{"id":45956,"date":"2022-11-23T10:31:48","date_gmt":"2022-11-23T09:31:48","guid":{"rendered":"https:\/\/safejournalists.net\/?p=45956"},"modified":"2022-11-23T10:31:48","modified_gmt":"2022-11-23T09:31:48","slug":"kako-ai-moze-pomoci-u-analizi-zastupljenosti-zena-u-vestima","status":"publish","type":"post","link":"https:\/\/safejournalists.net\/sr\/kako-ai-moze-pomoci-u-analizi-zastupljenosti-zena-u-vestima\/","title":{"rendered":"Kako AI mo\u017ee pomoc\u0301i u analizi zastupljenosti \u017eena u vestima"},"content":{"rendered":"

Od automatizacije proizvodnje sadr\u017eaja do pomaganja naporima provere \u010dinjenica, ve\u0161ta\u010dka inteligencija (AI) se poslednjih godina sve vi\u0161e koristi u novinarstvu. Usput su i moguc\u0301nosti koje algoritmi nude medijskim organizacijama postale jasnije.<\/p>\n

Me\u0111u njima, AI tehnologije mogu igrati ulogu u pobolj\u0161anju zastupljenosti \u017eena u vestima.\u00a0Ona je rekla on je rekao<\/a>, bot Financial Times-a, bio je jedan od prvih primera ovoga. Uveden 2018. godine, pomogao je redakciji sa sedi\u0161tem u Londonu da identifikuje raznolikost izvora u okviru svog izve\u0161tavanja.<\/p>\n

Medijske organizacije \u0161irom sveta sli\u010dno koriste AI tehnologije na mnogo na\u010dina kako bi im pomogle da analiziraju i identifikuju pristrasnosti u svom izve\u0161tavanju, otkriju govor mr\u017enje prema \u017eenama i jo\u0161 mnogo toga.<\/p>\n

Evo nekoliko primera.<\/b><\/p>\n

 <\/p>\n

Analiza pristrasnosti u medijima<\/b><\/p>\n

Sahiti Sarva<\/a>, in\u017eenjerka specijalizovana za kori\u0161c\u0301enje nauke o podacima za razumevanje politike, koautorka je vizuelnog eseja sa\u00a0Leonardom Nikoletijem<\/a>\u00a02021. godine u kome se ispituje priroda predstavljanja \u017eena u izve\u0161tavanju u vestima, pod naslovom\u00a0Kada \u017eene do\u0111u na naslovne strane<\/i><\/b><\/a>. Tim Sarve i Nikoleti za projekat je vi\u0161e od 10 godina analizirao vredne naslove iz 50 najboljih publikacija u Indiji, SAD, Velikoj Britaniji i Ju\u017enoj Africi.<\/p>\n

Sarva je objasnila svoj pristup na\u00a0virtuelnoj radionici<\/a>\u00a0koju je organizovala inicijativa\u00a0JournalismAI\u00a0<\/a>Londonske \u0161kole ekonomije ranije ove godine: \u201eSkrejpovali smo sve naslove ozna\u010dene sa 20 klju\u010dnih re\u010di koje su sinonim za \u017eene, devojke, \u017eensko i tako dalje, i to nam je dalo oko 382.139 naslova na engleskom.\u201d<\/p>\n

[Pro\u010ditajte vi\u0161e: Nova inicijativa se zala\u017ee za inovacije ve\u0161ta\u010dke inteligencije u redakcijama]<\/a>, eng<\/p>\n

Ovo je, naravno, bilo mnogo podataka. \u201eMislite da c\u0301e AI to olak\u0161ati\u201c, rekla je Sarva u intervjuu za ovaj \u010dlanak. Ali pre nego \u0161to neko po\u010dne da primenjuje bilo koji algoritam, ima mnogo posla. Naime, \u010di\u0161c\u0301enje, uklanjanje beskorisnih re\u010di i pronala\u017eenje pravih kodnih paketa za kori\u0161c\u0301enje. \u010cesto, rekla je, \u201etreba da budete kreativni u pogledu podataka koje c\u0301ete koristiti\u201c.<\/p>\n

\u201eNastavili smo i napravili sopstvene re\u010dnike koji ra\u010dunaju ne\u0161to \u0161to se naziva rodna pristrasnost u naslovima\u201c, objasnila je Sarva na radionici JournalismAI. \u201e[Ovo je uklju\u010divalo] kombinaciju rodnog jezika poput glumica, c\u0301erka, supruga, zajedno sa bihejvioralnim i dru\u0161tvenim stereotipima oko pola, poput emocionalne podr\u0161ke i brige.<\/p>\n

Kada je tim dobio ove re\u010dnike, koristio je metod ma\u0161inskog u\u010denja nazvan \u201eanaliza osec\u0301anja\u201c da bi razumeo kako to izgleda kada\u00a0\u017eene dospeju na naslovnice.\u00a0\u201eOtkrili smo da je pri\u010da \u2013 kada \u017eene dospevaju na naslovne strane \u2013 \u010desto veoma senzacionalna. Mnogo senzacionalnija od naslova koje obi\u010dno \u010ditamo i, vremenom, broj se samo povec\u0301avao. Ovo bi verovatno moglo biti zato \u0161to kada \u017eene dospeju na naslovne strane, pri\u010da \u0107e dva puta pre biti nasilna nego osna\u017euju\u0107a, rekala je Sarva.<\/p>\n

 <\/p>\n

Prac\u0301enje mizoginog diskursa<\/b><\/p>\n

Kao javne li\u010dnosti, \u017eene su \u010desto meta napada na dru\u0161tvenim mre\u017eama. Ko su po\u010dinioci? Novinari iz brazilske\u00a0AzMine<\/a>, argentinske\u00a0La Naci\u00f3n<\/a>\u00a0i latinoameri\u010dkih\u00a0CLIP-a<\/a>\u00a0i\u00a0DataCritica\u00a0<\/a>obratili su se AI kako bi saznali.<\/p>\n

Zajedno su razvili veb aplikaciju za otkrivanje govora mr\u017enje prema \u017eenama na Tviteru. \u201eSvesni eskalacije govora mr\u017enje, posebno upu\u0107enog \u017eenama, \u017eelimo da na\u0161 projekat bude u moguc\u0301nosti da brzo i asertivno prati kada neki od ovih mizoginih napada pokrene neki politi\u010dar\u201c, rekla je Barbara Liborio<\/a>\u00a0iz AzMine na istoj radionici JournalismAI.<\/p>\n

Napadi su, kako je aplikacijom utvr\u0111eno, dolazili posebno od politi\u010dara, me\u0111u ostalim javnim li\u010dnostima. \u201e[Ovo] je pokrenulo prave talase govora mr\u017enje\u201c, objasnila je Liborio, \u201ejer su pristalice tih politi\u010dara odlu\u010dile da napadaju ove \u017eene vi\u0161e nego pre\u201c.<\/p>\n

[Pro\u010ditajte vi\u0161e: Kako pobolj\u0161ati pokrivenost \u017eena iz radni\u010dke klase]<\/a>, eng<\/p>\n

Ako \u017eelite da model detektuje mizoginisti\u010dke poruke, nastavila je, AI tehnologija mora nau\u010diti \u0161ta je govor mr\u017enje prema \u017eenama. Kao prvi korak u procesu, tim Barbare Liborio napravio je bazu podataka sastavljenu od primera, ozna\u010davajuc\u0301i tvitove kao mizogine ili ne.<\/p>\n

Kada je ve\u0161ta\u010dka inteligencija nau\u010dila ovaj proces, njen tim je procenio koliko je efikasan u identifikaciji govora mr\u017enje prema \u017eenama. Napravili su sistem bodovanja, testirajuc\u0301i ga na portugalskom i \u0161panskom.<\/p>\n

Sa svojim modelom spremnim, napravili su veb aplikaciju koja poma\u017ee korisnicima da analiziraju tekst i datoteke. Liborio se nada da mogu da podele svoj prototip sa drugim inicijativama koje \u017eele da mapiraju rodno nasilje na dru\u0161tvenim mre\u017eama.<\/p>\n

 <\/p>\n

Polazna ta\u010dka<\/b><\/p>\n

\u201eTehnologije ve\u0161ta\u010dke inteligencije mogu biti od velike pomoc\u0301i da podr\u017ee novinare da bolje rade svoj posao\u201c, rekla je\u00a0Sabrina Argoub<\/a>, menad\u017eerka programa u JournalismAI. Kada je re\u010d o zastupljenosti \u017eena u vestima, rekla je ona, ve\u0161ta\u010dka inteligencija se mo\u017ee koristiti za pobolj\u0161anje transparentnosti i odgovornosti, uz podizanje svesti.\u00a0Projekat AIJO<\/a>, koji upore\u0111uje stopuu kom odnosu se mu\u0161karci i \u017eene citiraju u \u010dlancima ili prikazuju u vizuelnim vestima, jedan je od primera.<\/p>\n

Me\u0111utim, AI nije lek za sve, primetila je Argoub. Podr\u0161ka redakcija i novinara je neophodna da bi se ostvario istinski napredak po ovom pitanju.<\/p>\n

\u201eDobro je imati na umu da ma\u0161ina mo\u017ee da pru\u017ei podatke i da nam pomogne da proverimo koliko dobro radimo ili ne\u201c, rekla je ona. \u201eDa bismo preduzeli akciju, po\u010detna ta\u010dka i namera da se uhvati u ko\u0161tac sa nedovoljnom zastupljeno\u0161c\u0301u \u017eena u vestima treba da do\u0111u od samih redakcija i novinara.<\/p>\n","protected":false},"excerpt":{"rendered":"

Od automatizacije proizvodnje sadr\u017eaja do pomaganja naporima provere \u010dinjenica, ve\u0161ta\u010dka inteligencija (AI) se poslednjih godina sve vi\u0161e koristi u novinarstvu. Usput su i moguc\u0301nosti koje algoritmi nude medijskim organizacijama postale jasnije. Me\u0111u njima, AI tehnologije mogu igrati ulogu u pobolj\u0161anju zastupljenosti \u017eena u vestima.\u00a0Ona je rekla on je rekao, bot Financial Times-a, bio je jedan […]<\/p>\n","protected":false},"author":11,"featured_media":45957,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[1201],"tags":[],"class_list":["post-45956","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-news_belgrade"],"acf":[],"yoast_head":"\nKako AI mo\u017ee pomoc\u0301i u analizi zastupljenosti \u017eena u vestima – SafeJournalists<\/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:\/\/safejournalists.net\/sr\/kako-ai-moze-pomoci-u-analizi-zastupljenosti-zena-u-vestima\/?lang=sr\" \/>\n<meta property=\"og:locale\" content=\"sr_RS\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Kako AI mo\u017ee pomoc\u0301i u analizi zastupljenosti \u017eena u vestima – SafeJournalists\" \/>\n<meta property=\"og:description\" content=\"Od automatizacije proizvodnje sadr\u017eaja do pomaganja naporima provere \u010dinjenica, ve\u0161ta\u010dka inteligencija (AI) se poslednjih godina sve vi\u0161e koristi u novinarstvu. Usput su i moguc\u0301nosti koje algoritmi nude medijskim organizacijama postale jasnije. 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