{"status":true,"post":{"id":48108,"user_id":27,"status":1,"type":1,"orde":null,"notification_type":3,"static_post":0,"published_at":"2024-01-29 08:12:00","created_at":"2024-01-29T05:12:00.000000Z","updated_at":"2024-01-29T05:12:00.000000Z","edited_at":"2024-12-17 22:35:21","source_id":null,"post_id":48108,"is_featured":0,"title":"AI TRiSM: Yapay zeka g\u00fcven, risk ve g\u00fcvenlik y\u00f6netimi","slider_title":null,"slider_title_2":null,"slider_spot_title":null,"slider_spot_title_2":null,"home_title":null,"sub_title":null,"category_id":73,"description":"DO\u00c7. DR. ADNAN VEYSEL ERTEMEL","content":"


<\/span><\/strong><\/p>


<\/p>

adnan.ertemel@gmail.com<\/span><\/strong><\/p>

\u00a0<\/span><\/p>

Yapay zeka (YZ) sistemlerinin giderek artan kullan\u0131m\u0131, bu teknolojilerin g\u00fcvenilirli\u011fi, adaleti, dayan\u0131kl\u0131l\u0131\u011f\u0131, verimlili\u011fi ve veri korumas\u0131 gibi kavramlar\u0131n \u00f6ne \u00e7\u0131kmas\u0131na neden oldu. \u0130lgili kavramlar\u0131n ilk harflerinin birle\u015fiminden olu\u015fan ve k\u0131saca AI TRiSM (AI trust, risk and security management) olarak adland\u0131r\u0131lan bu kavram, yapay zeka modellerinin y\u00f6neti\u015fimini sa\u011flamak i\u00e7in olu\u015fturulan bir s\u00fcre\u00e7 ve metodoloji olarak tan\u0131mlanabilir. Bu yakla\u015f\u0131m, yapay zeka sistemlerinin g\u00fcvenilirli\u011fini art\u0131rma ve g\u00fcvenlik y\u00f6netimi konusunda \u00f6ncelikli bir strateji sunma amac\u0131n\u0131 ta\u015f\u0131r.<\/span><\/p>

\u00a0<\/span><\/p>

AI TRiSM, yapay zeka modellerinin y\u00f6neti\u015fimini sa\u011flayarak, bu modellerin g\u00fcvenilirli\u011fini art\u0131rmay\u0131 hedefler. Bu s\u00fcre\u00e7, yapay zeka modellerinin geli\u015ftirilme, test edilme, da\u011f\u0131t\u0131lma ve kullan\u0131lma a\u015famalar\u0131n\u0131 kapsar. G\u00fcvenilirlik, modelin do\u011frulu\u011fu, tutarl\u0131l\u0131\u011f\u0131 ve etkinli\u011fi \u00fczerinde odaklan\u0131rken, ayn\u0131 zamanda modelin adil olmas\u0131, veri korumas\u0131 ve diren\u00e7lili\u011fi de g\u00f6z \u00f6n\u00fcnde bulundurulur.<\/span><\/p>

\u00a0<\/span><\/p>

AD\u0130L VE ETK\u0130L\u0130 YAPAY ZEKA MODELLER\u0130<\/span><\/strong><\/p>

\u00a0<\/span><\/p>

AI TRiSM, yapay zeka modellerinin adalet ve etkililik a\u00e7\u0131s\u0131ndan de\u011ferlendirilmesini sa\u011flar. Adalet, yapay zeka modellerinin farkl\u0131 gruplar aras\u0131nda ayr\u0131mc\u0131l\u0131k yapmamas\u0131n\u0131 ve dengeli sonu\u00e7lar \u00fcretmesini ama\u00e7lar. Etkililik ise modelin belirlenen hedeflere ula\u015fma ve istenen sonu\u00e7lar\u0131 sa\u011flama kapasitesidir.<\/span><\/p>

\u00a0<\/span><\/p>

VER\u0130 KORUMA VE G\u00dcVENL\u0130K<\/span><\/strong><\/p>

\u00a0<\/span><\/p>

AI TRiSM, ayn\u0131 zamanda veri koruma ve g\u00fcvenlik risklerini azaltmay\u0131 da hedefler. Yapay zeka modelleri, genellikle b\u00fcy\u00fck miktarda veriyle e\u011fitildi\u011finden, veri korumas\u0131 ve gizlili\u011fi b\u00fcy\u00fck \u00f6nem ta\u015f\u0131r. Bu s\u00fcre\u00e7, veri toplama, depolama, i\u015fleme ve payla\u015fma a\u015famalar\u0131nda g\u00fcvenli\u011fi sa\u011flamak i\u00e7in \u00f6nlemler al\u0131r.<\/span><\/p>

\u00a0<\/span><\/p>

A\u00c7IKLANAB\u0130L\u0130RL\u0130K VE \u015eEFFAFLIK<\/span><\/strong><\/p>

\u00a0<\/span><\/p>

Yapay zeka modellerinin i\u015fleyi\u015finin a\u00e7\u0131klanabilir olmas\u0131, g\u00fcvenilirli\u011fi sa\u011flamak i\u00e7in temel bir gerekliliktir. Bu durum, modelin i\u00e7 \u00e7al\u0131\u015fma prensiplerini anla\u015f\u0131l\u0131r k\u0131larak do\u011fruluk, adalet, sorumluluk, istikrar ve \u015feffafl\u0131k ilkelerini g\u00fc\u00e7lendirir. Gartner\u2019\u0131n \u00f6ng\u00f6r\u00fcs\u00fcne g\u00f6re, yapay zeka hizmet sa\u011flay\u0131c\u0131lar\u0131n\u0131n yar\u0131s\u0131ndan fazlas\u0131n\u0131n, 2024 y\u0131l\u0131 sonuna kadar teknolojilerine bu a\u00e7\u0131klanabilirlik yeteneklerini entegre edece\u011fi d\u00fc\u015f\u00fcn\u00fcl\u00fcyor.<\/span><\/p>

\u00a0<\/span><\/p>

VER\u0130 ANOMAL\u0130LER\u0130N\u0130N \u0130ZLENMES\u0130<\/span><\/strong><\/p>

\u00a0<\/span><\/p>

AI modellerinin do\u011fru \u00e7al\u0131\u015fmas\u0131 ve k\u00f6t\u00fc niyetli sald\u0131r\u0131lardan korunmas\u0131 i\u00e7in \u00fcretim verileri s\u00fcrekli olarak izlenmeli. Veri anomalilerini alg\u0131lamak i\u00e7in AI tabanl\u0131 \u00e7\u00f6z\u00fcmlerin kullan\u0131lmas\u0131, operasyonel s\u00fcre\u00e7lerde \u00f6nemli bir iyile\u015fme sa\u011flar. Gartner\u2019\u0131n raporlar\u0131na g\u00f6re, bu teknolojiyi kullanan organizasyonlar\u0131n \u00e7o\u011fu, veri anomalilerini tespit etmek i\u00e7in AI tabanl\u0131 \u00e7\u00f6z\u00fcmleri kullanmaya ba\u015flayacak.<\/span><\/p>

\u00a0<\/span><\/p>

Sonu\u00e7 olarak yapay zeka sistemlerinin yayg\u0131nla\u015fmas\u0131yla birlikte, AI TRiSM\u2019nin rol\u00fc ve \u00f6nemi giderek art\u0131yor. \u0130lerleyen d\u00f6nemlerde bu yakla\u015f\u0131m\u0131n, yapay zeka sistemlerinin g\u00fcvenilirli\u011fini sa\u011flama ve riskleri en aza indirme konusunda kritik bir rol oynayaca\u011f\u0131 \u00f6ng\u00f6r\u00fcl\u00fcyor. Bu s\u00fcre\u00e7te hem i\u015fletmelerin hem de yapay zeka teknolojisi geli\u015ftiricilerinin, g\u00fcvenlik, risk y\u00f6netimi ve g\u00fcvenilirlik odakl\u0131 bir yakla\u015f\u0131m benimsemeleri kritik \u00f6nemdedir.\u00a0<\/span><\/p>","slug":"ai-trism-yapay-zeka-guven-risk-ve-guvenlik-yonetimi","tags":null,"meta_title":null,"meta_description":null,"meta_keywords":null,"news_cover_min":"\/front\/uploads\/blog\/thumbnail\/1706475600Ko3VM1ZssCaGGsq.webp","news_cover":null,"news_video_min":null,"news_video":null,"view_count":11945,"cropped_1200x675":null,"user":{"id":27,"name":"ADNAN VEYSEL","surname":"ERTEMEL","email":"doc-dr-adnan-veysel-ertemel@gmail.com","slug":"doc-dr-adnan-veysel-ertemel","avatar":"\/front\/uploads\/avatar\/17336916001r1LpO2XUqa1CPY.webp","status":1,"role":1,"email_verified_at":null,"orde":null,"created_at":"2022-10-24T10:50:02.000000Z","updated_at":"2024-12-18T09:48:24.000000Z","seo_title":null,"seo_description":null},"translations":[{"id":48234,"is_featured":0,"is_amp":0,"is_ads":0,"ads_link":null,"post_id":48108,"locale":"tr","category_id":73,"title":"AI TRiSM: Yapay zeka g\u00fcven, risk ve g\u00fcvenlik y\u00f6netimi","home_title":null,"sub_title":null,"slider_title":null,"slider_title_2":null,"slider_spot_title":null,"slider_spot_title_2":null,"subtitleuse":0,"description":"DO\u00c7. DR. ADNAN VEYSEL ERTEMEL","content":"


<\/span><\/strong><\/p>


<\/p>

adnan.ertemel@gmail.com<\/span><\/strong><\/p>

\u00a0<\/span><\/p>

Yapay zeka (YZ) sistemlerinin giderek artan kullan\u0131m\u0131, bu teknolojilerin g\u00fcvenilirli\u011fi, adaleti, dayan\u0131kl\u0131l\u0131\u011f\u0131, verimlili\u011fi ve veri korumas\u0131 gibi kavramlar\u0131n \u00f6ne \u00e7\u0131kmas\u0131na neden oldu. \u0130lgili kavramlar\u0131n ilk harflerinin birle\u015fiminden olu\u015fan ve k\u0131saca AI TRiSM (AI trust, risk and security management) olarak adland\u0131r\u0131lan bu kavram, yapay zeka modellerinin y\u00f6neti\u015fimini sa\u011flamak i\u00e7in olu\u015fturulan bir s\u00fcre\u00e7 ve metodoloji olarak tan\u0131mlanabilir. Bu yakla\u015f\u0131m, yapay zeka sistemlerinin g\u00fcvenilirli\u011fini art\u0131rma ve g\u00fcvenlik y\u00f6netimi konusunda \u00f6ncelikli bir strateji sunma amac\u0131n\u0131 ta\u015f\u0131r.<\/span><\/p>

\u00a0<\/span><\/p>

AI TRiSM, yapay zeka modellerinin y\u00f6neti\u015fimini sa\u011flayarak, bu modellerin g\u00fcvenilirli\u011fini art\u0131rmay\u0131 hedefler. Bu s\u00fcre\u00e7, yapay zeka modellerinin geli\u015ftirilme, test edilme, da\u011f\u0131t\u0131lma ve kullan\u0131lma a\u015famalar\u0131n\u0131 kapsar. G\u00fcvenilirlik, modelin do\u011frulu\u011fu, tutarl\u0131l\u0131\u011f\u0131 ve etkinli\u011fi \u00fczerinde odaklan\u0131rken, ayn\u0131 zamanda modelin adil olmas\u0131, veri korumas\u0131 ve diren\u00e7lili\u011fi de g\u00f6z \u00f6n\u00fcnde bulundurulur.<\/span><\/p>

\u00a0<\/span><\/p>

AD\u0130L VE ETK\u0130L\u0130 YAPAY ZEKA MODELLER\u0130<\/span><\/strong><\/p>

\u00a0<\/span><\/p>

AI TRiSM, yapay zeka modellerinin adalet ve etkililik a\u00e7\u0131s\u0131ndan de\u011ferlendirilmesini sa\u011flar. Adalet, yapay zeka modellerinin farkl\u0131 gruplar aras\u0131nda ayr\u0131mc\u0131l\u0131k yapmamas\u0131n\u0131 ve dengeli sonu\u00e7lar \u00fcretmesini ama\u00e7lar. Etkililik ise modelin belirlenen hedeflere ula\u015fma ve istenen sonu\u00e7lar\u0131 sa\u011flama kapasitesidir.<\/span><\/p>

\u00a0<\/span><\/p>

VER\u0130 KORUMA VE G\u00dcVENL\u0130K<\/span><\/strong><\/p>

\u00a0<\/span><\/p>

AI TRiSM, ayn\u0131 zamanda veri koruma ve g\u00fcvenlik risklerini azaltmay\u0131 da hedefler. Yapay zeka modelleri, genellikle b\u00fcy\u00fck miktarda veriyle e\u011fitildi\u011finden, veri korumas\u0131 ve gizlili\u011fi b\u00fcy\u00fck \u00f6nem ta\u015f\u0131r. Bu s\u00fcre\u00e7, veri toplama, depolama, i\u015fleme ve payla\u015fma a\u015famalar\u0131nda g\u00fcvenli\u011fi sa\u011flamak i\u00e7in \u00f6nlemler al\u0131r.<\/span><\/p>

\u00a0<\/span><\/p>

A\u00c7IKLANAB\u0130L\u0130RL\u0130K VE \u015eEFFAFLIK<\/span><\/strong><\/p>

\u00a0<\/span><\/p>

Yapay zeka modellerinin i\u015fleyi\u015finin a\u00e7\u0131klanabilir olmas\u0131, g\u00fcvenilirli\u011fi sa\u011flamak i\u00e7in temel bir gerekliliktir. Bu durum, modelin i\u00e7 \u00e7al\u0131\u015fma prensiplerini anla\u015f\u0131l\u0131r k\u0131larak do\u011fruluk, adalet, sorumluluk, istikrar ve \u015feffafl\u0131k ilkelerini g\u00fc\u00e7lendirir. Gartner\u2019\u0131n \u00f6ng\u00f6r\u00fcs\u00fcne g\u00f6re, yapay zeka hizmet sa\u011flay\u0131c\u0131lar\u0131n\u0131n yar\u0131s\u0131ndan fazlas\u0131n\u0131n, 2024 y\u0131l\u0131 sonuna kadar teknolojilerine bu a\u00e7\u0131klanabilirlik yeteneklerini entegre edece\u011fi d\u00fc\u015f\u00fcn\u00fcl\u00fcyor.<\/span><\/p>

\u00a0<\/span><\/p>

VER\u0130 ANOMAL\u0130LER\u0130N\u0130N \u0130ZLENMES\u0130<\/span><\/strong><\/p>

\u00a0<\/span><\/p>

AI modellerinin do\u011fru \u00e7al\u0131\u015fmas\u0131 ve k\u00f6t\u00fc niyetli sald\u0131r\u0131lardan korunmas\u0131 i\u00e7in \u00fcretim verileri s\u00fcrekli olarak izlenmeli. Veri anomalilerini alg\u0131lamak i\u00e7in AI tabanl\u0131 \u00e7\u00f6z\u00fcmlerin kullan\u0131lmas\u0131, operasyonel s\u00fcre\u00e7lerde \u00f6nemli bir iyile\u015fme sa\u011flar. Gartner\u2019\u0131n raporlar\u0131na g\u00f6re, bu teknolojiyi kullanan organizasyonlar\u0131n \u00e7o\u011fu, veri anomalilerini tespit etmek i\u00e7in AI tabanl\u0131 \u00e7\u00f6z\u00fcmleri kullanmaya ba\u015flayacak.<\/span><\/p>

\u00a0<\/span><\/p>

Sonu\u00e7 olarak yapay zeka sistemlerinin yayg\u0131nla\u015fmas\u0131yla birlikte, AI TRiSM\u2019nin rol\u00fc ve \u00f6nemi giderek art\u0131yor. \u0130lerleyen d\u00f6nemlerde bu yakla\u015f\u0131m\u0131n, yapay zeka sistemlerinin g\u00fcvenilirli\u011fini sa\u011flama ve riskleri en aza indirme konusunda kritik bir rol oynayaca\u011f\u0131 \u00f6ng\u00f6r\u00fcl\u00fcyor. Bu s\u00fcre\u00e7te hem i\u015fletmelerin hem de yapay zeka teknolojisi geli\u015ftiricilerinin, g\u00fcvenlik, risk y\u00f6netimi ve g\u00fcvenilirlik odakl\u0131 bir yakla\u015f\u0131m benimsemeleri kritik \u00f6nemdedir.\u00a0<\/span><\/p>","slug":"ai-trism-yapay-zeka-guven-risk-ve-guvenlik-yonetimi","orjinalimage":"\/front\/uploads\/blog\/thumbnail\/1706475600Ko3VM1ZssCaGGsq.webp","news_cover_min":"\/front\/uploads\/blog\/thumbnail\/1706475600Ko3VM1ZssCaGGsq.webp","news_cover":null,"news_video_min":null,"news_video":null,"cropped_638x552":null,"cropped_310x208":null,"cropped_416x247":null,"cropped_197x247":null,"cropped_416x600":null,"cropped_1200x675":null,"tags":null,"meta_title":null,"meta_description":null,"meta_keywords":null,"view_count":11945,"yt":0,"ytid":"","ytimage":null,"imgdate":"2000-01-01 00:00:00","cuff_cover":null,"cropped_358x214":null,"cropped_842x474":null}]}}