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1.
Entropy (Basel) ; 25(10)2023 Oct 09.
Artigo em Inglês | MEDLINE | ID: mdl-37895550

RESUMO

Recent advancements in artificial intelligence (AI) technology have raised concerns about the ethical, moral, and legal safeguards. There is a pressing need to improve metrics for assessing security and privacy of AI systems and to manage AI technology in a more ethical manner. To address these challenges, an AI Trust Framework and Maturity Model is proposed to enhance trust in the design and management of AI systems. Trust in AI involves an agreed-upon understanding between humans and machines about system performance. The framework utilizes an "entropy lens" to root the study in information theory and enhance transparency and trust in "black box" AI systems, which lack ethical guardrails. High entropy in AI systems can decrease human trust, particularly in uncertain and competitive environments. The research draws inspiration from entropy studies to improve trust and performance in autonomous human-machine teams and systems, including interconnected elements in hierarchical systems. Applying this lens to improve trust in AI also highlights new opportunities to optimize performance in teams. Two use cases are described to validate the AI framework's ability to measure trust in the design and management of AI systems.

2.
Artigo em Inglês | MEDLINE | ID: mdl-38187956

RESUMO

The convergence of Digital Twin technologies with precision health, the pharmaceutical industry, and life sciences has garnered substantial recent attention. As we advance toward personalized medicine and precision health, the fusion of Digital Twin and blockchain technologies is poised to enhance healthcare outcomes fundamentally. This conference discussion highlighted pivotal drivers accelerating the adoption of Digital Twin-enabled blockchain solutions, encompassing the shift to a decentralized World Wide Web (Web 3.0), the establishment of a global interconnected health ecosystem, and the distinct advantages offered by converging frontier technologies in optimizing healthcare, pharmaceutical industry, and life sciences. Yet, the effective deployment of blockchain-powered Digital Twins in precision health necessitates robust cyber safety measures, proactive ethical frameworks, data validation, provenance assurance, streamlined supply chain management, and heightened interoperability. These proceedings underscored blockchain-powered Digital Twins' pivotal role in reshaping health data management, security, sharing, ownership, and monetization and in revolutionizing pharmaceutical supply chain management and novel drugs and therapeutics development within the precision health domain.

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