Governing emerging technologies is one of the most important issues of the twenty-first century, and primarily concerns the public, private, and social initiatives that can shape the adoption and responsible development of digital technologies. This study surveys the emerging landscape of blockchain and artificial intelligence (AI) governance and maps the ecosystem of emerging platforms within industry and public and civil society. We identify the major players in the public, private, and civil society organizations and their underlying motivations, and examine the divergence and convergence of these motivation and the way they are likely to shape the future governance of these emerging technologies. There is a broad consensus that these technologies represent the present and future of economic growth, but they also pose significant risks to society. Indeed, there is also considerable confusion and disagreement among the major players about navigating the delicate balance between promoting these innovations and mitigating the risks they pose. While some in the industry are calling for self-regulation, others are calling for strong laws and state regulation to monitor these technologies. These disagreements, are likely to remain for the foreseeable future and may derail the optimal development of governance ecosystems across jurisdictions. Therefore, we propose that players should consider erecting new safeguards and using existing frameworks to protect consumers and society from the harms and dangers of these technologies. For instance, through re-examining existing legal and institutional arrangements to check whether these cater for emerging issues with new technologies, and as needed make necessary update/amendments. Further, there may be cases where existing legal and regulated systems are completely outdated and can't cover for new technologies, for example, when AI is used to influence political outcomes, or crypto currency frauds, or AI-powered autonomous vehicles, such cases call of agile governance regimes. This is important because different players in government, industry, and civil are still coming to terms with the governance challenges that these emerging technologies pose to society, and no one has a clear answer on optimal way to promote these technologies, at the same time limit the dangers they pose to users.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8874265 | PMC |
http://dx.doi.org/10.3389/frma.2022.801549 | DOI Listing |
Front Bioeng Biotechnol
December 2024
Electrical and Computer Engineering Department, Lebanese American University, Byblos, Lebanon.
This scoping review summarizes two emerging electrical impedance technologies: electrical impedance myography (EIM) and electrical impedance tomography (EIT). These methods involve injecting a current into tissue and recording the response at different frequencies to understand tissue properties. The review discusses basic methods and trends, particularly the use of electrodes: EIM uses electrodes for either injection or recording, while EIT uses them for both.
View Article and Find Full Text PDFDigit Discov
December 2024
Eindhoven University of Technology, Institute for Complex Molecular Systems, Eindhoven AI Systems Institute, Dept. Biomedical Engineering Eindhoven Netherlands
Deep learning has significantly accelerated drug discovery, with 'chemical language' processing (CLP) emerging as a prominent approach. CLP approaches learn from molecular string representations (, Simplified Molecular Input Line Entry Systems [SMILES] and Self-Referencing Embedded Strings [SELFIES]) with methods akin to natural language processing. Despite their growing importance, training predictive CLP models is far from trivial, as it involves many 'bells and whistles'.
View Article and Find Full Text PDFJ Diabetes Sci Technol
December 2024
CyberActa, Sudbury, MA, USA.
The use of artificial intelligence (AI) in diabetes management is emerging as a promising solution to improve the monitoring and personalization of therapies. However, the integration of such technologies in the clinical setting poses significant challenges related to safety, security, and compliance with sensitive patient data, as well as the potential direct consequences on patient health. This article provides guidance for developers and researchers on identifying and addressing these safety, security, and compliance challenges in AI systems for diabetes management.
View Article and Find Full Text PDFPediatr Res
December 2024
Department of Neurological Surgery, Ohio State University Medical Center, Columbus, OH, USA.
Background: Post-hemorrhagic hydrocephalus (PHH) is a severe complication in premature infants following intraventricular hemorrhage (IVH). It is characterized by abnormal cerebrospinal fluid (CSF) accumulation, disrupted CSF dynamics, and elevated intracranial pressure (ICP), leading to significant neurological impairments.
Objective: This review provides an overview of recent molecular insights into the pathophysiology of PHH and evaluates emerging therapeutic approaches aimed at addressing its underlying mechanisms.
J Pharm Sci
December 2024
Process Development, Amgen Inc., Thousand Oaks, CA 91320.
Analytical technologies and methods play a pivotal role in attribute understanding and control which are essential to the rapidly evolving field of pharmaceutical development and manufacturing. These technologies are advancing quickly, where innovations often involve both new scientific approaches and novel applications of established techniques. In many cases, the lack of harmonized global regulatory expectations presents challenges for the adoption of advanced technologies.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!