Results 121 to 130 of about 200,089 (297)

Harnessing Metacognition for Safe and Responsible AI

Technologies
The rapid advancement of artificial intelligence (AI) technologies has transformed various sectors, significantly enhancing processes and augmenting human capabilities.
Peter B. Walker, Jonathan J. Haase, Melissa L. Mehalick, Christopher T. Steele, Dale W. Russell, Ian N. Davidson   +5 more
doaj   +1 more source

Responsible Generative AI for SMEs in UK and Africa Case Study Cocreation Workshop Report

The University of Nottingham hosted a co-creational workshop from 29th to 31st January at the Jubilee Hotel & Conference facilities, bringing together participants from the RAISE project’s case studies across the UK and Africa.
Poder, Irma, Ochang, Paschal, Buckley, Matt, Stahl, Bernd, Eke, Damian, Rodrigues, Rowena, Cameron, Harriet   +6 more
core   +1 more source

A Knowledge‐Based Approach for Understanding and Managing Additive Manufacturing Data

Advanced Engineering Materials, EarlyView.
Additive manufacturing processes generate a large amount of data. Effectively managing, understanding, and retrieving information from this data remains a major challenge. Therefore, we propose an ontology‐based approach to integrate heterogeneous data, enable semantic queries, and support decision‐making.
Mina Abd Nikooie Pour, Prithwish Tarafder, Anton Wiberg, Huanyu Li, Johan Moverare, Patrick Lambrix   +5 more
wiley   +1 more source

Meaningful Human Control and Responsibility Gaps in AI: No Culpability Gap, but Accountability and Active Responsibility Gap

Journal of Integrative and Innovative Humanities
At the current stage of technological development, the rapid advancement of Artificial Intelligence (AI) has given rise to various ethical concerns. Among these, the “Responsibility Gap” notion has appeared as a prominent issue.
Tatdanai Khomkhunsorn
doaj  

Ethical AI framework for future SHRM research

Discover Artificial Intelligence
Doctoral research in Strategic Human Resources Management (SHRM) has significant impact to organisational productivity and employee performance. Employees’ attitude towards work changes dynamically depending on multiple factors and hence suitable SHRM ...
Gowri R., Senthil Kumar S., Neeraj Kumar Dubey   +2 more
doaj   +1 more source

Current Status and Challenges in Data Collection for Aerospace Coatings Deposited by Plasma Spraying

Advanced Engineering Materials, EarlyView.
An innovative approach has been integrated into the GRENAT project to optimize plasma spraying and coating performance. Raw materials are accelerated and melted in the plasma generated by torches, creating coatings. Monitoring sensors collect process data which are combined with ex situ characterization data.
Lila Randriamananjara, Vincent Rat, Quentin Dubreuil, Patrice Valorge, Simon Goutier, Alain Denoirjean, Olivier Messe, Céline Ruelle, Jean‐Philippe Poli   +8 more
wiley   +1 more source

SAFE AI metrics: An integrated approach

Machine Learning with Applications
We contribute to the field of AI governance with the development of a unified compliance metric that integrates three key dimensions of SAFE Artificial Intelligence: Security, Accuracy, and Explainability.
Paolo Giudici, Vasily Kolesnikov
doaj   +1 more source

Responsible AI in Youth Sectors Network Meeting Presentation

The Responsible AI in Youth Sectors Network (RAI YSN) is a shared space for open discussion, knowledge-building and coordinated action on AI’s expanding role in youth work, youth justice and care services.
Linus Tan, Joel McGregor, Caleb Lloyd
core  

AI and Agendas

In this paper, I argue that the primary AI-related ethical issue is that of the agendas driving AI. While there is a portion of AI-related ethical risks which stems from indeterministic elements of AI and their interaction with existing social and ...
Gogoshin, Dane Leigh
core   +1 more source

Toward Knowledge‐Based Workflows: A Semantic Approach to Atomistic Simulations for Mechanical and Thermodynamic Properties

Advanced Engineering Materials, EarlyView.
Knowledge‐based atomistic workflows are presented for mechanical and thermodynamic properties. By coupling modular simulations with ontology‐aligned metadata and provenance, Fe case studies on elastic behavior, defects, thermal properties, and Hall–Petch strengthening reveal how FAIR, queryable, and reusable simulation data can be generated. Mechanical
Abril Azócar Guzmán, Hoang‐Thien Luu, Sarath Menon, Tilmann Hickel, Nina Merkert, Stefan Sandfeld   +5 more
wiley   +1 more source