Cutarwar wakilci

Tsarin yana haifar da cutar wakilci idan suka ɓata sunan ƙungiyar mutane ta hanyar da ba ta dace ba. Lalacewar wakilci ya haɗa da ci gaba da ra'ayoyi masu cutarwa game da ko rage wanzuwar ƙungiyar zamantakewa, kamar launin fata, ƙabila, jinsi, ko ƙungiyar addini.  Algorithms na koyon injina galibi suna yin cutar wakilci lokacin da suka koyi alamu daga bayanan da ke da son zuciya na algorithm, kuma an nuna cewa hakan ya faru ne da manyan samfuran harshe .  Duk da cewa hana cutar wakilci a cikin samfura yana da mahimmanci don hana son zuciya mai cutarwa, masu bincike galibi ba su da takamaiman ma'anoni na cutar wakilci kuma suna haɗa shi da cutar rarrabuwa, rashin daidaito na rarraba albarkatu tsakanin ƙungiyoyin zamantakewa, wanda aka fi nazari sosai kuma yana da sauƙin aunawa.  Duk da haka, fahimtar illolin wakilci yana ƙaruwa kuma hana su ya zama yanki mai aiki na bincike. Masu bincike kwanan nan sun ƙirƙiri hanyoyi don ƙididdige cutar wakilci a cikin algorithms yadda ya kamata, suna samun ci gaba kan hana wannan cutar a nan gaba.  

 Nau'o'in 
Manyan nau'ikan lahani guda uku sun haɗa da nuna bambanci, ƙyama, da rashin amincewa. Wadannan subcategories suna gabatar da haɗari da yawa ga mutane da kungiyoyi.

Ana sauƙaƙa wa mutane tunanin cewa ra'ayin wani rukuni ne na mutane, yawanci ta hanyar launin fata da jinsi. Wannan yakan haifar da hana ilimi, aiki, gidaje, da sauran damammaki.  Misali, ra'ayin cewa 'yan tsiraru na 'yan Asiya Amurkawa suna da hazaka sosai kuma suna da ƙwarewa a lissafi na iya zama illa ga aiki da ilimi. 

Lalacewar wakilci yana faruwa ne lokacin da wakilcin ƙungiyoyin bayanai suka inganta ra'ayoyi masu cutarwa, haɓaka wariya da wariya a cikin zamantakewa. Wannan abin da ya faru yana da matuƙar muhimmanci a cikin nuna ƙungiyoyin da aka ware, waɗanda suka ƙunshi mutane masu launin fata, mata, mutanen LGBTQ+, da mutanen da ke da nakasa. Hotunan kafofin watsa labarai na waɗannan ƙungiyoyi galibi suna daina aiki don kama jerin sunayensu da sarkakiyar su. Madadin haka, galibi ana rage su zuwa zane-zane masu girma ɗaya, wanda a ƙarshe ke ci gaba da nuna wariya a cikin zamantakewa. Waɗannan zane-zanen da aka tsara suna taimakawa wajen taimakawa ra'ayoyi masu haɗari da kuma ware waɗannan wurare.

Cin zarafi wani aiki ne na sukar mutane ba bisa ƙa'ida ba. Wannan yakan faru ne lokacin da aka yi wa ƙungiyoyin zamantakewa rashin adalci.  ] Misali, lokacin neman sunaye masu "baƙi" idan aka kwatanta da waɗanda "fari" ke yi, wasu tsarin dawo da su yana ƙarfafa fahimtar ƙarya game da aikata laifuka ta hanyar nuna tallace-tallace ga kasuwancin bayar da beli.  Tsarin na iya canza wakilcin ƙungiya zuwa ƙasa da matsayin zamantakewa, wanda galibi ke haifar da rashin kulawa daga al'umma. 

Bincike ya nuna cewa nuna abubuwa masu haɗari a kafofin watsa labarai na iya haifar da babban tasiri ga mutane da kuma fannoni. Lawrence Bobo ya binciki batun ra'ayin ƙabilanci a cikin fina-finai, talabijin, da tallatawa. Baƙar fata 'yan Amurka galibi ana karɓar ayyukansu ta hanyar siffofi kamar "halayen tashin hankali ," " lalaci ," ko kuma "kawai don abubuwan gamsuwa." Duk da cewa waɗannan wakilcin na iya bayyana daban-daban a waje, suna ci gaba da haɓaka tsarin da ke ƙarƙashin farin jini da rashin daidaiton launin fata.  A matsayin yanayi, ana yawan wakilta baƙar fata a matsayin masu aikata laifukan doka ko kuma a matsayin manyan mukamai, wanda ke ƙara wa goyon bayan ra'ayin ƙabilanci da wariyar launin fata ta hukumomi .

Rashin fahimta, ko kuma rashin fahimtar juna, na iya bayyana ta hanyoyi da yawa, ciki har da, amma ba'a iyakance ga, gogewa da raba ƙungiyoyin zamantakewa ba, da kuma hana mutane 'yancin bayyana kansu.  Gogewa da raba ƙungiyoyin zamantakewa ya ƙunshi rashin daidaiton ganuwa na wasu ƙungiyoyin zamantakewa; musamman, rashin cancantar tsari a cikin tsarin algorithmic yana ci gaba da haifar da rashin daidaito ta hanyar ba da gudummawa ga ƙarancin wakilcin ƙungiyoyin zamantakewa.  Rashin barin mutane su gane kansu yana da alaƙa sosai saboda asalin mutane na iya 'shafe' ko 'ɓacewa' a cikin waɗannan algorithms. Rashin fahimta yana haifar da cutarwa fiye da matakin saman mutane ga mutane: cutar da hankali, warewar zamantakewa, da rashin tsaro na motsin rai na iya fitowa daga wannan ƙaramin rukuni na cutarwa ta wakilci. 

 Ƙididdiga 
Kamar yadda haɗarin lalacewar wakilci ya zama mafi fahimta, wasu masu bincike sun haɓaka hanyoyin don auna lalacewar wakilai a cikin algorithms.

Modeling stereotyping is one way to identify representational harm. Representational stereotyping can be quantified by comparing the predicted outcomes for one social group with the ground-truth outcomes for that group observed in real data. For example, if individuals from group A achieve an outcome with a probability of 60%, stereotyping would be observed if it predicted individuals to achieve that outcome with a probability greater than 60%. The group modeled stereotyping in the context of classification, regression, and clustering problems, and developed a set of rules to quantitatively determine if the model predictions exhibit stereotyping in each of these cases.[<span title="This claim needs references to reliable sources. (December 2023)">citation needed</span>]

Sauran yunkurin auna lalacewar wakilci sun mayar da hankali kan aikace-aikacen algorithms a cikin takamaiman yankuna kamar rubutun hoto, aikin algorithm wanda ke samar da taƙaitaccen Bayanan hoto. A cikin binciken da aka yi game da rubutun hoto, masu bincike sun auna nau'ikan lahani guda biyar. Don ƙididdigar stereotyping, sun auna adadin kalmomin da ba daidai ba waɗanda aka haɗa a cikin rubutun hoto na samfurin idan aka kwatanta da rubutun zinariya. Sun sake nazarin kowane ɗayan kalmomin da ba daidai ba, suna ƙayyade ko kalmar da ba daidai ta nuna alamar da ke da alaƙa da hoton ko kuma kuskuren da ba shi da alaƙa, wanda ya ba su damar samun ma'auni na adadin da ke faruwa a cikin wannan ƙarni. Wadannan masu bincike sun kuma yi ƙoƙari su auna mummunan rauni na wakilci. Don auna wannan, sun bincika mitar da aka ambata mutane a cikin hoton a cikin rubutun da aka samar. An yi la'akari da cewa idan ba a ambaci mutane a cikin taken ba, to wannan wani nau'i ne na rashin mutunci.

 Misalan 
Ɗaya daga cikin sanannun misalai na lalacewar wakilci Google ne ya yi a cikin 2015 lokacin da wani algorithm a cikin Hotunan Google ya rarraba Black mutane a matsayin gorillas. Masu haɓakawa a Google sun ce matsalar ta samo asali ne saboda babu isasshen fuskokin Black mutane a cikin bayanan horo don algorithm don koyon bambancin tsakanin Black mutane da gorillas. Google ya ba da gafara kuma ya gyara batun ta hanyar toshe algorithms dinsa daga rarraba komai a matsayin firamare. A cikin 2023, har yanzu an toshe algorithm na hotunan Google daga gano gorillas a cikin hotuna.

Wani misali mai yawa na lalacewar wakilci shine yiwuwar ƙididdigar da aka ƙayyade a cikin kalmomin da aka saka, waɗanda aka horar da su ta amfani da rubutu mai yawa. Wadannan kalmomin da aka saka sune wakilcin kalma a matsayin jerin lambobi a cikin sararin samaniya, wanda ke bawa mutum damar lissafin alaƙar da kamanceceniya tsakanin kalmomi. Koyaya, binciken da aka yi kwanan nan ya nuna cewa waɗannan kalmomin da aka saka na iya ƙunshe da nau'o'i masu lahani, kamar misali na yau da kullun cewa kalmar "mai tsara kwamfuta" sau da yawa tana da alaƙa da "mutum" fiye da "mata" a cikin sararin samaniya. Ana iya fassara wannan a matsayin kuskuren wakilci na shirye-shiryen kwamfuta a matsayin sana'a da maza suka fi dacewa, wanda zai zama misali na cutar wakilci.

 Magana da cutar wakilci 
Shirye-shiryen rage radadin wakilci sun haɗa da tallata hotunan ƙungiyoyin da aka ware a kafofin watsa labarai waɗanda suka fi haɗaka da kuma daidai. Masana da masu zanga-zanga sun ba da shawarar cewa hanyar rage raunin wakilci ya dogara ne akan ɗaga zaɓin muryoyi a baya da kuma a gaban kyamarar bidiyo ta dijital. Lokacin da aka ba wa ƙungiyoyin da aka ware damar wakiltar kansu, za su iya duba ra'ayoyin gargajiya kuma su gabatar da abubuwan da suka faru da gaske.

A cikin 'yan shekarun nan, ƙoƙarin ƙara wakilcin mutanen launin fata, mata, da LGBTQ+ a kafofin watsa labarai na gargajiya ya sami ɗan ci gaba. Fina-finai kamar Selma, wanda Ava DuVernay ta shirya, da kuma shirye-shiryen talabijin kamar Pose, wanda Ryan Murphy ya ƙirƙira, an yaba musu sosai saboda wakilcinsu mai zurfi da girmamawa na al'ummomin da aka ware. Waɗannan ayyuka suna da halaye masu rikitarwa da labarai waɗanda ke wucewa ga ra'ayoyi marasa tushe.

Wakiltar kai wata hanya ce mai mahimmanci wajen magance matsalar wakilci. Ta hanyar samar da wuraren da aka ware don ƙirƙirar labaransu, masu tsara kafofin watsa labarai za su iya rage ci gaba da ra'ayoyin masu haɗari. Wannan tsari ya ƙunshi kera kayayyakin kafofin watsa labarai ta hanyar mahalarta waɗannan al'ummomi da kuma tsarin kafofin watsa labarai masu wahala waɗanda suka yi watsi da su a tarihi.

 Bayanan da aka ambata 

Rukuni:Fasaha