We believe that artificial intelligence applications have great potential to facilitate and benefit humanity's life. We believe in the importance of using artificial intelligence ethically in all applications we implement and staying away from applications that will adversely affect humanity. We act by believing in this ethical responsibility in all our products and projects.<\/p>\n\n\n\n
Personal data is never used when processing camera images. The system does not rely on bodily cues and therefore does not use facial recognition or biometrics. Faces are blurred on all picture and video alerts to maintain anonymity. After the incoming data is processed on the artificial intelligence platform, only the data related to the notifications is kept encrypted in the system to be transmitted to our customer, other data is never stored.<\/p>\n\n\n\n
The most important benefit of BrightIQ is its positive impact on the well-being of employees, their families and society. Our goal is to support leaders in achieving the goal of zero accidents in occupational safety by providing previously unavailable data while protecting employee privacy. We prioritize ethical evaluation at every step of our product development process.<\/p>","protected":false},"excerpt":{"rendered":"
Yapay zeka uygulamalar\u0131n\u0131n insanl\u0131\u011f\u0131n hayat\u0131n\u0131 kolayla\u015ft\u0131rma ve fayda sa\u011flama konusunda b\u00fcy\u00fck potansiyele sahip oldu\u011funa inan\u0131yoruz. Hayata ge\u00e7irdi\u011fimiz t\u00fcm uygulamalarda yapay zekay\u0131 etik \u015fekilde kullanmaya ve insanl\u0131\u011f\u0131 k\u00f6t\u00fc etkileyecek uygulamalardan uzak durman\u0131n \u00f6nemine inan\u0131yoruz. T\u00fcm \u00fcr\u00fcnlerimizde ve projelerimizde bu etik sorumlulu\u011fa inanarak hareket ediyoruz. Kamera g\u00f6r\u00fcnt\u00fclerini i\u015flerken ki\u015fisel veriler kesinlikle kullan\u0131lmaz. Sistem bedensel ipu\u00e7lar\u0131na dayanmaz ve […]<\/p>","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-169","page","type-page","status-publish","hentry"],"acf":[],"_links":{"self":[{"href":"https:\/\/arvonas.com\/en\/wp-json\/wp\/v2\/pages\/169","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/arvonas.com\/en\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/arvonas.com\/en\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/arvonas.com\/en\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/arvonas.com\/en\/wp-json\/wp\/v2\/comments?post=169"}],"version-history":[{"count":4,"href":"https:\/\/arvonas.com\/en\/wp-json\/wp\/v2\/pages\/169\/revisions"}],"predecessor-version":[{"id":327,"href":"https:\/\/arvonas.com\/en\/wp-json\/wp\/v2\/pages\/169\/revisions\/327"}],"wp:attachment":[{"href":"https:\/\/arvonas.com\/en\/wp-json\/wp\/v2\/media?parent=169"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}