首页|Studies from Alan Turing Institute in the Area of Artificial Intelligence Described (Artificial Intelligence In Government: Concepts, Standards, and a Unified Framework)
Studies from Alan Turing Institute in the Area of Artificial Intelligence Described (Artificial Intelligence In Government: Concepts, Standards, and a Unified Framework)
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NETL
NSTL
Elsevier
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Research findings on Artificial Intelligence are discussed in a new report. According to news reporting originating from London, United Kingdom, by NewsRx correspondents, research stated, “Recent advances in artificial intelligence (AI), especially in generative language modelling, hold the promise of transforming government. Given the advanced capabilities of new AI systems, it is critical that these are embedded using standard operational procedures, clear epistemic criteria, and behave in alignment with the normative expectations of society.” Financial supporters for this research include Towards Turing 2.0 under the EPSRC, Alan Turing Insti- tute.Our news editors obtained a quote from the research from Alan Turing Institute, “Scholars in multiple domains have subsequently begun to conceptualize the different forms that AI applications may take, highlighting both their potential benefits and pitfalls. However, the literature remains fragmented, with researchers in social science disciplines like public administration and political science, and the fast-moving fields of AI, ML, and robotics, all developing concepts in relative isolation. Although there are calls to formalize the emerging study of AI in government, a balanced account that captures the full depth of theoretical perspectives needed to understand the consequences of embedding AI into a public sector context is lacking. Here, we unify efforts across social and technical disciplines by first conducting an integrative literature review to identify and cluster 69 key terms that frequently co-occur in the multidisciplinary study of AI. We then build on the results of this bibliometric analysis to propose three new multifaceted concepts for understanding and analysing AI-based systems for government (AI-GOV) in a more unified way: (1) operational fitness, (2) epistemic alignment, and (3) normative divergence.”
LondonUnited KingdomEuropeArtificial IntelligenceEmerg- ing TechnologiesMachine LearningAlan Turing Institute
NETL
NSTL
Elsevier
