Human-Centric Artificial Intelligence for Innovation

Explore the potential of Human-Centric Artificial Intelligence for groundbreaking innovation.

The concept of Human-Centric Artificial Intelligence emphasizes the role of Artificial Intelligence technologies designed with a primary focus on human needs and experiences. This approach contrasts with traditional AI models, which often prioritize performance metrics over user-centric design.

Incorporating human-centered design into Artificial Intelligence systems aims to create more accessible, transparent, and inclusive technologies. It ensures that AI solutions are not just efficient but also ethical and relatable, fostering trust and broader adoption among users.

By prioritizing user experiences and ethical considerations, Human-Centric Artificial Intelligence promises to drive innovation while addressing societal challenges, ultimately serving as a catalyst for breakthroughs in various fields.

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UK mps open inquiry into artificial intelligence and edtech in education

UK mps have launched a cross party inquiry into how artificial intelligence and education technology are reshaping learning across early years, schools, colleges and universities, and how government should balance innovation with safeguards. The education committee will examine opportunities to improve teaching and workload alongside risks around inequality, privacy, safeguarding and assessment.

Most UK firms see Artificial Intelligence training gap as shadow tool use grows

New research finds that 6 in 10 UK businesses say employees lack comprehensive Artificial Intelligence training, even as shadow use of unapproved tools becomes widespread and investment surges. Executives warn that without stronger skills, governance and strategy, many organisations risk missing out on expected Artificial Intelligence returns.

COSO issues internal control roadmap for governing generative artificial intelligence

COSO has released governance guidance that applies its Internal Control-Integrated Framework to generative artificial intelligence, offering audit-ready control structures and implementation tools for organizations. The publication details capability-based risk mapping, aligned controls, and practical templates to help institutions manage emerging technology risks.

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