{"id":2878,"date":"2023-07-22T20:51:19","date_gmt":"2023-07-22T20:51:19","guid":{"rendered":"https:\/\/dailyai.com\/?p=2878"},"modified":"2023-07-22T23:07:42","modified_gmt":"2023-07-22T23:07:42","slug":"generative-ai-is-leveling-up-fake-reviews","status":"publish","type":"post","link":"https:\/\/dailyai.com\/nb\/2023\/07\/generative-ai-is-leveling-up-fake-reviews\/","title":{"rendered":"Generativ kunstig intelligens gj\u00f8r falske anmeldelser bedre"},"content":{"rendered":"

Falske anmeldelser er allestedsn\u00e6rv\u00e6rende og uunng\u00e5elige, men de har aldri v\u00e6rt s\u00e5 vanskelige \u00e5 identifisere som n\u00e5. <\/strong><\/p>\n

If\u00f8lge noen estimater <\/span>40% av Amazon-anmeldelser er falske<\/span><\/a>, men dette gjelder ogs\u00e5 nettsteder som Trustpilot, Tripadvisor og Google Reviews. <\/span><\/p>\n

I april, <\/span>CNBC rapporterte<\/span><\/a> at noen Amazon-anmeldelser avsl\u00f8rer sitt opphav ved \u00e5 begynne med \"Som en AI-spr\u00e5kmodell ...\" For det meste er AI-genererte falske anmeldelser imidlertid utfordrende \u00e5 identifisere med det blotte \u00f8ye.\u00a0<\/span><\/p>\n

I et fors\u00f8k p\u00e5 \u00e5 sl\u00e5 ned p\u00e5 falske anmeldelser har Federal Trade Commission (FTC) nylig diskutert \u00e5 etablere regler for \u00e5 forby falske og betalte anmeldelser med strenge straffer for alle som bryter dem.\u00a0<\/span><\/p>\n

Michael Atleson, advokat i FTCs avdeling for reklamepraksis, sa: \"Vi vet ikke - vi har egentlig ingen mulighet til \u00e5 vite - i hvilken grad d\u00e5rlige akt\u00f8rer faktisk bruker noen av disse verkt\u00f8yene, og hvor mye som kan v\u00e6re botgenerert kontra menneskeskapt.\"<\/span><\/p>\n

Det forutsetter imidlertid at man kan skille falske anmeldelser fra ekte, noe som er sv\u00e6rt vanskelig n\u00e5 som kunstig intelligens er spr\u00e5klig presis og har kunnskap om en rekke emner.\u00a0<\/span><\/p>\n

AI forbedrer falske anmeldelser<\/span><\/h2>\n

Fakespot, en oppstartsbedrift som bruker kunstig intelligens til \u00e5 identifisere falske anmeldelser, har if\u00f8lge administrerende direkt\u00f8r Saoud Khalifah registrert en kraftig \u00f8kning av AI-genererte falske anmeldelser. Selskapet investerer n\u00e5 i teknikker som er utviklet for \u00e5 identifisere anmeldelser som er opprettet av AI-systemer, som ChatGPT.<\/span><\/p>\n

\"Det som er veldig annerledes i dag, er at modellene er s\u00e5 kunnskapsrike at de kan skrive om hva som helst\", sier Khalifah.<\/span><\/p>\n

Et annet sp\u00f8rsm\u00e5l er hvem som kan si at noen ikke bruker kunstig intelligens til \u00e5 hjelpe dem med \u00e5 skrive en autentisk anmeldelse?\u00a0<\/span><\/p>\n

AI-genererte anmeldelser er ikke strengt tatt i strid med Amazons retningslinjer. I f\u00f8lge en <\/span>talsperson for selskapet<\/span><\/a>lar selskapet kunder legge ut AI-skapte anmeldelser s\u00e5 lenge de er autentiske og overholder retningslinjene.<\/span><\/p>\n

Det viktigste sp\u00f8rsm\u00e5let er om AI-en som skal oppdage falske anmeldelser, kan overliste AI-en som genererer dem. Saoud Khalifah fra Fakespot bemerket at de f\u00f8rste AI-genererte falske anmeldelsene selskapet hans oppdaget, stammet fra India og ble opprettet av \"falske anmeldelsesg\u00e5rder\".<\/span><\/p>\n

\"Det er definitivt en vanskelig test \u00e5 best\u00e5 for disse deteksjonsverkt\u00f8yene\", sier Bhuwan Dhingra, assisterende professor i informatikk ved Duke University. \"For hvis modellene stemmer n\u00f8yaktig overens med m\u00e5ten mennesker skriver noe p\u00e5, kan du egentlig ikke skille mellom de to.\"<\/span><\/p>\n

Ben Zhao, professor i informatikk ved University of Chicago, hevdet p\u00e5 samme m\u00e5te at det er \"nesten umulig\" for AI \u00e5 fange opp AI-genererte anmeldelser p\u00e5 en effektiv m\u00e5te.\u00a0<\/span><\/p>\n

\"Det er en p\u00e5g\u00e5ende katt-og-mus-jakt, men det er til syvende og sist ikke noe grunnleggende som skiller et AI-skapt stykke innhold fra andre\", sier han.<\/span><\/p>\n

Inntil videre vil falske anmeldelser forbli en del av internettm\u00f8bleringen, og de vil sannsynligvis bli stadig vanskeligere \u00e5 skille fra ekte vare, b\u00e5de for mennesker og de avanserte AI-systemene som har til oppgave \u00e5 identifisere dem.\u00a0<\/span><\/p>\n

\"Det er skremmende for forbrukerne\", sier Teresa Murray, direkt\u00f8r for forbrukeroverv\u00e5kningskontoret til U.S. Public Interest Research Group.\u00a0<\/span><\/p>\n

\"Allerede n\u00e5 hjelper kunstig intelligens u\u00e6rlige bedrifter med \u00e5 spytte ut tusenvis av anmeldelser som h\u00f8res ekte ut, med en dialogisk tone i l\u00f8pet av sekunder.\"<\/span><\/p>\n

Tiden med d\u00e5rlig skrevne falske anmeldelser er forbi - gj\u00f8r deg klar for presist skrevne AI-anmeldelser som du ikke kan skille fra den ekte varen. <\/span><\/p>","protected":false},"excerpt":{"rendered":"

Falske anmeldelser er allestedsn\u00e6rv\u00e6rende og uunng\u00e5elige, men de har aldri v\u00e6rt s\u00e5 vanskelige \u00e5 identifisere. If\u00f8lge noen estimater er 40% av Amazon-anmeldelsene falske, men dette gjelder ogs\u00e5 nettsteder som Trustpilot, Tripadvisor og Google Reviews. I april rapporterte CNBC at noen Amazon-anmeldelser avsl\u00f8rer sitt opphav ved \u00e5 innlede teksten med \"As an AI language model ...\" For det meste er AI-genererte falske anmeldelser imidlertid utfordrende \u00e5 identifisere med det blotte \u00f8ye. I et fors\u00f8k p\u00e5 \u00e5 sl\u00e5 ned p\u00e5 falske anmeldelser diskuterte Federal Trade Commission (FTC) nylig \u00e5 etablere regler for \u00e5 forby falske og betalte anmeldelser med<\/p>","protected":false},"author":2,"featured_media":2880,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[88],"tags":[115,94,240],"class_list":["post-2878","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-ethics","tag-chatgpt","tag-deep-fakes","tag-fake-reviews"],"yoast_head":"\nGenerative AI is leveling up fake reviews | DailyAI<\/title>\n<meta name=\"description\" content=\"AI-generated reviews have become extremely hard to detect with the advent of advanced large language models (LLMs).\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" 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