Innovation is degenerative. It exploits and erodes our prosperity and health on the promise that success will repay the losses, a promise that is seldom if ever kept. So, what if our processes for innovation were regenerative, in the sense that they nourish and strengthen teams, organisations, communities and environment continuously, regardless of the outcome? What would this regenerative innovation process look like?
Category Archives: Uncategorized
Before wage work
Regular full-time employment at a single job may seem like the natural way of things, but it is, in fact, a fairly recent phenomenon. For hundreds of years before 1800, work took multiple forms and had varied meanings, motivations and outcomes. Making money was just a part of it, and often not a very important part.
Techno-optimism, perverted histories and stolen futures
AI has been ‘leveraged’ since 2014 to ‘transform’ the oil and gas industry, by enabling exploitation of previously hard-to-access reserves of fossil fuels, in full awareness of the irreparable damage done as a result. Techno-optimism is not merely naïve. Future histories of ‘transformation’ are often part of a political project to protect and advance the rights and interests of extractive capitalism while destroying cultures, societies and the environment without a care.
EU removes ‘emotional robots’ from the classroom
The new EU AI Act bans ‘unacceptably risky’ AI applications, including emotion-aware systems which educational researchers believe can significantly improve learning in the classroom. Is the EU right to outlaw emotional AI for learning along with such nefarious uses as social scoring and behavioural manipulation? And with the diffusion of emotional AI in mainstream consumer products including virtual reality headsets, might the ban be a backward step for European learners?
Emotional AI in education: applications and implications
With the passing of the EU AI Act, emotional AI in education may become another ‘failed idea’ in AI’s history. But we can also see it as a speculative future. If we imagine that an emerging technology will become mainstream, what are the possibilities, and what are the implications for how we design learning experiences?
What if courses are not the answer?
Universities are finding that creating and supporting more and more courses in an already saturated market is an unsustainable model. Instead, they should move to developing new value propositions based on things that are scarce, such as bespoke, learner co-created experiences, and challenge-based and entrepreneurial learning, creating opportunities for learners to practice skills, receive feedback, reflect, and build confidence and psychological capital.
Week notes: 17 July 2023
It may be wishful thinking to hope that AI will simply slot in to our current toolsets, making us more efficient at work. Even the current beta tools enable an order of magnitude increase in efficiency. Skill in doing a single thing will simply have no value. Instead, we will need skills in ‘multilearning’, or the ability to learn and deploy new knowledge and skills quickly. Very quickly.
Week notes: 3 July 2023
This week I began my research into individuals and teams who are able to 1) learn about new techs quickly while 2) discerning the impacts and applications in their domains while 3) starting to implement. How do they learn, select and adapt so quickly and effectively, while others do not? If you’re reading this and you are (or you know) someone or some team or startup that is learning, adopting and adapting new techs exceptionally fast, I’d love to talk.
Week notes: 26 June 2023
When technology advances quickly, remaking work and economies, how do we (individuals, groups, orgs, communities) determine the skills and capabilities needed to compete? And if specially convened panels of industry experts cannot answer this question, can we create alternative communities, entities, services and experiences to fill the void and enable young people in particular to find answers?
Week notes: 19 June 2023
This week I am thinking about the innovation that isn’t. The innovation that doesn’t happen. I don’t mean innovation that fails. I mean innovation that simply doesn’t occur. The innovation that isn’t. Might machine and social learning reverse the stagnation of ideas?
Matthew Moran 