Blockchain in Health - From Pilots to Mainstream and Implications for AI

主流 块链 数据科学 心理学 计算机科学 航空学 工程类 政治学 计算机安全 法学
作者
Sathya Krishnasamy,Badri Narayanan,BSc Atul Apte,M. Khurshid
出处
期刊:Blockchain in healthcare today [Partners in Digital Health]
卷期号:7 (1)
标识
DOI:10.30953/bhty.v7.309
摘要

Speakers delve into and beyond the previously published BHHTY journal article “Moving Beyond Proof of Concept and Pilots to Mainstream: Discovery and Lessons from Blockchain in Healthcare,” located at https://doi.org/10.30953/bhty.v6.280. This continuous enterprise blockchain technology journey extends the framework and solution assemblies including further developments, with cross over into generative AI and ethics. Objectives Learn specific examples on the economics of blockchain revealing low-hanging fruit for the move from pilots to adoption. Explore concepts such as: Data integrity, minimal data, inter-entity streamlining leading to efficiencies, and what is already possible with tech stack developments and economics in efficiency (in millions) from the previously published BHTY article at DOI: https://doi.org/10.30953/bhty.v6.280 Learn from other verticals to build a framework that is more comprehensive encompassing global perspectives Future proofing and stair-stepping design for an evolving technology – holistic guidance to find and execute the opportunities Obtain a framework for blockchain adoption based on the article. In addition, authors address the academic view of blockchain adoption, and that it is a combination of tech, policy, economics, consumer engagement, and operationalization. Acquire multi-dimensional discovery and specific blockchain constructs including provenance- consensus, trust maps, convergence, dApp human loops, and future proofing /stair-stepping Grasp global perspectives on evolving frameworks with in many verticals and the multi-dimensional nature of blockchain transformation, operationalization, blockchain-enterprise landscape, and AI automation. Gain a better understanding of why is blockchain an essential technology for the future of responsible AI and for scalability of solutions

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