{"id":5702,"date":"2025-12-15T08:27:00","date_gmt":"2025-12-15T07:27:00","guid":{"rendered":"https:\/\/www.websupport.cz\/blog\/?p=5702"},"modified":"2025-11-21T15:30:12","modified_gmt":"2025-11-21T14:30:12","slug":"navod-jak-trenovat-vase-algoritmy-a-neporusit-pri-tom-gdpr","status":"publish","type":"post","link":"https:\/\/www.websupport.cz\/blog\/2025\/12\/navod-jak-trenovat-vase-algoritmy-a-neporusit-pri-tom-gdpr\/","title":{"rendered":"N\u00e1vod: Jak tr\u00e9novat va\u0161e algoritmy a neporu\u0161it p\u0159i tom do GDPR?"},"content":{"rendered":"\n

M\u00e1te skv\u011blou aplikaci, kter\u00e1 u\u017e m\u00e1 sv\u00e9 z\u00e1kazn\u00edky a pot\u0159ebujete inovovat? Asi v\u00edte, \u017ee pokud pou\u017eijete pro tr\u00e9nink AI nebo jin\u00fdch algoritm\u016f osobn\u00ed \u00fadaje, automaticky se na v\u00e1s sesype spr\u0161ka povinnost\u00ed podle GDPR. O rizic\u00edch ani nemluv\u011b. Tr\u00e9nov\u00e1n\u00ed na synteticky vytvo\u0159en\u00fdch datech zase nemus\u00ed p\u0159in\u00e9st v\u00fdsledky, kter\u00e9 pot\u0159ebujete. Jak to tedy ud\u011blat?<\/p>\n\n\n\n

To tajemstv\u00ed se jmenuje anonymizace dat podle GDPR.<\/strong><\/p>\n\n\n\n

Ka\u017ed\u00fd dobr\u00fd IT specialista v\u00e1m \u0159ekne, \u017ee anonymizace dat je v dne\u0161n\u00edm technologick\u00e9m sv\u011bt\u011b utopie. Sta\u010d\u00ed p\u0159idat p\u00e1r \u00fadaj\u016f \u2013 i kdy\u017e to n\u011bkdy m\u016f\u017ee b\u00fdt dost t\u011b\u017ek\u00e9 \u2013 a um\u00edte zp\u011btn\u011b identifikovat danou osobu, tedy jej\u00ed \u00fadaje deanonymizovat.<\/p>\n\n\n\n

To je pravda.<\/p>\n\n\n\n

Nap\u0159\u00edklad jeden v\u00fdzkum <\/a>uk\u00e1zal, \u017ee anal\u00fdzou anonymizovan\u00e9ho datasetu s \u00fadaji z telefonn\u00edch hovor\u016f 1,5 milionu lid\u00ed v okruhu 100 km podle um\u00edst\u011bn\u00ed ant\u00e9ny, kter\u00e1 propojovala jejich hovor nebo SMS, nasb\u00edran\u00fdch za 15 m\u011bs\u00edc\u016f, bylo mo\u017en\u00e9 identifikovat 95 lid\u00ed jen s pou\u017eit\u00edm 4 zn\u00e1m\u00fdch lokaliza\u010dn\u00edch bod\u016f (kde se za t\u011bch 15 m\u011bs\u00edc\u016f nach\u00e1zeli). A k identifikaci v\u00edce ne\u017e 50\u202f% lid\u00ed sta\u010dily jen 2 lokaliza\u010dn\u00ed body (tedy domov \u2013 pr\u00e1ce). V\u00edce v\u011bd\u011bt nen\u00ed t\u0159eba, jen 2 \u00fadaje z va\u0161\u00ed GPS navigace a v\u011bd\u00ed, \u017ee jste to vy.<\/p>\n\n\n\n

Tak\u017ee realita d\u00e1v\u00e1 za pravdu IT specialist\u016fm. Ale nezoufejte. GDPR toti\u017e nevy\u017eaduje nezvratnou, 100% anonymizaci v technologick\u00e9m, ale v pr\u00e1vn\u00edm smyslu. Jak tomu rozum\u011bt?<\/p>\n\n\n\n

Pod\u00edvejme se na to.<\/p>\n\n\n\n

Co jsou osobn\u00ed \u00fadaje?<\/strong><\/h2>\n\n\n\n

Z\u0159ejm\u011b mnoz\u00ed z v\u00e1s rad\u011bji p\u0159esko\u010d\u00ed tuto \u010d\u00e1st, proto\u017ee \u201ev\u0161ak to je jasn\u00e9\u201c. Divili byste se, ale ur\u010dit, co je\u0161t\u011b jsou a co u\u017e nejsou osobn\u00ed \u00fadaje, nen\u00ed v\u016fbec jednoduch\u00e9.<\/p>\n\n\n\n

Podle pr\u00e1va jde o \u00fadaje, kter\u00e9 se t\u00fdkaj\u00ed osoby, kterou jsme u\u017e identifikovali, nebo kterou m\u016f\u017eeme s jejich pomoc\u00ed potenci\u00e1ln\u011b identifikovat.<\/p>\n\n\n\n

Identifikovat osobu<\/strong> znamen\u00e1 mo\u017enost vy\u010dlenit ji z ur\u010dit\u00e9 skupiny<\/strong> bu\u010f p\u0159\u00edmo \u2013 podle jej\u00edho jm\u00e9na, p\u0159\u00edjmen\u00ed, adresy, data narozen\u00ed nebo jin\u00fdch \u00fadaj\u016f, nebo nep\u0159\u00edmo. Nep\u0159\u00edmo znamen\u00e1, \u017ee osobu m\u016f\u017eeme odd\u011blit od ostatn\u00edch ve skupin\u011b, ani\u017e bychom znali jej\u00ed b\u011b\u017en\u00e9 identifika\u010dn\u00ed \u00fadaje. Sta\u010d\u00ed v\u011bd\u011bt, \u017ee je j\u00ed p\u0159id\u011blen ur\u010dit\u00fd identifik\u00e1tor (nap\u0159. cookies) nebo m\u00e1me jin\u00e9 \u00fadaje, nap\u0159. z GPS o tras\u00e1ch, kter\u00fdmi ka\u017ed\u00fd den cestuje, jak\u00e9 weby nav\u0161t\u011bvuje, jak\u00e1 dynamick\u00e1 IP j\u00ed byla p\u0159id\u011blena, kde se p\u0159ihla\u0161uje apod.<\/p>\n\n\n\n

Jak tedy zjist\u00edme, \u017ee dataset \u00fadaj\u016f, ze kter\u00fdch nev\u00edme, jak se n\u011bkdo jmenuje nebo kde bydl\u00ed, je v re\u017eimu GDPR?<\/strong><\/p>\n\n\n\n

Mus\u00edme si uv\u011bdomit, \u017ee osobn\u00ed \u00fadaje jsou informace, kter\u00e9 nemus\u00ed obsahovat p\u0159\u00edm\u00e9 identifika\u010dn\u00ed \u00fadaje, tedy b\u00fdt \u201eo osob\u011b\u201c. Z\u00e1le\u017e\u00ed i na \u00fa\u010delu \u00fadaj\u016f a n\u00e1sledn\u00e9m zp\u016fsobu jejich pou\u017eit\u00ed.<\/p>\n\n\n\n

Osobn\u00edmi \u00fadaji jsou obecn\u011b informace, kter\u00e9 se t\u00fdkaj\u00ed n\u011bjak\u00e9 osoby:<\/p>\n\n\n\n

    \n
  1. sv\u00fdm obsahem <\/strong>(jsou o dan\u00e9 osob\u011b),<\/li>\n\n\n\n
  2. sv\u00fdm \u00fa\u010delem <\/strong>(samy o sob\u011b nemus\u00ed obsahovat identifika\u010dn\u00ed informace o dan\u00e9 osob\u011b, ale jsou z\u00edsk\u00e1v\u00e1ny pro jej\u00ed pozd\u011bj\u0161\u00ed identifikaci, nap\u0159. z\u00e1znamy z kamer),<\/li>\n\n\n\n
  3. sv\u00fdm d\u016fsledkem <\/strong>(i kdy\u017e z nich sam\u00fdch je t\u011b\u017ek\u00e9 n\u011bkoho identifikovat, daj\u00ed se pou\u017e\u00edt s dopadem na pr\u00e1va a z\u00e1jmy konkr\u00e9tn\u00ed osoby, nap\u0159. ovlivn\u011bn\u00ed jej\u00edho chov\u00e1n\u00ed na internetu prost\u0159ednictv\u00edm personalizovan\u00e9 reklamy).<\/li>\n<\/ol>\n\n\n\n

    Co je anonymizace?<\/strong><\/h2>\n\n\n\n

    Pokud m\u00e1te jak\u00e9koli osobn\u00ed \u00fadaje ve sv\u00fdch syst\u00e9mech, podl\u00e9h\u00e1te GDPR. To znamen\u00e1 o\u0161et\u0159en\u00ed cel\u00e9ho datov\u00e9ho toku, p\u0159\u00edpravu povinn\u00e9 dokumentace, smluv s dodavateli slu\u017eeb, bezpe\u010dnostn\u00edch opat\u0159en\u00ed, proces\u016f pro vy\u0159izov\u00e1n\u00ed GDPR \u017e\u00e1dost\u00ed z\u00e1kazn\u00edk\u016f, hl\u00e1\u0161en\u00ed bezpe\u010dnostn\u00edch incident\u016f a p\u00e1r dal\u0161\u00edch v\u011bc\u00ed.<\/p>\n\n\n\n

    Chcete-li sv\u00e9 datasety vyu\u017e\u00edt k tr\u00e9nov\u00e1n\u00ed algoritm\u016f a nechcete proj\u00edt celou torturou nebo nev\u00edte, jak to podle GDPR d\u011blat, je t\u0159eba upravit datab\u00e1zi.<\/p>\n\n\n\n

    Prvn\u00ed ot\u00e1zka zn\u00ed: co kdy\u017e \u00fadaje odd\u011bl\u00edm tak, \u017ee z\u016fstane skupina, z n\u00ed\u017e nelze nic vyvodit, a zbytek ulo\u017e\u00edm odd\u011blen\u011b? Nebo identifika\u010dn\u00ed \u00fadaje nahrad\u00edm k\u00f3dem, kter\u00fd budu zn\u00e1t jen j\u00e1? Tento proces se naz\u00fdv\u00e1 pseudonymizace <\/strong>a podle GDPR je to jedno z bezpe\u010dnostn\u00edch opat\u0159en\u00ed ke zv\u00fd\u0161en\u00ed ochrany. Pokud ale druhou skupinu \u00fadaj\u016f uchov\u00e1v\u00e1te a m\u016f\u017eete ji kdykoli p\u0159i\u0159adit k prvn\u00ed, st\u00e1le jste v re\u017eimu GDPR.<\/p>\n\n\n\n

    Jak se tedy z n\u011bj dostat?<\/p>\n\n\n\n

    Anonymizace <\/strong>je proces, kdy se osobn\u00ed \u00fadaje nezvratn\u011b uprav\u00ed tak, \u017ee zp\u011btn\u011b z nich nen\u00ed mo\u017en\u00e9 identifikovat \u017e\u00e1dnou osobu. Ani nep\u0159\u00edmo.<\/p>\n\n\n\n

    Nezvratn\u011b v\u0161ak neznamen\u00e1, \u017ee je to \u00fapln\u011b nemo\u017en\u00e9. Ale kde je hranice, kdy podle GDPR jsou data anonymizov\u00e1na a kdy ne?<\/p>\n\n\n\n

    GDPR to vid\u00ed prakticky<\/strong><\/h2>\n\n\n\n

    Pr\u00e1vo m\u00e1 slou\u017eit lidem, proto by nem\u011blo b\u00fdt absurdn\u00ed. Stejn\u011b je tomu i zde.<\/p>\n\n\n\n

    GDPR vy\u017eaduje p\u0159ijet\u00ed p\u0159im\u011b\u0159en\u00fdch opat\u0159en\u00ed k zaji\u0161t\u011bn\u00ed anonymizace, aby \u017e\u00e1dn\u00e1 osoba nemohla b\u00fdt z dat identifikov\u00e1na nebo po p\u0159id\u00e1n\u00ed dal\u0161\u00edch dat.<\/strong><\/p>\n\n\n\n

    P\u0159i volb\u011b p\u0159im\u011b\u0159en\u00fdch opat\u0159en\u00ed je t\u0159eba zohlednit v\u0161echny zp\u016fsoby, kter\u00e9 by bylo pravd\u011bpodobn\u011b mo\u017en\u00e9 pou\u017e\u00edt k deanonymizaci.<\/p>\n\n\n\n

    P\u0159i posouzen\u00ed, zda je mo\u017en\u00e9 je pravd\u011bpodobn\u011b pou\u017e\u00edt, je d\u016fle\u017eit\u00e9 zohlednit:<\/p>\n\n\n\n

      \n
    • n\u00e1klady<\/strong>, kter\u00e9 by deanonymizace vy\u017eadovala,<\/li>\n\n\n\n
    • \u010das <\/strong>pot\u0159ebn\u00fd k deanonymizaci,<\/li>\n\n\n\n
    • aktu\u00e1ln\u00ed technologie<\/strong>, kter\u00e9 by \u0161lo pou\u017e\u00edt,<\/li>\n\n\n\n
    • potenci\u00e1ln\u00ed technologick\u00fd v\u00fdvoj<\/strong> v bl\u00edzk\u00e9 budoucnosti,<\/li>\n\n\n\n
    • ve\u0159ejn\u011b dostupn\u00e1 data<\/strong>, kter\u00e1 by \u0161la k dat\u016fm p\u0159ipojit,<\/li>\n\n\n\n
    • unikl\u00e1 data<\/strong>, nap\u0159. na dark webu,<\/li>\n\n\n\n
    • citlivost <\/strong>anonymizovan\u00fdch dat <\/strong>nebo osob, kter\u00fdch se data t\u00fdkala, a motivaci <\/strong>ciz\u00edch osob je deanonymizovat<\/strong>.<\/li>\n<\/ul>\n\n\n\n

      Je proto vhodn\u00e9 ud\u011blat anal\u00fdzu rizik deanonymizace podle v\u00fd\u0161e uveden\u00fdch kategori\u00ed. Pokud vyjde, \u017ee data by teoreticky mohla b\u00fdt deanonymizov\u00e1na, ale st\u00e1lo by to tolik \u010dasu, pen\u011bz a nep\u0159im\u011b\u0159en\u00e9ho \u00fasil\u00ed, a nemysl\u00edte si, \u017ee by o to n\u011bkdo m\u011bl z\u00e1jem, m\u016f\u017eete je pova\u017eovat za anonymizovan\u00e1.<\/p>\n\n\n\n

      Sta\u010d\u00ed tedy z\u00edskat nebo vytvo\u0159it dataset, kter\u00fd s p\u0159im\u011b\u0159enou pravd\u011bpodobnost\u00ed nen\u00ed mo\u017en\u00e9 deanonymizovat. Tedy ne \u00fapln\u011b nemo\u017en\u00e9. A m\u016f\u017eete za\u010d\u00edt tr\u00e9novat sv\u00e9 algoritmy.<\/p>\n\n\n\n

      Nejlep\u0161\u00ed anonymiza\u010dn\u00ed techniky<\/strong><\/h2>\n\n\n\n

      GDPR i v\u011bt\u0161ina podobn\u00fdch p\u0159edpis\u016f EU obsahuje tzv. performativn\u00ed pravidla<\/strong>. Ta ur\u010duj\u00ed, jak\u00fd v\u00fdsledek m\u00e1te dos\u00e1hnout, ale ne\u0159\u00edkaj\u00ed, jak toho dos\u00e1hnout.<\/p>\n\n\n\n

      Poj\u010fme si zm\u00ednit alespo\u0148 n\u011bkter\u00e9 z doporu\u010den\u00fdch technik. \u017d\u00e1dn\u00e1 z nich sama o sob\u011b nen\u00ed dostate\u010dnou z\u00e1rukou anonymizace, proto je vhodn\u00e9 je kombinovat, p\u0159\u00edpadn\u011b pou\u017e\u00edt je co nejv\u00edce.<\/p>\n\n\n\n

      Samoz\u0159ejm\u011b, konkr\u00e9tn\u00ed typ zvolen\u00e9 techniky v\u017edy z\u00e1le\u017e\u00ed na tom, co s anonymizovan\u00fdmi daty pot\u0159ebujeme d\u011blat.<\/p>\n\n\n\n

      Maskov\u00e1n\u00ed<\/strong><\/h3>\n\n\n\n

      Maskov\u00e1n\u00ed je jednoduch\u00e1 technika, kter\u00e1 je sp\u00ed\u0161e dopl\u0148kem ostatn\u00edch efektivn\u011bj\u0161\u00edch metod a m\u011bla by b\u00fdt jejich nezbytnou sou\u010d\u00e1st\u00ed. Spo\u010d\u00edv\u00e1 v odebr\u00e1n\u00ed zjevn\u00fdch identifik\u00e1tor\u016f z datab\u00e1ze, jako jsou jm\u00e9na, p\u0159\u00edjmen\u00ed, bydli\u0161t\u011b atd. Sama o sob\u011b v\u0161ak nep\u0159edstavuje anonymizaci, proto\u017ee ve v\u011bt\u0161in\u011b p\u0159\u00edpad\u016f mohou zb\u00fdvaj\u00edc\u00ed identifik\u00e1tory pohodln\u011b sta\u010dit k identifikaci konkr\u00e9tn\u00edch osob.<\/p>\n\n\n\n

      Kdy\u017e u\u017e m\u00e1me v prvn\u00edm kroku maskovan\u00e1 data, m\u016f\u017eeme pokra\u010dovat d\u00e1le.<\/p>\n\n\n\n

      Randomizace<\/strong><\/h3>\n\n\n\n

      Randomizace <\/strong>p\u0159edstavuje techniku anonymizace, v r\u00e1mci kter\u00e9 se data uprav\u00ed tak, \u017ee se t\u00edm p\u0159eru\u0161\u00ed propojen\u00ed mezi osobou a daty, ani\u017e by se sn\u00ed\u017eila hodnota dat.<\/p>\n\n\n\n

      Tato \u00faprava m\u016f\u017ee zahrnovat dopln\u011bn\u00ed n\u00e1hodn\u00fdch dat (tzv. noise addition) nebo drobn\u00e9 n\u00e1hodn\u00e9 zm\u011bny tak, aby se propojen\u00ed mezi osobou a jej\u00edmi daty p\u0159eru\u0161ilo.<\/p>\n\n\n\n

      P\u0159\u00edklad:<\/strong> Pokud m\u00e1me dataset osob s ur\u010ditou v\u00fd\u0161kou, m\u016f\u017eeme ke ka\u017ed\u00e9mu doplnit nebo odebrat p\u00e1r centimetr\u016f z v\u00fd\u0161ky. Ve v\u00fdsledku pom\u011br v\u00fd\u0161ky jednoho k druh\u00e9mu z\u016fstane zachov\u00e1n, ale nelze u\u017e naj\u00edt mezi nimi osobu s ur\u010ditou v\u00fd\u0161kou, proto\u017ee tato ji\u017e bude pat\u0159it n\u011bkomu jin\u00e9mu nebo se v datab\u00e1zi v\u016fbec nenach\u00e1z\u00ed.<\/p>\n\n\n\n

      Tip:<\/strong> K nahrazen\u00ed skute\u010dn\u00fdch dat fiktivn\u00edmi m\u016f\u017eete pou\u017e\u00edt nap\u0159\u00edklad Python knihovnu pro generov\u00e1n\u00ed fale\u0161n\u00fdch \u00fadaj\u016f, tedy n\u00e1stroj pou\u017e\u00edvan\u00fd speci\u00e1ln\u011b pro anonymizaci dataset\u016f.<\/p>\n\n\n\n

      Samostatn\u00fdm podtypem randomizace je permutace<\/strong>, kdy skute\u010dn\u00e9 \u00fadaje pat\u0159\u00edc\u00ed ur\u010dit\u00fdm osob\u00e1m \u201eposouv\u00e1me\u201c mezi nimi tak, \u017ee se ztrat\u00ed spojen\u00ed mezi osobou a skute\u010dn\u00fdm \u00fadajem.<\/p>\n\n\n\n

      P\u0159\u00edklad:<\/strong> Pokud m\u00e1me stejn\u00fd dataset osob s ur\u010ditou v\u00fd\u0161kou, tyto v\u00fd\u0161ky jen prom\u00edch\u00e1me tak, aby ur\u010dit\u00e1 osoba A s v\u00fd\u0161kou 167 cm byla po permutaci osobou A s v\u00fd\u0161kou 185 cm. Tak m\u016f\u017eeme pracovat se skute\u010dn\u00fdmi daty o v\u00fdskytu ur\u010dit\u00e9 v\u00fd\u0161ky, ale ztrat\u00ed se propojen\u00ed s p\u016fvodn\u00ed osobou.<\/p>\n\n\n\n

      Generalizace<\/strong><\/h3>\n\n\n\n

      Tato technika zahrnuje redukci p\u0159esn\u00fdch dat, pokud nejsou pot\u0159ebn\u00e1. V z\u00e1sad\u011b se odebere konkr\u00e9tn\u00ed hodnota a dan\u00fd subjekt nebo informace se za\u0159ad\u00ed do ur\u010dit\u00e9 skupiny. T\u00edmto zp\u016fsobem bude ur\u010dit\u00fd atribut sd\u00edlen s v\u00edce lidmi v dan\u00e9 skupin\u011b.<\/p>\n\n\n\n

      P\u0159\u00edklad:<\/strong> Pokud pracujeme s datab\u00e1z\u00ed lid\u00ed, kte\u0159\u00ed maj\u00ed ur\u010dit\u00fd v\u011bk, v\u00fd\u0161ku a p\u016fvod ur\u010den\u00fd m\u011bstem, m\u016f\u017eeme z nich vytvo\u0159it skupiny od \u2013 do, tedy rozd\u011blen\u00ed lid\u00ed:
      \u2013 podle v\u011bku, nap\u0159. 16\u201325, 26\u201335, 36\u201345 atd.;
      \u2013 spolu se skupinou podle v\u00fd\u0161ky, nap\u0159. 166\u2013175 cm, 176\u2013185 cm, 186\u2013195 cm atd.;
      \u2013 s lokalizac\u00ed podle okresu, kraje nebo jin\u00e9 geografick\u00e9 oblasti m\u00edsto konkr\u00e9tn\u00edho m\u011bsta.<\/p>\n\n\n\n

      I v tomto p\u0159\u00edpad\u011b je t\u0159eba b\u00fdt opatrn\u00fd. Pokud m\u00e1me osobu s nezvyklou v\u00fd\u0161kou, nap\u0159. 205 cm, nebo v\u00e1hou, \u0159ekn\u011bme 185 kg v ur\u010dit\u00e9m m\u011bst\u011b, a m\u011bsto nahrad\u00edme okresem nebo krajem, st\u00e1le je vysok\u00e1 pravd\u011bpodobnost jej\u00ed identifikovatelnosti, hlavn\u011b pokud ani ve v\u011bt\u0161\u00edm geografick\u00e9m prostoru nen\u00ed v\u00edce osob s takto nadpr\u016fm\u011brnou v\u00fd\u0161kou.<\/p>\n\n\n\n

      Vyu\u017eit\u00ed pravd\u011bpodobnosti<\/strong><\/h3>\n\n\n\n

      Pokud pracujete s dokumenty s osobn\u00edmi \u00fadaji, kter\u00e9 vytv\u00e1\u0159ej\u00ed u\u017eivatel\u00e9 nap\u0159\u00edklad i ve va\u0161\u00ed aplikaci, a chcete je anonymizovat, m\u016f\u017eete vypo\u010d\u00edtat pravd\u011bpodobnost, s jakou se n\u011bkter\u00e9 sekce nebo ur\u010dit\u00fd obsah v dokumentech opakuj\u00ed. Tak\u00e9 pravd\u011bpodobnost, jak \u010dasto se opakuj\u00ed ur\u010dit\u00e9 chyby nebo chybn\u00e9 vzorce p\u0159i jejich tvorb\u011b. A tyto n\u00e1sledn\u011b vyu\u017e\u00edt p\u0159i tvorb\u011b upraven\u00fdch (anonymizovan\u00fdch) dokument\u016f.<\/p>\n\n\n\n

      Pokud nav\u00edc zamaskujete kontaktn\u00ed \u00fadaje fale\u0161n\u00fdmi (viz Python knihovnu v\u00fd\u0161e), p\u0159\u00edpadn\u011b nahrad\u00edte i dal\u0161\u00ed \u00fadaje t\u00edmto zp\u016fsobem, jste na nejlep\u0161\u00ed cest\u011b k anonymizovan\u00fdm \u00fadaj\u016fm.<\/p>\n\n\n\n

      Pamatujte, \u017ee \u017e\u00e1dn\u00e1 anonymiza\u010dn\u00ed technika nen\u00ed 100\u202f% spolehliv\u00e1<\/strong>. To v\u0161ak ani nepot\u0159ebujete. Nezapome\u0148te zohlednit v\u00fd\u0161e uveden\u00e1 krit\u00e9ria a pokud zjist\u00edte, \u017ee v\u00e1mi pou\u017eit\u00e9 techniky jsou jen s velk\u00fdmi n\u00e1klady prolomiteln\u00e9, je velk\u00e1 \u0161ance, \u017ee jste mimo GDPR.<\/p>\n\n\n\n

      Nezapome\u0148te respektovat soukrom\u00ed ostatn\u00edch stejn\u011b, jako vy o\u010dek\u00e1v\u00e1te respekt k tomu sv\u00e9mu.<\/p>\n\n\n\n

      Tento obsah m\u00e1 pouze informa\u010dn\u00ed charakter.<\/em><\/p>\n","protected":false},"excerpt":{"rendered":"

      M\u00e1te skv\u011blou aplikaci, kter\u00e1 u\u017e m\u00e1 sv\u00e9 z\u00e1kazn\u00edky a pot\u0159ebujete inovovat? Asi v\u00edte, \u017ee pokud pou\u017eijete pro tr\u00e9nink AI nebo jin\u00fdch algoritm\u016f osobn\u00ed \u00fadaje, automaticky se na v\u00e1s sesype spr\u0161ka povinnost\u00ed podle GDPR. O rizic\u00edch ani nemluv\u011b. Tr\u00e9nov\u00e1n\u00ed na synteticky vytvo\u0159en\u00fdch datech zase nemus\u00ed p\u0159in\u00e9st v\u00fdsledky, kter\u00e9 pot\u0159ebujete. Jak to tedy ud\u011blat? To tajemstv\u00ed se […]<\/p>\n","protected":false},"author":48,"featured_media":5720,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[575,4],"tags":[930,20,959,19],"class_list":["post-5702","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-bezpecnost","category-technologie","tag-ai","tag-bezpecnost","tag-gdpr","tag-websupport"],"yoast_head":"\nN\u00e1vod: Jak tr\u00e9novat va\u0161e algoritmy a neporu\u0161it p\u0159i tom do GDPR? - Websupport.cz Blog<\/title>\n<meta name=\"description\" content=\"P\u0159ehled technik anonymizace dat podle GDPR a jejich praktick\u00e9 vyu\u017eit\u00ed p\u0159i tr\u00e9nov\u00e1n\u00ed algoritm\u016f bez rizika poru\u0161en\u00ed pravidel ochrany osobn\u00edch \u00fadaj\u016f.\" \/>\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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