A lot of critics have expressed their growing concern over the rise of automation because of the potential of machines taking over humans’ jobs. After all, machines are indeed cheaper, more efficient, and better in following instructions than actual workers. However, those afraid of such an “AI apocalypse” might have reason to have hope – as some say while machine may indeed take humans’ jobs, they may also be able to train humans for new jobs.
If studies are to be believed, almost 50-percent of all jobs today could be taken over by automation during the next few decades – and even occupations that machines wouldn’t be easily able to “master” will likely see various changes to their duties and responsibilities by the time smart technology becomes fully integrated into their systems. Given the various improvements in technology today, there’s no way of telling just how “intelligent” machines can change the way work will work for humans, or how jobs of people will be “evolving” with their automated counterparts in mind. While these questions remain plentiful, perhaps one thing is constant: the future of work for humans will be vastly different from before, and workers will need new skills in order to fully embrace this new shard future with machines.
This isn’t the easiest thing to do, however, as this has also created a massive need for companies and workforces around the world to create systems that can help reskill workers and match them with careers befitting their new roles. This is a pressing and difficult challenge, as this involves analyzing huge sets of data and devising ways of integrating a lot of complicated variables.
Interestingly, this is exactly the kind of problem AIs are conceptualized to solve – so why not turn to the very things that can answer our questions? Maybe reskilling can be done with the help of AI?
Thinking about various means to deploy AI to address the various problems automation creates might seem a bit counterintuitive – but the scale of the problem at hand does demand unique approaches. There’s no guarantee if productivity through automation will actually get to make more jobs than it “displaced,” which happened during the last industrial revolution. However, if that historical moment will serve as a basis, there will evidently be a huge skill shift – in both demand and supply.
It doesn’t help that a lot of people have started to become terrified of the prospect either, as 72-percent of people in the United States alone have expressed concerns that machines have begun taking over human tasks in various workplaces.
Meanwhile, job market provider Burning Glass has indicated an increase for “hybrid” jobs, which include jobs that have mixtures of sector expertise and digital skills – such as marketing analysts. The Burning Glass analysis pointed out that very few university degrees can help teach both skill sets, however, and even then only very few certification courses in industries also help improve prospects for employment.
This may leave others to think that automation will then become a zero-sum game, that human workers will eventually be wiped out of the ecosystem. However, the reality is a bit more complicated than that.
It’s important to understand that just because technology adoption exist, it doesn’t necessarily mean human jobs will replace. When the ATM was conceptualized, it was thought of as the “killer” of bank staff – but the ATM’s arrival actually heralded the creation of more bank tellers as well. This is because ATMs reduced the costs of running a bank branch, which means there’s more room to open more banks and hire more people.
In fact, it appears to be very rare for automation to completely remove an occupation. The deployment of AI systems and robotics will only really require a skill shift in the job market, as machines will usually just take over the “routine” parts of their work. This means humans will be more or less left to spend more time on the relationship-focused or creative elements of their jobs. This means bank tellers needed to have less skills to make deposits and withdrawals, and instead have softer skills to help customers and build loyalty with them by giving assistance to other financial needs.
The positive effects of automation can’t be discounted either. For instance, automated platforms run by AI can help save countless lives by making sure minute signs of cancer are detected on medical images. Better protection against cybercrime and mitigating climate change are other things AI could help with as well – as humans may have more rewarding experiences with work once bots and AI take over the more repetitive tasks.
Of course, these positive effects will only take light once the potentially destructive and disruptive effects of AI are mitigated, and people are educated on the transformative values of AI.
Not to mention, AI and automation have various impacts from company to company, and even industry-to-industry. This is why there’s no currently existing way to create a uniform “response” to how career transitions would work with automation in mind. Rather, it may help providing a more personalized strategy for each person first before going through the retraining process of how human workers could create better careers in the future.
The reality of the matter is, a lot of workers globally would have to be retrained – and geographies and industries will have to be transcendent in order to prepare everyone for a more automated future. Helping workers make a case-by-case transition can help companies deliver more hybrid platforms and automated solutions in helping people remain crucial and relevant to the workplaces of the future.
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