))
#115 The Future of work, leadership & innovation with karl Lillrud
Manage episode 442759620 series 2811944
Innehåll tillhandahållet av Suzie Lewis. Allt poddinnehåll inklusive avsnitt, grafik och podcastbeskrivningar laddas upp och tillhandahålls direkt av Suzie Lewis eller deras podcastplattformspartner. Om du tror att någon använder ditt upphovsrättsskyddade verk utan din tillåtelse kan du följa processen som beskrivs här https://sv.player.fm/legal.
"The path that leads to success is the path where you dare to take on those challenges and question yourself"
A fabulous conversation with karl about crafting our own path in the age of technology. How can we use what technology brings to leaders as individuals and to the workplace ?
Many of us fall into autopilot mode, driven by societal pressures, especially in large organizations, and we discuss work being defined by life experiences rather than the other way around.
Amidst rapid AI advancements, human resistance to change is natural—our survival instincts kick in - but instead of merely managing technological changes, we should embrace them. There is a lack of AI expertise among many leaders and we need to help foster a culture of learning and risk-taking, moving away from traditional education to collaborative learning. This shift promotes inclusive conversations and empathy, crucial elements in a world increasingly influenced by AI. AI should enhance decision-making, not replace human judgment.
Karl shares his stories, experience and insights from setting up his innovation factory and working with leaders and youth all across the globe.
The main insights you'll get from this episode are :
- Innovation requires an atypical mindset and not accepting the norm – there are always alternatives, which can be more challenging but also more rewarding; taking a ‘detour’ prevents autopilot and keeps the brain active.
- We have evolved over millennia to follow the norm in order to save energy, avoid risk and survive; it takes a long time to change mental models, particularly compared to the exponential speed of tech and, more recently, (generative) AI.
- Boundaries and limitations have been removed to make way for AI, but this involves bypassing safety features. What does that mean for humans? We like to feel in control, although we don’t always fully understand the technology.
- There are inherent problems and risks, and the challenge of AI in business is how it will be managed from a legal standpoint; companies should try out new technology on mock data first, then use AI to make the solution more efficient.
- We must let AI strategies emerge using synthetic data to then make decisions about which AI-enabled tools will be most beneficial - leaders often do not understand enough about AI and should work closely with those who do.
- Leaders must be comfortable with not knowing and feel free to ask ‘stupid’ questions on a development journey – the teacher/student approach doesn’t work with AI as everyone must play around with it together to find answers.
- The hierarchy of leadership will be partly managed by AI (algorithms), i.e. an AI decision support engine, that will redefine boundaries; AI will treat us as humans if we treat it as human.
- The ‘innovation factory’ initiative is about learning from other entrepreneurs and inventors, and pushing boundaries - cultures can prevent progress and all ideas should be welcome to ‘fail forward’ and add knowledge.
- Aimed mostly at universities, it goes from no idea, to defining, questioning and pressure-testing an idea in order to reshape and repurpose it, and to develop microproducts along the way (in contrast to an accelerator).
- Today’s regenerative approach can involve ‘AI for good’, giving us options for us to then make the decisions, e.g. how can AI prevent war? We can instruct an AI solution to help us do good.
- We still have agency over the technology but will be an AI-enabled society by 2030: AI will help us become more human and less robotic (e.g. robots working in windowless warehouses).
- When we move too fast, we crash; the current rate of change is very fast and we must be able to mitigate the crash, e.g. reducing our dependency on big tech providers by using multiple power sources, platforms and providers.
- Constantly collecting data to train models means that we lose sight of threats, such as a virus manipulating us and the data; we must try to guard against these by trusting our (human) intuition and impulses.
- We can all become ‘micromentors’ to either support someone else or ask for support from someone else - guided conversations are productive and helpful; an education system based on rights and wrongs does not reflect or serve the society in which we live.
Find out more about Karl and his work here :
119 episoder
Dela
