phrase, cela peut affecter ses chances d'obtenir le poste.<\/p>\n

    Les chercheurs ont d\u00e9clar\u00e9 que OpenAI<\/span> devrait faire savoir que Whisper hallucine et qu'il devrait chercher \u00e0 savoir pourquoi il g\u00e9n\u00e8re des transcriptions probl\u00e9matiques.<\/p>\n

    Ils sugg\u00e8rent \u00e9galement que les nouvelles versions de Whisper soient con\u00e7ues pour mieux r\u00e9pondre aux besoins des communaut\u00e9s mal desservies, telles que les personnes souffrant d'aphasie ou d'autres troubles de la parole.<\/p>","protected":false},"excerpt":{"rendered":"

    Les outils de transcription de la parole en texte sont devenus inestimables, mais une nouvelle \u00e9tude montre que lorsque l'IA se trompe, le texte hallucin\u00e9 est souvent nuisible. Les outils de transcription par IA sont devenus extr\u00eamement pr\u00e9cis et ont transform\u00e9 la fa\u00e7on dont les m\u00e9decins tiennent les dossiers des patients ou dont nous r\u00e9digeons les proc\u00e8s-verbaux des r\u00e9unions. Nous savons qu'ils ne sont pas parfaits et nous ne sommes donc pas surpris lorsque la transcription n'est pas tout \u00e0 fait correcte. Une nouvelle \u00e9tude a r\u00e9v\u00e9l\u00e9 que lorsque des transcripteurs IA plus avanc\u00e9s, comme Whisper d'OpenAI, commettent des erreurs, ils ne se contentent pas de produire un texte confus ou al\u00e9atoire. Ils hallucinent des phrases enti\u00e8res, et ces hallucinations sont souvent p\u00e9nibles. Nous savons que tous les mod\u00e8les d'IA hallucinent. Lorsque<\/p>","protected":false},"author":6,"featured_media":12048,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[84],"tags":[163,107],"class_list":["post-12043","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-industry","tag-ai-risks","tag-generative-ai"],"yoast_head":"\nAI transcription tools generate harmful hallucinations | DailyAI<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/dailyai.com\/fr\/2024\/05\/ai-transcription-tools-generate-harmful-hallucinations\/\" \/>\n<meta property=\"og:locale\" content=\"fr_FR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"AI transcription tools generate harmful hallucinations | DailyAI\" \/>\n<meta property=\"og:description\" content=\"Speech-to-text transcribers have become invaluable but a new study shows that when the AI gets it wrong the hallucinated text is often harmful. 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