+ Generative AI and skills in the workplace
Issue 30. This week:
The future of work
Challenges and opportunities shaping Work:life.
🗒 Lifelong regenerative skills development
📕 The Amateur
🔍 Generative AI and skills in the workplace
Trends and signals
Emerging trends in skills, jobs and careers.
🗒 New economic elite
📊 The growing 65+ workforce in the U.S.
🔍 Labour market exposure to AI across countries
Know-how
Practical technology skills and knowledge to utilise today.
🗒 Inbox Zero
📺 Microsoft Copilot meeting recaps
💡 Decision making with a decision matrix
This is the last Edaith brief to be dispatched this year. I’ll be taking a staycation and challenging myself to a few days unplugged.
Wishing you happy holidays and a joyful start to 2024!
Tina
🗒 Lifelong regenerative skills development
In the 1970 book Future Shock futurist Alvin Toffler predicted that “The illiterate of the 21st century will not be those who cannot read and write, but those who cannot learn, unlearn, and relearn.” With this starting point, this RSA commentary puts forward a case for a lifelong ‘regenerative’ approach to skills development.
The skills we need in the workforce are changing at an unprecedented rate (and will continue to do so), the amount of time we spend in jobs is falling, and the duration of our working lives is increasing.
“What this means is that our learning systems should be planning not just for lifelong access to courses, but for a lifetime of learning and learning and learning again… Taking a regenerative approach to skills means accepting that our learning is never complete, but is part of a cycle. Over a lifetime we will work to develop skills, many of which will become obsolete over time, and then we must begin the process again.”
Regenerative skills development also includes the hard work of unlearning skills central to occupations in superseded and unsustainable jobs and industries.
🔗 Learn, unlearn, relearn (Royal Society of the Arts)
📕 The Amateur
Andy Merrifield’s critical theory was an influence in my PhD research in terms of exploring how individual agency might enable the transformation of cities both physically and functionally. This more recent work further develops argumentation for individuals to take action rather passivity, because elevating interests over conformity and authority, especially as a novice, benefits human wellbeing and enables innovative outcomes.
🔍 Generative AI and skills in the workplace
Australia’s Future Skills Organisation has just released a report seeking to better understand the impacts of generative AI technologies on the Vocational Education and Training (VET) system. It builds on work by the U.S. Department of Labor to identify which vocational qualifications will be most impacted by generative AI, such as conversational chatbots, text and image generation.
The primary impact on the training system will be at the university level
In vocational training certifications, the higher the skills level, the higher the likely impact of generative AI
The qualifications expected to be most impacted are Financial Services, Business Services and ICT
Although ‘impact’ could be automation, for work that is currently highly skilled ‘impact’ will most likely be augmentation and adaptation of tasks for greater productivity.
For example, generative AI can speed up repetitive communications and administration through use of generative text, more efficient sourcing and identification of internal and external data needed to complete tasks through natural language processing capabilities coupled with an AI chatbot interface, and greater prevalence of custom software solutions in businesses with the help of generative AI programming tools.
🔗 Impact of generative AI on skills in the workplace (Future Skills Organisation)
🗒 New economic elite
Last year billionaires accumulated more wealth through inheritance than wealth made through entrepreneurship. This was the first time this has occurred in nine years according to a UBS report.
This trend is expected to continue over the next 20 years as more than 1,000 billionaires pass an estimated USD 5.2 trillion to their children, but the heirs aren’t necessarily taking part in the family business.
“More than half of the 53 heirs surveyed are choosing to step away, opting for careers more suited to their own ambitions, skills, and circumstances. There is also a rise in heirs becoming philanthropists and driving sustainable innovation, creating new business ventures, or building on existing ones with a focus on sustainability and philanthropy.”
📊 The growing 65+ workforce in the U.S.
Roughly one-in-five Americans ages 65 and older (19%) were employed in 2023 – nearly double the share of those who were working 35 years ago.
The average annual earnings of older workers lag behind those of younger workers, but the gap is nowhere near what it once was.
Women make up a larger share of the older workforce than they have in the past, representing 46% of all workers ages 65 and older.
🔗 Older Workers Are Growing in Number and Earning Higher Wages (Pew Research Centre)
🔍 Labour market exposure to AI across countries
In this recent IMF Working Paper, worker level micro-data from a handful of Advanced Economies (AEs) and Emerging Markets (EMs) indicates that women and highly educated workers face greater occupational exposure to AI across contexts. Workers in the upper end of earnings distribution are more likely to be in occupations with high AI exposure, but also high potential complementarity i.e. lower risks of job displacement.
Although the research did not identify a straightforward association between age and AI exposure:
“One general observation is that the youngest workers tend to have lower AI exposure than prime-age workers. Moreover, conditional on being in high-exposure occupations, younger workers are also less likely to be in jobs with high complementarity, and thus are more susceptible to potential negative impacts stemming from widespread AI adoption.
🔗 Labor Market Exposure to AI: Cross-country Differences and Distributional Implications (International Monetary Fund)
🗒 Inbox Zero
Over the break I’ll get my inboxes down to zero. I base my process on the gtd (Getting Things Done) framework and do a complete clear-out every few months. It’s worth the effort to reduce the cognitive load, and each delete is so satisfying.
🔗 Getting Your Inbox to Zero (Getting Things Done)
📺 Microsoft Copilot meeting recaps
If you’re working with Teams, you can get Copilot to summarise meetings and email the attendees with a simple prompt. It uses data saved in the meeting channel folder (a meeting transcription is automatically saved there). The recaps can also be used simply for your own information if you were invited to a meeting but didn’t attend.
🔗 Send out meeting recaps in just 2 steps with Copilot (Microsoft, <1min)
💡Decision making with a decision matrix
When there are multiple factors to be considered in decision making, a decision matrix helps to identify the best performing alternative. It requires the allocation of importance to different criteria influencing the decision, because in most cases not all factors in decision making should be considered equal.
In business it’s also called a Multiple Criteria Decision Analysis (MCDA) and can become a complex equation. However, this framework in its basic form is a useful tool for individuals to navigate an important decision, or for building an evidence base for work proposals.
How to use a decision matrix
Identify the criteria: The first step is to define the criteria that will be used to evaluate the options. These criteria should be specific, measurable, and relevant to the decision at hand.
Define the weighting system: Once the criteria have been identified, assign a weight to each one based on their importance. It makes sense if the weights add up to 100%, with higher amounts given to more critical criteria. Another method is to use a ranking system for weighting where the most important criteria is given the highest number (e.g. 5) and then least important the lowest number (e.g. 1).
Rate options: List out all the options that will be evaluated. Using a scale of 1-10, rate each option against each criterion.
Calculate scores: Multiply the rating for each criterion by its weight. Once all weighted scores are completed, add up the weighted scores for each option. This will give a total score for each option and indicate the best performing alternatives.
Get Edaith. Be well informed.
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