Regulatory Aspects of Artificial Intelligence on Blockchain

2022 ◽  
2020 ◽  
Vol 36 (6) ◽  
pp. 443-449
Author(s):  
Julian Varghese

<b><i>Background:</i></b> Artificial intelligence (AI) applications that utilize machine learning are on the rise in clinical research and provide highly promising applications in specific use cases. However, wide clinical adoption remains far off. This review reflects on common barriers and current solution approaches. <b><i>Summary:</i></b> Key challenges are abbreviated as the RISE criteria: Regulatory aspects, Interpretability, interoperability, and the need for Structured data and Evidence. As reoccurring barriers of AI adoption, these concepts are delineated and complemented by points to consider and possible solutions for effective and safe use of AI applications. <b><i>Key Messages:</i></b> There is a fraction of AI applications with proven clinical benefits and regulatory approval. Many new promising systems are the subject of current research but share common issues for wide clinical adoption. The RISE criteria can support preparation for challenges and pitfalls when designing or introducing AI applications into clinical practice.


Author(s):  
David L. Poole ◽  
Alan K. Mackworth

2020 ◽  
Vol 51 (4) ◽  
pp. 239-253
Author(s):  
John V. Petrocelli ◽  
Haley F. Watson ◽  
Edward R. Hirt

Abstract. Two experiments investigate the role of self-regulatory resources in bullshitting behavior (i.e., communicating with little to no regard for evidence, established knowledge, or truth; Frankfurt, 1986 ; Petrocelli, 2018a ), and receptivity and sensitivity to bullshit. It is hypothesized that evidence-based communication and bullshit detection require motivation and considerably greater self-regulatory resources relative to bullshitting and insensitivity to bullshit. In Experiment 1 ( N = 210) and Experiment 2 ( N = 214), participants refrained from bullshitting only when they possessed adequate self-regulatory resources and expected to be held accountable for their communicative contributions. Results of both experiments also suggest that people are more receptive to bullshit, and less sensitive to detecting bullshit, under conditions in which they possess relatively few self-regulatory resources.


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