{"id":3964,"date":"2023-08-09T06:56:16","date_gmt":"2023-08-09T06:56:16","guid":{"rendered":"https:\/\/dailyai.com\/?p=3964"},"modified":"2023-08-09T06:56:16","modified_gmt":"2023-08-09T06:56:16","slug":"we-want-unbiased-llms-but-its-impossible-heres-why","status":"publish","type":"post","link":"https:\/\/dailyai.com\/sv\/2023\/08\/we-want-unbiased-llms-but-its-impossible-heres-why\/","title":{"rendered":"Vi vill ha opartiska LLM:er, men det \u00e4r om\u00f6jligt. H\u00e4r \u00e4r varf\u00f6r."},"content":{"rendered":"

F\u00f6retag som OpenAI och Meta arbetar h\u00e5rt f\u00f6r att g\u00f6ra sina spr\u00e5kmodeller s\u00e4krare och mindre partiska, men helt opartiska modeller kan vara en pipedream.<\/strong><\/p>\n

A <\/span>ny forskningsrapport<\/span><\/a> fr\u00e5n University of Washington, Carnegie Mellon University och Xi'an Jiaotong University drog slutsatsen att alla AI-spr\u00e5kmodeller som de testade uppvisade politisk partiskhet.<\/span><\/p>\n

Efter att ha unders\u00f6kt k\u00e4llorna till partiskheten drog de slutsatsen att partiskhet i spr\u00e5kmodeller \u00e4r oundvikligt.<\/span><\/p>\n

Chan Park, en av artikelf\u00f6rfattarna, s\u00e4ger: \"Vi tror inte att n\u00e5gon spr\u00e5kmodell kan vara helt fri fr\u00e5n politiska f\u00f6rdomar.\"<\/span><\/p>\n

Forskarna testade 14 olika spr\u00e5kmodeller och bad dem uttala sig om \u00e4mnen som demokrati, rasism och feminism, f\u00f6r att se vilken sida av det politiska spektrumet modellerna hamnade p\u00e5.<\/span><\/p>\n

Resultaten visade att OpenAI:s ChatGPT och GPT-4 l\u00e5g l\u00e4ngst till v\u00e4nster medan Meta:s Llama gav de mest h\u00f6gerinriktade svaren.<\/span><\/p>\n

Utbildningsdata \u00e4r inte den enda k\u00e4llan till partiskhet<\/span><\/h2>\n

Den uppenbara k\u00e4llan till f\u00f6rsp\u00e4nning<\/a> \u00e4r de data som dessa modeller tr\u00e4nas p\u00e5. Men den nya forskningen visade att \u00e4ven efter att ha rensat data fr\u00e5n f\u00f6rdomar var modellerna mottagliga f\u00f6r f\u00f6rdomar p\u00e5 l\u00e5g niv\u00e5 som fanns kvar i data.<\/span><\/p>\n

Man skulle kunna f\u00f6rv\u00e4nta sig att en LLM som tr\u00e4nats p\u00e5 en massa Fox News-data skulle vara mer pro-republikansk i sina svar. Men problemet ligger inte bara i tr\u00e4ningsdatan.\u00a0<\/span><\/p>\n

Det visar sig att n\u00e4r de f\u00f6rtr\u00e4nade spr\u00e5kmodellerna finjusteras och anv\u00e4nds, f\u00e5r de ytterligare f\u00f6rdomar fr\u00e5n sina operat\u00f6rer.<\/span><\/p>\n

Soroush Vosoughi, bitr\u00e4dande professor i datavetenskap vid Dartmouth College, f\u00f6rklarade att f\u00f6rdomar introduceras i n\u00e4stan varje skede av en LLM:s utveckling.<\/span><\/p>\n

Ett exempel p\u00e5 detta \u00e4r hur OpenAI f\u00f6rs\u00f6ker ta bort partiskhet fr\u00e5n sina modeller. De anv\u00e4nder en teknik som kallas \"Reinforcement Learning through Human Feedback\" eller RLHF f\u00f6r att tr\u00e4na sina modeller.<\/span><\/p>\n

I RLHF tr\u00e4nar en m\u00e4nsklig operat\u00f6r modellen p\u00e5 samma s\u00e4tt som man tr\u00e4nar en hundvalp. Om valpen g\u00f6r n\u00e5got bra f\u00e5r den en godbit. Om den tuggar i sig dina tofflor: \"Stygg hund!\"<\/span><\/p>\n

En RLHF-operat\u00f6r st\u00e4ller n\u00e5gra fr\u00e5gor till modellen och en annan operat\u00f6r utv\u00e4rderar sedan de m\u00e5nga svar som modellen ger. Den andra operat\u00f6ren utv\u00e4rderar svaren och rangordnar dem efter vad de gillade mest.<\/span><\/p>\n

I en <\/span>inl\u00e4gg om hur de tr\u00e4nar sin AI<\/span><\/a>OpenAI sade att de instruerar m\u00e4nskliga utbildare att \"undvika att ta st\u00e4llning till kontroversiella \u00e4mnen\" och att \"granskare inte b\u00f6r gynna n\u00e5gon politisk grupp\".<\/span><\/p>\n

Det l\u00e5ter som en bra id\u00e9, men \u00e4ven om vi verkligen f\u00f6rs\u00f6ker att inte vara det, \u00e4r alla m\u00e4nniskor partiska. Och det p\u00e5verkar oundvikligen modellens tr\u00e4ning.\u00a0<\/span><\/p>\n

Till och med f\u00f6rfattarna till den artikel som vi n\u00e4mnde ovan erk\u00e4nde i sin slutsats att deras egna f\u00f6rdomar kan ha p\u00e5verkat deras forskning.<\/span><\/p>\n

L\u00f6sningen kan vara att f\u00f6rs\u00f6ka g\u00f6ra spr\u00e5kmodellerna s\u00e5 bra som m\u00f6jligt och sedan anpassa dem till de f\u00f6rdomar som m\u00e4nniskor har. <\/span><\/p>\n

M\u00e4nniskor s\u00e4ger ofta att de vill ha den opartiska sanningen, men sedan slutar de h\u00e5lla sig till sin f\u00f6redragna nyhetsk\u00e4lla som Fox eller CNN.\u00a0<\/span><\/p>\n

Vi \u00e4r inte alltid \u00f6verens om vad som \u00e4r r\u00e4tt eller fel och den h\u00e4r nya forskningen verkar visa att AI inte heller kommer att kunna hj\u00e4lpa oss att r\u00e4kna ut det.<\/span><\/p>","protected":false},"excerpt":{"rendered":"

F\u00f6retag som OpenAI och Meta arbetar h\u00e5rt f\u00f6r att g\u00f6ra sina spr\u00e5kmodeller s\u00e4krare och mindre partiska, men helt opartiska modeller kan vara en pipedr\u00f6m. Ett nytt forskningsdokument fr\u00e5n University of Washington, Carnegie Mellon University och Xi'an Jiaotong University drog slutsatsen att alla AI-spr\u00e5kmodeller som de testade visade politisk bias. Efter att ha unders\u00f6kt k\u00e4llorna till partiskheten drog de slutsatsen att partiskhet i spr\u00e5kmodeller var oundvikligt. Chan Park, en av artikelf\u00f6rfattarna, s\u00e4ger: \"Vi tror inte att n\u00e5gon spr\u00e5kmodell kan vara helt fri fr\u00e5n politiska f\u00f6rdomar.\" Forskarna testade 14 olika spr\u00e5kmodeller och fr\u00e5gade dem<\/p>","protected":false},"author":6,"featured_media":3979,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[88],"tags":[103,213,207,105,91],"class_list":["post-3964","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-ethics","tag-ai-debate","tag-bias","tag-llm","tag-machine-learning","tag-policy"],"yoast_head":"\nWe want unbiased LLMs but it\u2019s impossible. 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