Actualidad - inteligencia artificial

Las nuevas tecnologías, junto con los continuos cambios socioeconómicos a nivel global, han aumentado y acelerado la complejidad en los entornos profesionales. El enfoque experimental para poder abordar este reto es esencial, tal y como desgrana Dave Snowden en su modelo Cynefin. El equilibrio entre personas, robots y algoritmos está cambiando rápidamente y una de las claves para actuar es conocer el sistema de relaciones que se produce entre ellos.


Welcome to Sensemaking, AI, and Learning (SAIL)- a look at the trends and technologies impacting education.
In numerous meetings with university leadership, educators, and faculty over the last few months, a growing anxiety around the implications of AI is palpable. For some, this anxiety is existential. For most, however, it's an awareness that AI is yet another technology that requires a change pedagogy, teaching, and learning. In a workshop yesterday, I asked senior leadership how serious they viewed the risk of AI (low, medium, significant). Most felt it was a medium risk - significant but not fatal to the university.


Reflections on my TEDX Talk.
Last night, I gave a TEDX Talk on AI and Education.
I decided to start the talk by taking the audience back to 1984 and the work of Educational Psychologist, Benjamin Bloom. At the time, Bloom was exploring a big education research question: what are the optimal conditions for human learning?


Sal Khan, the founder and CEO of Khan Academy, thinks artificial intelligence could spark the greatest positive transformation education has ever seen. He shares the opportunities he sees for students and educators to collaborate with AI tools -- including the potential of a personal AI tutor for every student and an AI teaching assistant for every teacher -- and demos some exciting new features for their educational chatbot, Khanmigo.


In a recent experiment, researchers used large language models to translate brain activity into words.
Think of the words whirling around in your head: that tasteless joke you wisely kept to yourself at dinner; your unvoiced impression of your best friend’s new partner. Now imagine that someone could listen in.


The dream: AI will exponentially enhance our productivity and creativity. It will optimize everything that can be optimized, freeing us humans up to do work that truly matters. It will lead to new breakthroughs in science, scale up mental health services, detect and cure cancer, and more. It will finally enable humanity to realize its full potential.
The nightmare: present and future harm. Estimates suggest AI will eliminate 300 million jobs worldwide, with 18 percent of work to be automated, over-proportionally affecting knowledge workers in advanced economies.


This week I spent a few days at the ASU/GSV conference and ran into 7,000 educators, entrepreneurs, and corporate training people who had gone CRAZY for AI.
No, I’m not kidding. This community, which makes up people like training managers, community college leaders, educators, and policymakers is absolutely freaked out about ChatGPT, Large Language Models, and all sorts of issues with AI. Now don’t get me wrong: I’m a huge fan of this. But the frenzy is unprecedented: this is bigger than the excitement at the launch of the i-Phone.


Among the millions of words written about ChatGPT, LamDA, Bard and Bing, and the excitement about rethinking assessment/ collaborating with artificial minds/ disrupting higher education (choose your pulse-raiser), this sentence felt significant to me. It’s from Nature’s Editorial of 23 Jan, and it explains that AI tools will not be credited with (co)authorship of any papers published in Nature journals because:
any attribution of authorship carries with it accountability for the work, and AI tools cannot take such responsibility.


Over 300 years since the first written exam was used in the English education system, this traditional form of assessment continues to divide opinion. To their supporters, written exams provide a rigorous test of students’ knowledge and understanding that acts as a source of motivation as well as a sound basis for progression onto university or employment. Indeed, Prime Ministers, Education Secretaries, Schools Ministers and regulators have publicly stated that written exams are the ‘best and fairest’ way to measure pupils’ attainment. Meanwhile, critics argue that written exams are narrow assessments that focus too much on memorisation and fail to provide students with the wide range of skills that they need for later life and work.


The narrative around cheating students doesn’t tell the whole story. Meet the teachers who think generative AI could actually make learning better.
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