Autoethnographic research has encountered challenges around verification, transparency and veracity of data, and issues have been debated due to its subjective nature (see Jones, 2010; Keeler, 2019; Méndez, 2013). Additional complications arise regarding neutrality and objectivity associated with the researchers’ identities and experiences being represented in autoethnographic accounts. The authors acknowledge that the accounts provided are subjective, and have influenced the research process and product.
How Renewable Energy, Indigenous Heritage, and Economic Innovation Create a Global Hub for Inclusive AI…
普通话翻译 (Pǔtōnghuà Fānyì) PDF TATANKA.site, ChurchofAI.website, ISCed.org/SDG4.ai, and VOX.gdn aim to forge a Sustainable, Inclusive…
Download (FREE) all MP3s (320 Kbps) and images: ling.zip (299 MB) Human Editor's Note: This…
Google's Deep Dive Podcast: China's Edge in AI Development: Leveraging Its STEM Talent Pool https://youtu.be/cDZ41lapNCE…
Google's Deep Dive Podcast: AI, Sofia's Tera Danco https://youtu.be/dviOF9GoNXQ Tera Danco (Full Album) by AI…
Google's Deep Dive Podcast: China's $150 Billion AI Development Plan: A Vision for Global Leadership…