The future of video entertainment: Immersive, gamified, and diverse — from mckinsey.com
“There’ll be a blurring of the lines between things we watch and things we play”
We need to go beyond the focus on STEM (science, tech, engineering, math) towards HECI (humanity, ethics, creativity, imagination) — from futuristgerd.com by Gerd Leonhard
…an important realisation that recently dawned on me. What will our schools, colleges and universities do about this?
“It wasn’t raining when Noah built the ark.”
Gerd Leonhard
Also see:
Boost Usability of Libraries & Knowledge Hubs with Automation — from learningsolutionsmag.com by Markus Bernhardt
Excerpts (emphasis DSC):
Our article series looks at the top three areas where we see automation and AI revolutionizing the way in which successful L&D teams work: Asset libraries and knowledge hubs; hyper-personalized, truly adaptive learning; and capability mapping. This article examines the impact of AI and automation on maintaining asset libraries and knowledge hubs.
…
Thus, the contextualization engine becomes a powerful content management tool. It is also easy to use and requires no particular subject matter knowledge of the user; the librarian who has read everything does that for the user. And this works, of course, with articles, slide decks, audio, video, and even VR/AR content, and basically any file type.
Assets can be mapped to competencies, skills, learning objectives, departments, the requirements of a specific course or workshop, or to the horizontals and verticals of an organization’s internal restructuring model. And this takes place within seconds and minutes, and at scale.
With the ability to map content as well as practice exercises, questions, and assessments automatically into each concept’s complexity tree, it is now possible to use automation and AI to deliver adaptive and truly personalized learning content and learning paths.
Every month Essentials publish an Industry Trend Report on AI in general and the following related topics:
- AI Research
- AI Applied Use Cases
- AI Ethics
- AI Robotics
- AI Marketing
- AI Cybersecurity
- AI Healthcare
The Race to Hide Your Voice — from wired.com by Matt Burgess
Voice recognition—and data collection—have boomed in recent years. Researchers are figuring out how to protect your privacy.
AI: Where are we now? — from educause.edu by EDUCAUSE
Is the use of AI in higher education today invisible? dynamic? perilous? Maybe it’s all three.
What is artificial intelligence and how is it used? — from europart.europa.eu; with thanks to Tom Barrett for this resource
AI: Where are we now? — from educause.edu by EDUCAUSE
Is the use of AI in higher education today invisible? dynamic? perilous? Maybe it’s all three.
Also see:
Also relevant/see:
Radar Trends to Watch: June 2022 — from oreilly.com
Excerpt:
The explosion of large models continues. Several developments are especially noteworthy. DeepMind’s Gato model is unique in that it’s a single model that’s trained for over 600 different tasks; whether or not it’s a step towards general intelligence (the ensuing debate may be more important than the model itself), it’s an impressive achievement. Google Brain’s Imagen creates photorealistic images that are impressive, even after you’ve seen what DALL-E 2 can do. And Allen AI’s Macaw (surely an allusion to Emily Bender and Timnit Gebru’s Stochastic Parrots paper) is open source, one tenth the size of GPT-3, and claims to be more accurate. Facebook/Meta is also releasing an open source large language model, including the model’s training log, which records in detail the work required to train it.
Designing for Autism, ADHD, and More: Representing Neurodivergence — from learningsolutionsmag.com by Judy Katz
Excerpt:
Understanding inclusion from a neurodiversity perspective has both a DEI component (addressed in this article), and an accessibility component (addressed in the two articles to come in this series). As learning and development professionals, applying both is not just about accommodating impairment or staying compliant with the ADA. It’s about unlocking the talents that diverse neurotypes bring.
Positives of neurodivergence
One of the best things you can do to lead to greater acceptance of neurodivergence in the workplace is to learn and reinforce to others that neurodivergent brains are often different in positive ways, despite broad negative stereotypes. Here are some examples, but remember, not all traits apply to all individuals; if you know one neurodivergent, you know one neurodivergent.
#autistics #ADHD #Aspergers #neurodivergence #DEI
Also from learningsolutionsmag.com:
Automation, AI Will Advance—and Challenge—Learning Leadership — by Markus Bernhardt
Excerpt:
The current momentum of change, seen across all sectors and industries, is unparalleled in magnitude and speed; both are accelerating. The need for businesses to adapt has arguably never been more pressing, while challenges continue to grow at an increasing pace.
The digital revolution has arrived, and we already find ourselves in the thick of it. For learning and development (L&D), the time has come that deploying automation will be key. When we look at other departments within organizations, we can no longer imagine how marketing, sales, finance, or HR would fare without automation. Here, automation has celebrated some huge successes, gathering momentum as available technology is deployed more broadly. The results are increasing efficiencies, accuracy, and speed, and at scale.
This article introduces a short series on automation and AI and their impact on L&D.
How to ensure we benefit society with the most impactful technology being developed today — from deepmind.com by Lila Ibrahim
In 2000, I took a sabbatical from my job at Intel to visit the orphanage in Lebanon where my father was raised. For two months, I worked to install 20 PCs in the orphanage’s first computer lab, and to train the students and teachers to use them. The trip started out as a way to honour my dad. But being in a place with such limited technical infrastructure also gave me a new perspective on my own work. I realised that without real effort by the technology community, many of the products I was building at Intel would be inaccessible to millions of people. I became acutely aware of how that gap in access was exacerbating inequality; even as computers solved problems and accelerated progress in some parts of the world, others were being left further behind.
After that first trip to Lebanon, I started reevaluating my career priorities. I had always wanted to be part of building groundbreaking technology. But when I returned to the US, my focus narrowed in on helping build technology that could make a positive and lasting impact on society. That led me to a variety of roles at the intersection of education and technology, including co-founding Team4Tech, a non-profit that works to improve access to technology for students in developing countries.
Also relevant/see:
Microsoft AI news: Making AI easier, simpler, more responsible — from venturebeat.com by Sharon Goldman
But one common theme bubbles over consistently: For AI to become more useful for business applications, it needs to be easier, simpler, more explainable, more accessible and, most of all, responsible.