arXiv AI By Dalton Ross Smith, Wilburn Whittington, Alejandro Martinez, Aidan Duncan, Gang Li

A Conceptual Framework for Enhancing Workforce Readiness for Smart Manufacturing in the AI Era

Read the original on arXiv AI →

arXiv:2608. 11540v1 Announce Type: cross Abstract: The convergence of artificial intelligence (AI), Industrial Internet of Things, cyber-physical systems, and advanced robotics is reshaping manufacturing faster than engineering curricula can adapt, widening the gap between the competencies required on the shop floor and those delivered by traditional engineering and technology education.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv AI.

arXiv AI
Jun 15

Thinking Outside the [Chat]Box: Bridging Computer Science and Industrial Design for Cognitive-Inclusive Generative AI

arXiv:2606. 14306v1 Announce Type: cross Abstract: Current Generative AI (GenAI) interfaces remain largely constrained to chatbox interaction, which can impose high cognitive demands on users and create substantial barriers for people with intellectual disabilities (ID), including prompt formulation difficulties, response overload, and limited mechanisms to assess information reliability.

By Virginia Francisco, Daniel Guasch, Raquel Herv\'as
arXiv AI
5d ago

RAIL: An Automatic Classifier of the Artificial Intelligence Readiness Level

arXiv:2608. 13428v1 Announce Type: new Abstract: Assessing the maturity of artificial intelligence technologies is essential for investment decisions, project management, and policy monitoring, yet the available readiness frameworks are heterogeneous and difficult to apply automatically: the adaptation of Technology Readiness Levels to AI lacks AI-specific gating criteria, the Machine Learning Technology Readiness Levels presuppose access to internal process artifacts, and AI/data readiness dimension models employ scales that resist direct comparison.

By Juan Irving Vasquez, Juan Terven, Laura-Ivoone Garay-Jimenez