Forward-looking leadership lessons for effective leaders using AI emerge through recent conversations with three visionary professors in the UK, including what kinds of jobs are AI-resilient, how to shape education for AI users, and how to use AI to enhance human well-being and thrive while managing risk:
1. What kinds of jobs are AI resilient
In a recent article, Professor David Shrier of Imperial College Business School, along with Julian Emanuel and Mark Harris of Evercore ISI, wrote about AI-resilient jobs. The team has 160 million U.S. Occupations, which aggregated educational and economic data spanning 20 industries, 250+ subsectors and 800+ occupations, examined how workers used 52 competencies in 41 activities to complete their jobs. Their analysis found that cognitive abilities (such as information ordering and memorization) are more at risk of being outperformed by AI than by humans.
In contrast, creative- or power-based abilities (such as originality, verbal expression, or explosive energy) are at low risk of being replaced by AI. The more social interaction and empathy required for the job, the lower the risk; And, the more physical labor a job entails, the less risk it poses (subject, in the latter case, to the possibility of robotic automation).
From an industry perspective, AI risk to jobs is greatest in high-value-added service sector jobs such as law, computer and math, and business and financial operations jobs; And this risk is low in most manufacturing-based sectors. Overall, researchers estimate that productivity AI-powered tools could control an average of 32% of every job function across the US economy to improve productivity.
By 2032, $12 trillion of global GDP will be generated by incorporating and applying artificial intelligence. With such large-scale disruption, effective CEOs and boards of directors are building capabilities and immediately launching AI initiatives to remain competitive.
2. How to shape AI education for users
Durham University Professor Sue Black, OBE, award-winning computer scientist, champion of women in STEM and digital skills expert leading the campaign to save Bletchley Park in the UK. In a recent article, he outlined several key principles in shaping education for AI users. First, help users understand that the technology isn't usually the problem, but the way people use it can be. It is essential that those using the technology understand what it is intended to do.
(for example, generative AI is not a search engine; it is sentence and code completion), as well as how it is used, who controls it, and who built and tested it. For example, users need to understand why productive AI creates “illusions” and how to reduce them. Second, identify biases in computer data and models. When Sue Black's team first got into generative AI models, they found the tools powerful and potentially positive; However, when investigating whether any type of prompt induces bias, it only took a few prompts (and a few seconds) to identify the bias.
Effective leaders educate as many people as possible about the risk of bias so that users can identify and address bias before it starts. Third, support AI users to be continuous learners and teachers simultaneously. In today's environment, individuals are constantly updating themselves asking, "What's the latest thing I need to see?" And by the ability to find things for themselves. It is important for leaders and users not to be intimidated by technology jargon or afraid of technology.
3. Using AI to enhance human well-being and flourishing
Professor Keun Ruan of New York University is the CISO of Google Cloud and co-founder of the Happiness Foundation and haia.ai in Oxford, England. In his paper and subsequent book on cybernomics, he sets the scene for better understanding how technology (and AI in particular) contributes to human productivity and flourishing, as well as risks.
He notes that with AI technology, people will work less on mundane and mundane tasks and more on higher-level thinking and problem solving, allowing them to live more productive, healthier and potentially longer lives. Therefore, AI technology (when used appropriately) can create new expectations and discovery. History shows that if tools are used effectively, there are plenty of benefits.
Economic theories for both human and riskFactors suggest that increased education and access to AI will lead to greater and more sustainable economic value. Next, society is at a historical turning point, defined by human relationships with the technological tools they have invented. There is a great opportunity through the collective imagination to reflect and reinvent a growth mindset, shifting focus from external physical production to internal human fulfillment and well-being.
The next phase of the technology-driven industrial revolution is likely to be about human empowerment with technology at the center. Effective leaders identify problems and opportunities as human-driven rather than technology-driven and guide technology (and the people who use it) to solve them.
While it's still early days for productive AI, effective leaders are experimenting with learning in safe contexts and boundaries and are already beginning to apply early learning to practical application in their organizations.
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