Introduction
One of the biggest topics of discussion at BML is artificial intelligence (AI). Specifically, we obsess on where AI will hit hardest, when it comes to jobs.
Full disclosure – we are interested in this because we work with technology to bring businesses through periods of massive change (BML Digital) and because we find humans to do technology-dominated jobs (BML Work).
Across both of these areas, we are resolutely ‘Team Human’. We have big issues with technology hype around digital transformation. We apply the most human-centric approach to senior technology recruitment in the market.
Don’t get us wrong, we are not a bunch of Luddites. We all pack iPhones, engage in tech-driven side hustles and love Uber and Netflix. But if we can find spots where being human and ‘doing human’ gives an edge over a sea of standardised technology outputs, we are going to be very happy.
Which brings us back to AI. In this case we sought to see if AI could give us any better insight on business issues than our own experience.
We will come back to that word ‘better’ in a bit, but right now, it is enough to set out that we tried to assess if the likes of Bard or ChatGPT could do a better job understanding a business issue, compared to the Mk1 human.
We even gave the AI a boost by picking a subject it should know all about – AI: specifically AI and the impact on jobs.
This is what we found:
AI on AI…
(Created 06/05/2023, using Smith AI with the prompt “What impact AI will have on the job market and include reference data?”)
In recent years, the rise of artificial intelligence (AI) has generated a lot of discussion about the impact it will have on the jobs market. While some experts predict that AI will lead to job losses, others believe it will create new job opportunities by augmenting human skills. Here’s a closer look at the potential impact of AI on the jobs market over the next 10 years, backed by reference data.
Job Losses
One common concern about AI is that it will lead to widespread job losses, particularly in sectors such as manufacturing and transportation, where automation technologies have already been deployed. According to a study by the McKinsey Global Institute, up to 800 million jobs around the world could be impacted by automation and AI by 2030. The report also suggests that as many as 375 million workers may need to switch occupational categories and learn new skills to remain employable.
New Job Opportunities
While AI may disrupt certain jobs, it also has the potential to create new job opportunities by augmenting human capabilities. For example, AI could be used to improve decision-making abilities, enhance customer experiences, and increase productivity. A report by the World Economic Forum (WEF) estimates that AI and automation could create around 133 million new jobs worldwide by 2022, particularly in areas such as data analysis, software development, and cybersecurity.
Transformation of Existing Jobs
Rather than replacing human workers, AI is likely to transform many jobs by augmenting the work that humans do. For example, AI could be used to automate repetitive, routine tasks, freeing up humans to focus on more complex and creative work. A recent report by PwC suggests that AI could boost the economy by up to $15.7 trillion by 2030, with much of this value coming from productivity gains and the augmentation of existing jobs.
Upskilling and Reskilling
With the rise of automation and AI, there will be a growing need for workers to have the skills and knowledge required to work alongside these technologies. This means that many workers will need to upskill or reskill themselves in order to remain employable in the changing jobs market. The WEF report mentioned above highlights the need for more investment in lifelong learning programs to help workers keep pace with technological change.
Conclusion
The impact of AI on the jobs market over the next 10 years remains uncertain. While there is no question that the rise of AI will lead to some job losses, it is also clear that it has the potential to create new jobs and transform existing ones. Policymakers and business leaders will need to take steps to mitigate the negative impacts of automation on workers, such as investing in retraining programs and designing policies that prioritize workers, while also capitalizing on the opportunities presented by these emerging technologies. Importantly, the global workforce will also need to encourage the growth of innovative AI products, which could lead to the development of new job categories, higher compensation, and more economic stimulus.
The above is 759 words written by AI, so we sought to match that. We should also add for the sake of transparency that we went back and added in the links to properly credit the three studies mentioned – but other than that, the above section is all AI.
So now it’s our turn:
BML on AI
You cannot talk about AI without talking about jobs. Technology has always been seen in terms of what it does for humans, and this evolved very quickly, into what it could do ‘instead’ of humans.
This is nothing new. Before Caxton set up his printing press in Westminster around 1475, books in England were copied out by hand, by scribes. Otis’ first steam powered, mechanical excavator was first patented in 1836: prior to that, digging was totally manual.
But it is now 2023 and yes, AI does present some differences to these established cases of machines ‘replacing’ humans.
Firstly, there is the issue of scale. Mckinsey has identified that 800 million jobs around the world will be ‘impacted by automation and AI by 2030’. They also suggest 375 million workers may need to change jobs.
These are not just industry-changing numbers. They are world-changing numbers.
Secondly, AI – like the Internet and the mobile revolution before – is not just going to take jobs away or force them to change. It will create jobs on a massive scale. In 2020, the World Economic Forum (WEF) estimated that AI and automation could yield around 133 million new jobs worldwide by 2022. In 2022 they updated this to suggest that 97 million new roles will be created by 2025 as humans, machines and algorithms increasingly work together.
Getting personal
Whilst instructive, this focus on macro-economic numbers risks a purely quantitative approach to the issue. The fundamental question people ask is not ‘how many jobs will be lost to AI?’ but rather ‘will my job be lost to AI?’. And somewhere as an off shoot of that spectrum, is also the question ‘will AI change my job and if so, how?’
It is all very well to suggest that millions of people will have to change jobs, or to quote a recent report by PwC that suggests that AI could boost the global economy by $15.7 trillion by 2030, driven by productivity gains and AI augmentation of existing roles. But the million dollar question is HOW will these changes been seen and felt.
It makes most sense to identify the areas that AI will undeniably ‘consume’. Data entry, financial processing, data analysis, and first line customer service roles all face a substantial threat. If a job is predominantly driven by a standardised process with clear, defined steps especially if that process is kick-started by technology, then that job is at profound risk. Not to sound melodramatic, but it is just a matter of time.
As AI systems are better trained, this group of roles will expand – although typically at more junior levels. Thus, entry level software coders, trainee legal researchers and content creators focused on social media may become at risk.
At the other end of the scale, there are some jobs that are ‘AI-proof’. Skilled tradespeople (plumbers, carpenters, brick-layers, mechanics, electricians and so forth…) are pretty safe in terms of the job they actually do. High end professionals are also in a good place – especially if that role comes with responsibility for substantial decisions.
Thus, for the vast majority of us, the question is not how AI will make us irrelevant, but more, how we will have to learn to get along with a new, AI presence in our working lives. Gartner reckons that the number of businesses using AI has increased 270% in the past four years, so AI is clearly another ‘new normal’.
There are already some really interesting indicators of how this normal is shaking out. From CEOs giving away entire strategies to drastic improvements in bills of materials built on personalised shopping engines, how someone uses AI is going to be as embedded as how they use email.
The comparison with email is instructive. It has taken 44 years for email to go from inception to more than 4 billion accounts worldwide, and to become (arguably) the dominant method of business communication. No one saw that coming – no one foresaw the impact of the internet and the ease with which we would be able to access emails. So no one speculated and anticipated for the changes.
But with AI we are better prepared. We are already trying to get a grip on what AI is going to mean at the personal, individual level as well as across the planet. Who will be impacted and how are being addressed by the smartest organisations precisely because AI is the latest in a series of profound technological impacts and it is the humans that have learnt what that means.
Conclusion
The original brief for this exercise was to find out what approach – AI or human – led to better insight when addressing a specific business issue. Of course, better is a subjective term, but beyond the fact that AI can likely integrate a greater number of sources, versus the intuitive, human turns of phrase or illustrative metaphors and leaps that AI cannot replicate, it was always going to be inevitable that we would have to conclude that the hybrid approach is now all that is available.
We are already at the point where there are multiple AI systems to choose from, and indeed, there may yet develop and AI arms race for supremacy, but as this project shows, any such winner would still need to integrate with humans in order to effect any meaningful change, be it on the labour market or anywhere else.