{"id":2198,"date":"2020-03-10T07:36:03","date_gmt":"2020-03-10T14:36:03","guid":{"rendered":"https:\/\/melindaozel.com\/?p=2198"},"modified":"2025-02-21T16:02:34","modified_gmt":"2025-02-21T21:02:34","slug":"big-techs-homogeneous-hiring-habits-are-harming-our-data","status":"publish","type":"post","link":"https:\/\/melindaozel.com\/cs\/big-techs-homogeneous-hiring-habits-are-harming-our-data\/","title":{"rendered":"Homogenn\u00ed n\u00e1borov\u00e9 zvyklosti velk\u00fdch technologick\u00fdch firem po\u0161kozuj\u00ed na\u0161e data"},"content":{"rendered":"

V na\u0161em digit\u00e1ln\u00edm sv\u011bt\u011b zam\u011b\u0159en\u00e9m na spot\u0159ebitele jsme vytvo\u0159ili nal\u00e9havou pot\u0159ebu inovovat a vyv\u00edjet nov\u00e9 produkty. S trendem strojov\u00e9ho u\u010den\u00ed a samovoln\u00fdm tlakem na rychl\u00fd pohyb a rozb\u00edjen\u00ed - chci \u0159\u00edct \"budov\u00e1n\u00ed\" - v\u011bc\u00ed pot\u0159ebuj\u00ed velk\u00e9 technologick\u00e9 firmy neust\u00e1le konstrukt\u00e9ry. V d\u016fsledku toho se softwarov\u00ed in\u017een\u00fd\u0159i stali velmi \u017e\u00e1dan\u00fdm zbo\u017e\u00edm, kter\u00e9 dominuje po\u010dtu zam\u011bstnanc\u016f a podn\u011bcuje nab\u00eddkov\u00e9 v\u00e1lky nap\u0159\u00ed\u010d spole\u010dnostmi. S rostouc\u00edmi ambicemi v oblasti strojov\u00e9ho u\u010den\u00ed v\u0161ak rostou i pot\u0159eby v oblasti dat, co\u017e m\u011bn\u00ed probl\u00e9my zam\u011b\u0159en\u00e9 na in\u017een\u00fdry v mezioborov\u00e9 z\u00e1le\u017eitosti. Projekty, kter\u00e9 p\u0159in\u00e1\u0161ej\u00ed velmi nejednozna\u010dn\u00e1 data - jako nap\u0159\u00edklad v\u00fdrazy obli\u010deje pro sledov\u00e1n\u00ed obli\u010deje - vy\u017eaduj\u00ed porozum\u011bn\u00ed dat\u016fm p\u0159esahuj\u00edc\u00ed r\u00e1mec in\u017een\u00fdrstv\u00ed; vy\u017eaduj\u00ed mezioborov\u00e9 spojen\u00ed mezi in\u017een\u00fdrstv\u00edm a dopl\u0148kov\u00fdm oborem, kter\u00fd je aplikov\u00e1n. Proto je pro technologick\u00e9 firmy z\u00e1sadn\u00ed, aby p\u0159evzaly odpov\u011bdnost za integritu dat zapojen\u00edm odborn\u00edk\u016f z oboru do procesu v\u00fdvoje produktu.<\/p>\n

A\u010dkoli v kultu\u0159e velk\u00fdch technologick\u00fdch firem nen\u00ed up\u0159ednost\u0148ov\u00e1n\u00ed jin\u00fdch ne\u017e in\u017een\u00fdrsk\u00fdch rol\u00ed, ostatn\u00ed odv\u011btv\u00ed uzn\u00e1vaj\u00ed d\u016fle\u017eitost aktu\u00e1ln\u00edch odborn\u00fdch znalost\u00ed v oblasti strojov\u00e9ho u\u010den\u00ed. Nap\u0159\u00edklad oblast biotechnologi\u00ed se spol\u00e9h\u00e1 na spolupr\u00e1ci jak l\u00e9ka\u0159sk\u00fdch odborn\u00edk\u016f a<\/em> in\u017een\u00fd\u0159i. V tomto p\u0159\u00edpad\u011b je pot\u0159eba spolupr\u00e1ce z\u0159ejm\u00e1, ale v nejasn\u011bj\u0161\u00edch oblastech specializace nen\u00ed v\u017edy z\u0159ejm\u00e1. Jak ji\u017e bylo zm\u00edn\u011bno d\u0159\u00edve, jednou z hlavn\u00edch oblast\u00ed, kter\u00e1 trp\u00ed nejasnost\u00ed a nepochopen\u00edm, je sledov\u00e1n\u00ed obli\u010dej\u016f. B\u011b\u017en\u00e9 p\u0159\u00edpady pou\u017eit\u00ed sledov\u00e1n\u00ed obli\u010deje - v\u010detn\u011b obli\u010dejov\u00fdch filtr\u016f, detekce rys\u016f pro reklamu na produkty (nap\u0159. detekce rt\u016f pro testov\u00e1n\u00ed rt\u011bnek nebo detekce o\u010d\u00ed pro br\u00fdle) a avatar\u016f - jsou relativn\u011b ne\u0161kodn\u00e9. Pokud v\u0161ak uva\u017eujeme o m\u00e9n\u011b \"roztomil\u00fdch\" p\u0159\u00edpadech pou\u017eit\u00ed, jako je detekce emoc\u00ed, sledov\u00e1n\u00ed chov\u00e1n\u00ed a detekce podvod\u016f s aplikacemi v syst\u00e9mu trestn\u00edho soudnictv\u00ed, poji\u0161\u0165ovnictv\u00ed nebo ve sv\u011bt\u011b kybernetick\u00e9 bezpe\u010dnosti - v\u00fdkon modelu strojov\u00e9ho u\u010den\u00ed se st\u00e1v\u00e1 sporn\u00fdm; a pokud se prov\u00e1d\u00ed nespr\u00e1vn\u00fdm zp\u016fsobem, st\u00e1v\u00e1 se nebezpe\u010dn\u00fdm. S technologi\u00ed rozpozn\u00e1v\u00e1n\u00ed obli\u010deje a jej\u00edm neregulovan\u00fdm pou\u017e\u00edv\u00e1n\u00edm v r\u016fzn\u00fdch zem\u00edch a odv\u011btv\u00edch je ji\u017e zn\u00e1mo mnoho probl\u00e9m\u016f. Vzhledem k tomu, \u017ee sledov\u00e1n\u00ed v\u00fdrazu obli\u010deje neumo\u017e\u0148uje pouhou identifikaci osoby, ale sp\u00ed\u0161e ji pozoruje a vyvozuje z n\u00ed z\u00e1v\u011bry o jej\u00edm chov\u00e1n\u00ed, m\u016f\u017ee b\u00fdt mnohem invazivn\u011bj\u0161\u00ed.<\/p>\n

Navzdory z\u00e1sadn\u00edmu v\u00fdznamu v\u00fdrazov\u00fdch dat pro sledov\u00e1n\u00ed obli\u010deje se v oblasti velk\u00fdch technologi\u00ed \u010dasto nep\u0159ikl\u00e1d\u00e1 priorita kvalit\u011b v\u00fdrazov\u00fdch dat. Produktov\u00ed mana\u017ee\u0159i, in\u017een\u00fd\u0159i, u\u017eivatel\u0161t\u00ed v\u00fdzkumn\u00edci a softwarov\u00ed in\u017een\u00fd\u0159i se b\u011b\u017en\u011b spol\u00e9haj\u00ed na sv\u00e9 vlastn\u00ed povrchn\u00ed znalosti a ad hoc vyhled\u00e1v\u00e1n\u00ed, m\u00edsto aby vyu\u017eili hloubku znalost\u00ed, kterou by jim mohl poskytnout odborn\u00edk. Softwarov\u00ed in\u017een\u00fd\u0159i jsou sice mistry ve vytv\u00e1\u0159en\u00ed algoritm\u016f, ale \u010dasto maj\u00ed jen povrchn\u00ed znalosti o tom, co do dat pat\u0159\u00ed. Vzhledem k jejich vysok\u00e9mu pracovn\u00edmu vyt\u00ed\u017een\u00ed a zam\u011b\u0159en\u00ed na vlastn\u00ed specializovan\u00e9 znalosti nen\u00ed pro in\u017een\u00fdry re\u00e1ln\u00e9, aby si vytvo\u0159ili dal\u0161\u00ed odborn\u00e9 znalosti v oblasti pe\u010dliv\u00e9ho zkoum\u00e1n\u00ed jemn\u00fdch v\u00fdrazov\u00fdch dat nebo zvl\u00e1dnut\u00ed slo\u017eit\u00fdch koncept\u016f v oblasti v\u00fdzkumu emoc\u00ed.<\/p>\n

Ur\u010dit, jak\u00fd typ dat je pot\u0159eba, jak je shroma\u017e\u010fovat a jak je ozna\u010dovat, je velmi obt\u00ed\u017en\u00e9. choulostiv\u00fd proces<\/a>. Pokud se rozhodnete zam\u011b\u0159it na \u0161patn\u00e9 \u00fadaje, nez\u00e1le\u017e\u00ed na tom, jak dob\u0159e je shroma\u017e\u010fujete nebo ozna\u010dujete. Pokud se zam\u011b\u0159\u00edte na u\u017eite\u010dn\u00e1 data, ale shrom\u00e1\u017ed\u00edte je nevhodn\u011b, tak\u00e9 se to nepoda\u0159\u00ed. Je\u0161t\u011b v\u00edce sel\u017ee, pokud je neozna\u010d\u00edte p\u0159esn\u011b a\/nebo nep\u0159esn\u011b. Vzhledem k morfologick\u00fdm rozd\u00edl\u016fm v rysech obli\u010deje, p\u0159irozen\u00fdm zkreslen\u00edm p\u0159i interpretaci v\u00fdraz\u016f a kontroverz\u00edm mezi v\u00fdzkumn\u00edky emoc\u00ed i anatomy obli\u010deje mus\u00ed ka\u017ed\u00e1 skupina vyv\u00edjej\u00edc\u00ed algoritmy pro sledov\u00e1n\u00ed obli\u010deje se z\u00e1m\u011bry p\u0159esahuj\u00edc\u00edmi r\u00e1mec \"vyzkou\u0161ej, ne\u017e si koup\u00ed\u0161 rt\u011bnku\" p\u0159ijmout odpov\u011bdnost a etickou odpov\u011bdnost za integritu dat.<\/p>\n

Ne\u0161\u0165astn\u00fdm stavem velk\u00fdch technologi\u00ed je sb\u011br nebo z\u00edsk\u00e1v\u00e1n\u00ed velk\u00e9ho mno\u017estv\u00ed dat a jejich p\u0159ed\u00e1v\u00e1n\u00ed t\u0159et\u00edm stran\u00e1m, kter\u00e9 je ozna\u010duj\u00ed, nam\u00edsto toho, aby zajistily, \u017ee z\u00e1kladn\u00edm stavebn\u00edm kamen\u016fm jejich algoritm\u016f dob\u0159e rozum\u00ed ti, kdo je pou\u017e\u00edvaj\u00ed. Tito \u0161t\u00edtkova\u010di jsou obvykle extern\u00ed, na z\u00e1klad\u011b smlouvy a t\u00e9m\u011b\u0159 v\u017edy podhodnoceni. Pro sledov\u00e1n\u00ed kvality \u0161t\u00edtkova\u010d\u016f se standardn\u011b vytv\u00e1\u0159ej\u00ed a prosazuj\u00ed r\u016fzn\u00e9 kl\u00ed\u010dov\u00e9 ukazatele v\u00fdkonnosti neboli KPI, ale proto\u017ee se Big Tech rozhodl neinvestovat prost\u0159edky do lid\u00ed, kte\u0159\u00ed by mohli legitimn\u011b dohl\u00ed\u017eet na kvalitu pokro\u010dil\u00fdch dat, jsou KPI obvykle libovoln\u00e9 a maj\u00ed jen malou hodnotu. Probl\u00e9m d\u00e1le prohlubuje skute\u010dnost, \u017ee pokud in\u017een\u00fd\u0159i nejsou n\u00e1le\u017eit\u011b vybaveni hloubkou znalost\u00ed, aby mohli identifikovat z\u00e1kladn\u00ed pravdy, co vlastn\u011b m\u011b\u0159\u00ed? Existuje u\u010den\u00ed bez dohledu. A pak je tu ne\u0159\u00edzen\u00e9 in\u017een\u00fdrstv\u00ed.<\/p>\n

Kdy\u017e jsem pracoval pro jednu z velk\u00fdch p\u011bti spole\u010dnost\u00ed v Silicon Valley, byl jsem neust\u00e1le \u0161okov\u00e1n non\u0161alantn\u00edm p\u0159\u00edstupem ke slo\u017eit\u00fdm \u00fadaj\u016fm o sledov\u00e1n\u00ed obli\u010deje. P\u0159esto\u017ee moji kolegov\u00e9 byli \u0161pi\u010dkov\u00fdmi odborn\u00edky na v\u00fdvoj algoritm\u016f, m\u011bli jen povrchn\u00ed znalosti o anatomii obli\u010deje, z\u00e1kladn\u00edch pojmech emoc\u00ed a v\u00fdrazov\u00e9m chov\u00e1n\u00ed. Stejn\u011b jako u jin\u00fdch vysoce specializovan\u00fdch obor\u016f vy\u017eaduje pochopen\u00ed nuanc\u00ed lidsk\u00e9ho v\u00fdrazu roky intenzivn\u00edho studia a zku\u0161enost\u00ed. P\u0159esto\u017ee jsem byl hlavn\u00edm odborn\u00edkem na v\u00fdraz obli\u010deje, kter\u00fd zasv\u011btil sv\u016fj \u017eivot a kari\u00e9ru pochopen\u00ed nuanc\u00ed lidsk\u00e9 tv\u00e1\u0159e, byl jsem pravideln\u011b vylu\u010dov\u00e1n z d\u016fle\u017eit\u00fdch sch\u016fzek a pl\u00e1novac\u00edch zased\u00e1n\u00ed. \u010casto jsem p\u0159istihl spolupracovn\u00edky, jak se n\u00e1hodn\u011b prob\u00edraj\u00ed zastaral\u00fdmi a nep\u0159esn\u00fdmi referen\u010dn\u00edmi str\u00e1nkami o v\u00fdrazu (kter\u00e9 v sou\u010dasn\u00e9 dob\u011b poskytov\u00e1n\u00ed nov\u00fdch \u0159e\u0161en\u00ed pro tuto oblast<\/a>) p\u0159i pokusech o sestaven\u00ed pl\u00e1nu datov\u00e9ho potrub\u00ed. Moje odborn\u00e9 znalosti byly \u010dasto odsunuty do role dozorce a m\u00e9 dovednosti byly zneu\u017e\u00edv\u00e1ny k nepodstatn\u00fdm \u00fakol\u016fm, jako je klasifikace typ\u016f vous\u016f a barvy vlas\u016f. Kdy\u017e jsem upozornil na trendy v nekonzistenci dat nebo p\u0159edv\u00eddal probl\u00e9my s hardwarem, byl jsem posazen a nab\u00eddnuta mi lekce \"jak funguje strojov\u00e9 u\u010den\u00ed\".<\/p>\n

V mnoha pracovn\u00edch nab\u00eddk\u00e1ch se objevuje po\u017eadavek na X let praxe v oblasti sledov\u00e1n\u00ed obli\u010deje, ale po\u017eadavek na souvisej\u00edc\u00ed praxi nesta\u010d\u00ed. Stejn\u011b jako in\u017een\u00fdra, kter\u00fd v minulosti pracoval v oblasti l\u00e9ka\u0159sk\u00e9 techniky, neoprav\u0148uje k tomu, aby se stal l\u00e9ka\u0159em, pouh\u00e1 pr\u00e1ce na technologii sledov\u00e1n\u00ed obli\u010deje neoprav\u0148uje in\u017een\u00fdra k tomu, aby se stal odborn\u00edkem na v\u00fdrazy obli\u010deje nebo emoce. Pokud by se kladl v\u011bt\u0161\u00ed d\u016fraz na naj\u00edm\u00e1n\u00ed vhodn\u00fdch odborn\u00edk\u016f, mo\u017en\u00e1 by se zm\u00edrnil boj o in\u017een\u00fdry se vz\u00e1cn\u00fdmi a specifick\u00fdmi zku\u0161enostmi; takov\u00e9 zm\u00edrn\u011bn\u00ed by mohlo vytvo\u0159it prostor pro inovativn\u011bj\u0161\u00ed spolupr\u00e1ci mezi in\u017een\u00fdrstv\u00edm a dopl\u0148kov\u00fdmi obory, s nimi\u017e m\u016f\u017ee b\u00fdt spojeno.<\/p>\n

Tunelov\u00e9 vid\u011bn\u00ed velk\u00fdch technologick\u00fdch firem zam\u011b\u0159en\u00e9 na in\u017een\u00fdrstv\u00ed je nedbal\u00fd zvyk, kter\u00fd je t\u0159eba zm\u011bnit. A\u010dkoli jsou softwarov\u00ed in\u017een\u00fd\u0159i pro proces strojov\u00e9ho u\u010den\u00ed skute\u010dn\u011b nezbytn\u00ed, ambice strojov\u00e9ho u\u010den\u00ed n\u00e1s p\u0159ivedly do bodu, kdy mus\u00edme uznat pot\u0159ebu mezioborov\u00e9 \u010dinnosti. Data pro syst\u00e9my podm\u00edn\u011bn\u00e1 nuancemi by nem\u011bla b\u00fdt br\u00e1na na lehkou v\u00e1hu - zejm\u00e9na pokud krv\u00e1cej\u00ed potenci\u00e1lem pro invazivn\u00ed p\u0159\u00edpady pou\u017eit\u00ed. Pokud by si spole\u010dnosti cenily odbornosti v oblasti datov\u00fdch p\u0159edm\u011bt\u016f se stejnou \u00factou a podporou, jakou maj\u00ed v p\u0159\u00edpad\u011b in\u017een\u00fdrsk\u00fdch odborn\u00fdch znalost\u00ed, algoritmy\u00a0a\u00a0<\/em>\u00fadaje, z nich\u017e jsou sestaveny, by byly komplexn\u011bj\u0161\u00ed a m\u00e9n\u011b chybn\u00e9. Nedostatek ucelen\u00fdch datov\u00fdch syst\u00e9m\u016f zp\u016fsob\u00ed, \u017ee budeme m\u00edt neregulovan\u00e9 produkty n\u00e1chyln\u00e9 ke zkreslen\u00ed. Nerovnov\u00e1ha investic vych\u00fdlen\u00e1 sm\u011brem k algoritm\u016fm a odklon\u011bn\u00e1 od kvality dat povede k promarn\u011bn\u00e9mu in\u017een\u00fdrsk\u00e9mu \u00fasil\u00ed, nedostate\u010dn\u00fdm produkt\u016fm a \u0161\u00ed\u0159en\u00ed neetick\u00fdch technologi\u00ed.<\/p>\n

Neh\u00e1zejte v\u0161echny po\u010dty zam\u011bstnanc\u016f do jednoho ko\u0161\u00edku. Naj\u00edmejte zodpov\u011bdn\u011b.<\/p>","protected":false},"excerpt":{"rendered":"

S rostouc\u00edmi ambicemi v oblasti strojov\u00e9ho u\u010den\u00ed rostou i pot\u0159eby dat a probl\u00e9my zam\u011b\u0159en\u00e9 na in\u017een\u00fdry se m\u011bn\u00ed v mezioborov\u00e9 z\u00e1le\u017eitosti.<\/p>","protected":false},"author":60486633,"featured_media":2199,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[676756913,676756994,676756915,676756914,676757008,676756993],"tags":[],"class_list":["post-2198","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-action-units","category-ar-vr","category-facial-expressions","category-muscles","category-free","category-tech","generate-columns","tablet-grid-50","mobile-grid-100","grid-parent","grid-50"],"yoast_head":"\nBig Tech's Homogeneous Hiring Habits Are Harming Our Data - Face the FACS | Facial Expressions in Animation, AI, & Behavior<\/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:\/\/melindaozel.com\/cs\/big-techs-homogeneous-hiring-habits-are-harming-our-data\/\" \/>\n<meta property=\"og:locale\" content=\"cs_CZ\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Big Tech's Homogeneous Hiring Habits Are Harming Our Data\" \/>\n<meta property=\"og:description\" content=\"As machine learning ambitions grow, data needs grow as well, transforming engineer-centric problems into cross-disciplinary matters.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/melindaozel.com\/cs\/big-techs-homogeneous-hiring-habits-are-harming-our-data\/\" \/>\n<meta property=\"og:site_name\" content=\"Face the FACS | Facial Expressions in Animation, AI, & Behavior\" \/>\n<meta property=\"article:publisher\" content=\"https:\/\/facebook.com\/facetheFACS\/\" \/>\n<meta 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