{"id":381,"date":"2022-08-28T16:48:36","date_gmt":"2022-08-28T16:48:36","guid":{"rendered":"https:\/\/optimus.qsandbox.com:3443\/app_user\/qsu6361\/site\/ayushstha143-magazinex-demo.sites.qsandbox.com\/?p=381"},"modified":"2026-04-26T14:53:27","modified_gmt":"2026-04-26T14:53:27","slug":"premier-league-fa-cup-reaction","status":"publish","type":"post","link":"https:\/\/thepotentialtoday.com\/?p=381","title":{"rendered":"Ghost AI, Beyaz Yakada Liyakat A\u00e7\u0131\u011f\u0131n\u0131 B\u00fcy\u00fct\u00fcyor"},"content":{"rendered":"\n

TPT olarak yapay zekan\u0131n kurumlarda kullan\u0131m\u0131 ile istihdam performans ili\u015fkisini analiz etti\u011fimiz sinyallerden biri olan bu bu sinyal bize \u015funu s\u00f6yl\u00fcyor; emek piyasas\u0131nda AI eri\u015fimi e\u015fit da\u011f\u0131lmad\u0131\u011f\u0131 i\u00e7in, \u0130K’n\u0131n performans de\u011ferlendirme sistemleri art\u0131k yaln\u0131zca eme\u011fi de\u011fil, g\u00f6r\u00fcnmez ara\u00e7 avantaj\u0131n\u0131 da \u00f6l\u00e7\u00fcyor olabilir.<\/em><\/p>\n\n\n\n

Rahatlat\u0131c\u0131 hik\u00e2yenin sonu<\/h2>\n\n\n\n

Kurumsal d\u00fcnyada uzun s\u00fcre rahatlat\u0131c\u0131 bir hik\u00e2ye anlat\u0131ld\u0131; yapay zeka gelir, i\u015fleri h\u0131zland\u0131r\u0131r, verimlili\u011fi art\u0131r\u0131r ve herkes biraz daha g\u00fc\u00e7l\u00fc hale gelir. Ancak sahadaki ger\u00e7ek bu hik\u00e2yeyle \u00f6rt\u00fc\u015fm\u00fcyor. Yapay zeka i\u015fte kullan\u0131l\u0131yor, evet; ama e\u015fit kullan\u0131lm\u0131yor. Daha y\u00fcksek gelirli, daha e\u011fitimli ve tam zamanl\u0131 \u00e7al\u0131\u015fanlar yapay zekaya daha h\u0131zl\u0131 eri\u015fiyor; kurumsal e\u011fitim ise bu h\u0131z\u0131n belirgin \u015fekilde gerisinde kal\u0131yor.<\/p>\n\n\n\n

New York Fed’e dayanan ara\u015ft\u0131rma notlar\u0131 tabloyu somutla\u015ft\u0131r\u0131yor. \u00c7al\u0131\u015fanlar\u0131n %39’u son 12 ayda i\u015fte yapay zeka kullanm\u0131\u015f ancak bu oran d\u00fc\u015f\u00fck gelir grubunda %15,9’a inerken y\u00fcksek gelir grubunda %66,3’e \u00e7\u0131k\u0131yor. \u0130\u015fverenin yapay zeka e\u011fitimi sundu\u011funu s\u00f6yleyenlerin oran\u0131 ise yaln\u0131zca %15,9.\u00b9 Bu rakamlar, yapay zekan\u0131n e\u015fitleyici bir g\u00fc\u00e7 olmaktan \u00e7ok avantajl\u0131 bilgi \u00e7al\u0131\u015fanlar\u0131n\u0131 h\u0131zland\u0131ran bir kald\u0131ra\u00e7 olarak \u00e7al\u0131\u015ft\u0131\u011f\u0131n\u0131 d\u00fc\u015f\u00fcnd\u00fcr\u00fcyor.<\/p>\n\n\n\n

Peki bu e\u015fitsiz eri\u015fim nereye s\u0131z\u0131yor? Emek piyasas\u0131ndaki bu yeni fark, beyaz yakal\u0131 performans\u0131na, oradan da insan kaynaklar\u0131n\u0131n de\u011ferlendirme sistemlerine sessizce kar\u0131\u015f\u0131yor. Ve tam bu noktada ortaya yeni diyebilece\u011fimiz bir kavram \u00e7\u0131k\u0131yor: Ghost Merit Gap.<\/p>\n\n\n\n

Ayn\u0131 rol, farkl\u0131 altyap\u0131<\/h2>\n\n\n\n

Bu a\u00e7\u0131\u011f\u0131n olu\u015fma mekanizmas\u0131 asl\u0131nda basit. Ayn\u0131 rolde \u00e7al\u0131\u015fan iki ki\u015fi d\u00fc\u015f\u00fcnelim. Biri ki\u015fisel yapay zeka ara\u00e7lar\u0131yla ara\u015ft\u0131rmay\u0131 k\u0131salt\u0131yor, yaz\u0131y\u0131 parlat\u0131yor, toplant\u0131 \u00f6zetini \u00e7\u0131kar\u0131yor, sunumu h\u0131zland\u0131r\u0131yor. Di\u011feri ayn\u0131 i\u015fi daha \u00e7ok manuel y\u00fcr\u00fct\u00fcyor. Y\u00f6netici \u00e7o\u011fu zaman yaln\u0131zca sonucu g\u00f6r\u00fcyor; biri daha h\u0131zl\u0131, daha cilal\u0131, daha \u00fcretken. Ancak g\u00f6r\u00fcnen performans fark\u0131n\u0131n ne kadar\u0131 ger\u00e7ekten yetenek, ne kadar\u0131 ara\u00e7 eri\u015fimi, ne kadar\u0131 da g\u00f6r\u00fcnmez yapay zeka kullan\u0131m\u0131 bunu sistematik bi\u00e7imde ay\u0131ran \u015firket say\u0131s\u0131 \u00e7ok az.<\/p>\n\n\n\n

\u00dcstelik bu kullan\u0131m \u00e7o\u011funlukla g\u00f6r\u00fcn\u00fcr de\u011fil. BCG’nin APAC verisinde \u00e7al\u0131\u015fanlar\u0131n %58’i, \u015firket resmen sa\u011flamasa bile yapay zeka kullanaca\u011f\u0131n\u0131 s\u00f6yl\u00fcyor.\u00b2 Microsoft’un 2024 Work Trend verisinde ise yapay zeka kullananlar\u0131n %78’i kendi arac\u0131n\u0131 i\u015fe getirmi\u015f, %52’si de yapay zekay\u0131 en \u00f6nemli i\u015flerinde kulland\u0131\u011f\u0131n\u0131 s\u00f6ylemeye isteksiz.\u00b3 Yani kurum rollout yapt\u0131\u011f\u0131nda herkese e\u015fit imk\u00e2n sunulmu\u015f olmuyor; bireysel giri\u015fkenlik, stat\u00fc ve ara\u00e7 eri\u015fimi \u00f6nden gidiyor, \u015firket sonucu sonradan fark ediyor.<\/p>\n\n\n\n

Yapay zekan\u0131n bu \u015fekilde g\u00f6lgede kalmas\u0131, yaln\u0131zca bir \u015feffafl\u0131k sorunu olarak kalsayd\u0131 belki y\u00f6netilebilirdi. Ne var ki bu g\u00f6r\u00fcnmezlik, performans sistemlerinin temel varsay\u0131m\u0131n\u0131 \u00e7\u00fcr\u00fctmeye ba\u015fl\u0131yor.<\/p>\n\n\n\n

Meritokrasinin k\u00f6r noktas\u0131<\/h2>\n\n\n\n

Emek piyasas\u0131 a\u00e7\u0131s\u0131ndan bunun anlam\u0131 \u015fu; beyaz yakal\u0131 i\u015flerde performans art\u0131k yaln\u0131zca bilgi, disiplin ve deneyimle a\u00e7\u0131klanamayabilir. Bunlara bir de yapay zeka eri\u015fimi, yapay zeka okuryazarl\u0131\u011f\u0131 ve yapay zeka kullanma cesareti ekleniyor. Bu \u00fc\u00e7\u00fc e\u015fit da\u011f\u0131lmad\u0131\u011f\u0131nda, \u015firketler asl\u0131nda ayn\u0131 ba\u015flang\u0131\u00e7 \u00e7izgisine sahip olmayan \u00e7al\u0131\u015fanlar\u0131 tek bir merit sistemi i\u00e7inde k\u0131yasl\u0131yor. D\u0131\u015far\u0131dan bak\u0131nca ayn\u0131 KPI, ayn\u0131 rol, ayn\u0131 de\u011ferlendirme \u00e7er\u00e7evesi var gibi g\u00f6r\u00fcn\u00fcyor; i\u00e7eride ise oyunun zemini kaym\u0131\u015f durumda.<\/p>\n\n\n\n

Bu kayman\u0131n beyaz yakal\u0131 d\u00fcnyada \u00f6zellikle kritik olmas\u0131n\u0131n bir sebebi var; yapay zekan\u0131n en erken ve en etkili dokundu\u011fu alanlar bilgi yo\u011fun i\u015fler. Yaz\u0131, analiz, \u00f6zetleme, ara\u015ft\u0131rma, sunum, raporlama vb. yapay zeka \u00f6nce fiziksel \u00fcretim hatt\u0131na de\u011fil, bili\u015fsel \u00fcretim hatt\u0131na girdi. Bu y\u00fczden fark ilk olarak beyaz yaka i\u00e7inde hissediliyor. D\u00fc\u015f\u00fck gelirli \u00e7al\u0131\u015fanlar ve sahadaki \u00e7al\u0131\u015fanlar i\u00e7in eri\u015fim s\u0131n\u0131rl\u0131 kald\u0131\u011f\u0131nda, beyaz yakalar\u0131n bir k\u0131sm\u0131 “normalden h\u0131zl\u0131” de\u011fil, “yeni bir altyap\u0131yla \u00e7al\u0131\u015fan” bir gruba d\u00f6n\u00fc\u015f\u00fcyor. Klasik performans sistemi ise bu fark\u0131 \u00e7o\u011fu zaman do\u011fal yetenek fark\u0131 san\u0131yor.<\/p>\n\n\n\n

\u0130nsan kaynaklar\u0131 a\u00e7\u0131s\u0131ndan en b\u00fcy\u00fck problem tam burada ba\u015fl\u0131yor. Performans sistemleri tarihsel olarak \u00e7\u0131kt\u0131y\u0131, davran\u0131\u015f\u0131 ve hedef ger\u00e7ekle\u015fmesini \u00f6l\u00e7mek \u00fczere tasarland\u0131. Ancak Ghost AI \u00e7a\u011f\u0131nda art\u0131k sorulmas\u0131 gereken sorular farkl\u0131la\u015ft\u0131. Bu \u00e7\u0131kt\u0131 hangi i\u015f ad\u0131m\u0131nda yapay zekayla desteklendi? Son do\u011frulamay\u0131 kim yapt\u0131? \u00c7al\u0131\u015fan ayn\u0131 kaliteye s\u00fcre uzasa da yapay zeka olmadan da ula\u015fabiliyor mu? Y\u00f6neticinin “y\u00fcksek performans” diye okudu\u011fu \u015fey ger\u00e7ekten muhakeme mi, yoksa daha iyi ara\u00e7 kullan\u0131m\u0131 m\u0131?<\/p>\n\n\n\n

Bu sorular sorulmad\u0131\u011f\u0131nda meritokrasi bozuluyor ama d\u0131\u015far\u0131dan bozulmu\u015f gibi g\u00f6r\u00fcnm\u00fcyor. En riskli durum da bu; sistem adil g\u00f6r\u00fcn\u00fcrken adaletsizlik \u00fcretiyor. Analiz ara\u00e7lar\u0131m\u0131zdan Context Interpreter projeksiyonundaki te\u015fhis de bunu do\u011fruluyor; \u015firket performans\u0131, insan katk\u0131s\u0131n\u0131 de\u011fil yapay zeka eri\u015fimini ve gizli ara\u00e7 kullan\u0131m\u0131n\u0131 \u00f6d\u00fcllendirmeye ba\u015flarsa, performans sistemi meritokrasi gibi g\u00f6r\u00fcn\u00fcrken e\u015fitsizlik \u00fcretir.\u2074<\/p>\n\n\n\n

\u00dcst \u00fcste binen \u00fc\u00e7 k\u0131r\u0131lma<\/h2>\n\n\n\n

Bu yap\u0131sal \u00e7atlak tek bir sonu\u00e7 do\u011furmuyor; birbirine ba\u011fl\u0131 \u00fc\u00e7 k\u0131r\u0131lma yarat\u0131yor ve her biri di\u011ferini besliyor.<\/p>\n\n\n\n

\u0130lk k\u0131r\u0131lma \u00fccret ve terfi alan\u0131nda. PwC’nin 2025 AI Jobs Barometer’\u0131na g\u00f6re yapay zeka becerili \u00e7al\u0131\u015fanlar i\u00e7in ortalama %56 \u00fccret primi raporlan\u0131yor.\u2075 Bu veri tek ba\u015f\u0131na her terfi yapay zeka y\u00fcz\u00fcnden demek de\u011fil; ancak emek piyasas\u0131n\u0131n yapay zeka destekli beceriyi ekonomik olarak \u00f6d\u00fcllendirmeye ba\u015flad\u0131\u011f\u0131n\u0131 g\u00f6steriyor. G\u00f6r\u00fcnmez yapay zeka kullan\u0131m\u0131n\u0131n performans notlar\u0131na ve terfilere kar\u0131\u015ft\u0131\u011f\u0131 bir ortamda, beyaz yakal\u0131 \u00fccret farklar\u0131 daha da b\u00fcy\u00fcyebilir.<\/p>\n\n\n\n

\u0130kinci k\u0131r\u0131lma \u00f6\u011frenme zincirinde. Junior bir \u00e7al\u0131\u015fan yapay zeka yard\u0131m\u0131yla \u00e7ok iyi g\u00f6r\u00fcnen bir \u00e7\u0131kt\u0131 \u00fcretebilir; ancak o \u00e7\u0131kt\u0131n\u0131n arkas\u0131ndaki analiz, muhakeme ve problem \u00e7\u00f6zme kas\u0131 ayn\u0131 h\u0131zla geli\u015fmeyebilir. K\u0131sa vadede y\u00f6neticinin g\u00f6z\u00fcne y\u00fcksek performans gibi g\u00f6r\u00fcnen \u015fey, orta vadede ustala\u015fma a\u00e7\u0131\u011f\u0131na d\u00f6n\u00fc\u015febilir. \u015eirket h\u0131z kazan\u0131rken \u00e7\u0131rakl\u0131k kaybedebilir.<\/p>\n\n\n\n

\u00dc\u00e7\u00fcnc\u00fc k\u0131r\u0131lma ise hukuki ve y\u00f6neti\u015fim cephesinde. AB AI Act kapsam\u0131nda istihdam, terfi, g\u00f6rev da\u011f\u0131l\u0131m\u0131 ve performans de\u011ferlendirme ama\u00e7l\u0131 yapay zeka kullan\u0131mlar\u0131 y\u00fcksek riskli alanlar aras\u0131nda say\u0131l\u0131yor; yapay zeka okuryazarl\u0131\u011f\u0131na ili\u015fkin y\u00fck\u00fcml\u00fcl\u00fckler devreye giriyor.\u2076 ABD taraf\u0131nda da EEOC ve New York’taki bias audit \u00e7er\u00e7eveleri, performans kararlar\u0131nda yapay zeka kullan\u0131m\u0131n\u0131n yaln\u0131zca verimlilik de\u011fil, ayr\u0131mc\u0131l\u0131k ve a\u00e7\u0131klanabilirlik ba\u015fl\u0131\u011f\u0131 oldu\u011funu hat\u0131rlat\u0131yor.\u2077 \u0130nsan kaynaklar\u0131 i\u00e7in savunulamayan performans sistemi art\u0131k yaln\u0131zca k\u00f6t\u00fc tasar\u0131m de\u011fil, riskli bir altyap\u0131.<\/p>\n\n\n\n

Bu \u00fc\u00e7 k\u0131r\u0131lma birbirinden ba\u011f\u0131ms\u0131z de\u011fil. \u00dccret fark\u0131 a\u00e7\u0131ld\u0131k\u00e7a \u00f6\u011frenme zinciri daha da k\u0131r\u0131l\u0131yor, \u00f6\u011frenme zinciri k\u0131r\u0131ld\u0131k\u00e7a hukuki savunulabilirlik zay\u0131fl\u0131yor, hukuki bask\u0131 artt\u0131k\u00e7a sistemin me\u015fruiyet kayb\u0131 g\u00f6r\u00fcn\u00fcr hale geliyor. D\u00f6ng\u00fcy\u00fc k\u0131rmak i\u00e7in m\u00fcdahale noktas\u0131 a\u00e7\u0131k.<\/p>\n\n\n\n

Bast\u0131rmamal\u0131, g\u00f6r\u00fcn\u00fcr hale getirmeli<\/h2>\n\n\n\n

\u0130nsan kaynaklar\u0131n\u0131n g\u00f6revi yapay zekay\u0131 bast\u0131rmak de\u011fil, g\u00f6r\u00fcn\u00fcr k\u0131l\u0131p standardize etmek. Bunun ilk ad\u0131m\u0131 “yapay zeka kulland\u0131 m\u0131?” av\u0131na \u00e7\u0131kmak de\u011fil; performans de\u011ferlendirmesine bir a\u00e7\u0131kl\u0131k katman\u0131 eklemek. Yukar\u0131da da \u00f6rneklendi\u011fi gibi baz\u0131 i\u015f t\u00fcrlerinde \u015fu soru standart hale gelebilir; “Hangi i\u015f ad\u0131m\u0131 yapay zeka destekliydi, son do\u011frulamay\u0131 kim yapt\u0131?” Bu yakla\u015f\u0131m \u00e7al\u0131\u015fan\u0131 kriminalize etmez, y\u00f6neticinin \u00e7\u0131kt\u0131y\u0131 daha do\u011fru okumas\u0131n\u0131 sa\u011flar.<\/p>\n\n\n\n

\u0130kinci ad\u0131m, rol bazl\u0131 minimum yapay zeka eri\u015fimini e\u015fitlemek. Yapay zeka baz\u0131 \u00e7al\u0131\u015fanlar i\u00e7in gizli s\u00fcper g\u00fc\u00e7, di\u011ferleri i\u00e7in yasak b\u00f6lge olmamal\u0131. \u00dc\u00e7\u00fcnc\u00fc ad\u0131m ise de\u011ferlendirme \u00f6l\u00e7\u00fct\u00fcn\u00fc ham h\u0131zdan daha olgun bir yere ta\u015f\u0131mak; \u00e7\u0131kt\u0131 kalitesi, muhakeme, do\u011frulama disiplini ve \u015feffaf kullan\u0131m. Bunlar olmadan yaln\u0131zca \u00e7ok \u00e7\u0131kt\u0131 \u00f6d\u00fcllendirildi\u011finde, \u015firket en parlak \u00e7al\u0131\u015fan\u0131 de\u011fil, en iyi gizlenen ara\u00e7 avantaj\u0131n\u0131 \u00f6d\u00fcllendirme riskiyle kar\u015f\u0131 kar\u015f\u0131ya kal\u0131r.<\/p>\n\n\n\n

Yap\u0131sal a\u00e7\u0131k m\u0131, bireysel davran\u0131\u015f m\u0131?<\/h2>\n\n\n\n

Bu noktada izlenmesi gereken birka\u00e7 kritik g\u00f6sterge var. Ayn\u0131 rolde y\u00fcksek performans notlar\u0131 yapay zeka eri\u015fimi y\u00fcksek ekiplerde mi toplan\u0131yor? Y\u00f6neticiler performans fark\u0131n\u0131 “daha h\u0131zl\u0131” ve “daha cilal\u0131” d\u0131\u015f\u0131nda a\u00e7\u0131klayabiliyor mu? Terfi ya da bonus itirazlar\u0131nda sonradan ortaya \u00e7\u0131kan gizli yapay zeka kullan\u0131m \u00f6r\u00fcnt\u00fcleri art\u0131yor mu? D\u00fc\u015f\u00fck eri\u015fimli ekiplerde adalet alg\u0131s\u0131 bozuluyor mu? Bu sorulara “evet” yan\u0131t\u0131 \u00e7o\u011fal\u0131yorsa mesele bireysel davran\u0131\u015ftan \u00e7\u0131km\u0131\u015f, yap\u0131sal bir a\u00e7\u0131\u011fa d\u00f6n\u00fc\u015fm\u00fc\u015f demektir.<\/p>\n\n\n\n

\u00d6zetle tablo netle\u015fiyor; emek piyasas\u0131nda yapay zeka e\u015fitsiz da\u011f\u0131l\u0131yor, beyaz yakal\u0131 i\u015flerde bu e\u015fitsizlik verimlilik fark\u0131na d\u00f6n\u00fc\u015f\u00fcyor, insan kaynaklar\u0131 ise \u00e7o\u011fu zaman bu yeni fark\u0131 eski performans diliyle \u00f6l\u00e7meye \u00e7al\u0131\u015f\u0131yor. As\u0131l a\u00e7\u0131k tam burada olu\u015fuyor; piyasa \u00e7oktan de\u011fi\u015fti, performans sistemi hen\u00fcz de\u011fi\u015fmedi. \u015eirketlerin bundan sonra \u00f6\u011frenmesi gereken \u015fey y\u00fcksek performans\u0131 \u00f6d\u00fcllendirmek de\u011fil, g\u00f6r\u00fcnmez ara\u00e7 avantaj\u0131n\u0131 \u00f6d\u00fcllendirmemeyi \u00f6\u011frenmek.<\/p>\n\n\n\n

\n\n\n\n

Dipnotlar<\/h2>\n\n\n\n

\u00b9 Federal Reserve Bank of New York. AI and the Labor Market: Evidence from the SCE Labor Market Survey<\/em>. <\/p>\n\n\n\n

\u00b2 BCG. AI at Work: What People Are Really Doing with Gen AI<\/em> (APAC verisi). <\/p>\n\n\n\n

\u00b3 Microsoft. 2024 Work Trend Index Annual Report<\/em>. <\/p>\n\n\n\n

\u2074 Context Interpreter. Ghost AI Projeksiyonu: Y\u00f6netim, Operasyon, Finans ve HR Performans Mimarisi Etkileri<\/em>. <\/p>\n\n\n\n

\u2075 PwC. 2025 AI Jobs Barometer<\/em>. <\/p>\n\n\n\n

\u2076 Avrupa Birli\u011fi. Regulation (EU) 2024\/1689 \u2014 AI Act<\/em>.<\/p>\n\n\n\n

\u2077 U.S. Equal Employment Opportunity Commission (EEOC); New York City Department of Consumer and Worker Protection. .<\/p>\n\n\n\n

\n

<\/p>\n<\/div>\n\n\n\n

<\/p>\n","protected":false},"excerpt":{"rendered":"

Kurumsal d\u00fcnyada uzun s\u00fcre rahatlat\u0131c\u0131 bir hik\u00e2ye anlat\u0131ld\u0131: yapay zeka gelir, i\u015fleri h\u0131zland\u0131r\u0131r, verimlili\u011fi art\u0131r\u0131r ve herkes biraz daha g\u00fc\u00e7l\u00fc hale gelir. Ancak sahadaki ger\u00e7ek bu hik\u00e2yeyle \u00f6rt\u00fc\u015fm\u00fcyor. Yapay zeka i\u015fte kullan\u0131l\u0131yor, evet; ama e\u015fit kullan\u0131lm\u0131yor…<\/p>\n","protected":false},"author":1,"featured_media":610,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"colormag_page_container_layout":"default_layout","colormag_page_sidebar_layout":"default_layout","footnotes":""},"categories":[49],"tags":[],"class_list":["post-381","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-perspektif"],"magazineBlocksPostFeaturedMedia":{"thumbnail":"https:\/\/thepotentialtoday.com\/wp-content\/uploads\/2022\/08\/pink-piggy-bank-1-150x150.jpg","medium":"https:\/\/thepotentialtoday.com\/wp-content\/uploads\/2022\/08\/pink-piggy-bank-1-300x199.jpg","medium_large":"https:\/\/thepotentialtoday.com\/wp-content\/uploads\/2022\/08\/pink-piggy-bank-1.jpg","large":"https:\/\/thepotentialtoday.com\/wp-content\/uploads\/2022\/08\/pink-piggy-bank-1.jpg","1536x1536":"https:\/\/thepotentialtoday.com\/wp-content\/uploads\/2022\/08\/pink-piggy-bank-1.jpg","2048x2048":"https:\/\/thepotentialtoday.com\/wp-content\/uploads\/2022\/08\/pink-piggy-bank-1.jpg","colormag-highlighted-post":"https:\/\/thepotentialtoday.com\/wp-content\/uploads\/2022\/08\/pink-piggy-bank-1-392x272.jpg","colormag-featured-post-medium":"https:\/\/thepotentialtoday.com\/wp-content\/uploads\/2022\/08\/pink-piggy-bank-1-390x205.jpg","colormag-featured-post-small":"https:\/\/thepotentialtoday.com\/wp-content\/uploads\/2022\/08\/pink-piggy-bank-1-130x90.jpg","colormag-featured-image":"https:\/\/thepotentialtoday.com\/wp-content\/uploads\/2022\/08\/pink-piggy-bank-1.jpg","colormag-default-news":"https:\/\/thepotentialtoday.com\/wp-content\/uploads\/2022\/08\/pink-piggy-bank-1-150x150.jpg","colormag-featured-image-large":"https:\/\/thepotentialtoday.com\/wp-content\/uploads\/2022\/08\/pink-piggy-bank-1.jpg"},"magazineBlocksPostAuthor":{"name":"admin","avatar":"https:\/\/secure.gravatar.com\/avatar\/e0ab7dc85ea35ba8001cbfd85ce1f13ca897a9296c11d46f815cdc835f4a18ad?s=96&d=mm&r=g"},"magazineBlocksPostCommentsNumber":"0","magazineBlocksPostExcerpt":"Kurumsal d\u00fcnyada uzun s\u00fcre rahatlat\u0131c\u0131 bir hik\u00e2ye anlat\u0131ld\u0131: yapay zeka gelir, i\u015fleri h\u0131zland\u0131r\u0131r, verimlili\u011fi art\u0131r\u0131r ve herkes biraz daha g\u00fc\u00e7l\u00fc hale gelir. Ancak sahadaki ger\u00e7ek bu hik\u00e2yeyle \u00f6rt\u00fc\u015fm\u00fcyor. Yapay zeka i\u015fte kullan\u0131l\u0131yor, evet; ama e\u015fit kullan\u0131lm\u0131yor...","magazineBlocksPostCategories":["Perspektif"],"magazineBlocksPostViewCount":56,"magazineBlocksPostReadTime":9,"magazine_blocks_featured_image_url":{"full":["https:\/\/thepotentialtoday.com\/wp-content\/uploads\/2022\/08\/pink-piggy-bank-1.jpg",640,425,false],"medium":["https:\/\/thepotentialtoday.com\/wp-content\/uploads\/2022\/08\/pink-piggy-bank-1-300x199.jpg",300,199,true],"thumbnail":["https:\/\/thepotentialtoday.com\/wp-content\/uploads\/2022\/08\/pink-piggy-bank-1-150x150.jpg",150,150,true]},"magazine_blocks_author":{"display_name":"admin","author_link":"https:\/\/thepotentialtoday.com\/?author=1"},"magazine_blocks_comment":0,"magazine_blocks_author_image":"https:\/\/secure.gravatar.com\/avatar\/e0ab7dc85ea35ba8001cbfd85ce1f13ca897a9296c11d46f815cdc835f4a18ad?s=96&d=mm&r=g","magazine_blocks_category":"Perspektif<\/a>","_links":{"self":[{"href":"https:\/\/thepotentialtoday.com\/index.php?rest_route=\/wp\/v2\/posts\/381","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/thepotentialtoday.com\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/thepotentialtoday.com\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/thepotentialtoday.com\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/thepotentialtoday.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=381"}],"version-history":[{"count":2,"href":"https:\/\/thepotentialtoday.com\/index.php?rest_route=\/wp\/v2\/posts\/381\/revisions"}],"predecessor-version":[{"id":979,"href":"https:\/\/thepotentialtoday.com\/index.php?rest_route=\/wp\/v2\/posts\/381\/revisions\/979"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/thepotentialtoday.com\/index.php?rest_route=\/wp\/v2\/media\/610"}],"wp:attachment":[{"href":"https:\/\/thepotentialtoday.com\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=381"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/thepotentialtoday.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=381"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/thepotentialtoday.com\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=381"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}