Automation in the Workplace: How to Bridge the Digital Skills Gap

Artificial Intelligence, Digital Transformation | 0 comments | by Erin Quilliam

Technological advances such as AI and automation in the workplace are blurring the boundaries between the physical and digital world are pushing us into the fourth industrial revolution.

The effects of this revolution are difficult to predict and fill many with trepidation just as it does excitement.

One of the most frequently asked questions, and growing concerns amidst these technological advances, are if automation and AI will replace jobs.

will AI answerthepublic

You need only see the data for a search of “AI” on answerthepublic to see there is a growing concern that AI will take over the world and our jobs.

But how justified are these fears? Should we be worried that our own technological prowess will put us out of work within the next few years?

In short, no.

To Understand the Future, Examine the Past

As we have already said, this is the fourth industrial revolution.

While previous events did not see the adoption of AI, they were still the effect of introducing technological advancements to the workforce in order to increase productivity.

To understand the possible outcome of the introduction of automation and AI in the workplace, we must look to the past to find any patterns that could help predict the outcome of this new revolution.

Human Invention Has Always Had a Key Purpose

In fact, you could look at any industry, any invention, any technological advancement throughout human history. There is one striking similarity in purpose across all of them.

All human invention is to allow us to complete tasks better and more efficiently. Across industries, we create new methods and machines that will eliminate labour, minimise the time we take to do things, and increase our effectiveness.

For example, the use of AI in the medical industry means we can identify new methods of cancer diagnosis and treatment due to the vast volume of data it can handle, and the speed and efficiency it employs in pattern recognition.

Meanwhile, far more humble inventions like the microwave and the vacuum allow us to carry out household tasks in less time. And in the case of the vacuum, much more efficiently than the manual alternative.

From ready meals to machine learning, we are continually creating novel ways to save ourselves time. We strive for convenience and efficiency so we can better use our time elsewhere. Be that spending it with our families, or working on other projects.

Previous Shifts in the Workplace Had Similar Effects

One of the most seismic shifts in society came as a result of the introduction of machinery in agriculture.

In the United States in the middle of the 19th century, 60% of their workforce was in the agricultural sector. By 1970, that number shrank dramatically to just 5%.

Despite this significant drop in the number of agricultural workers, there is still enough food produced to feed the nation. In fact, food production has increased tenfold. Nowadays, a fewer number of people are able to create higher quantities of food due to the introduction of more efficient farming methods and machinery.

For example, Maine’s blueberry industry has been able to increase production by up to 30 million pounds per year, whilst reducing worker numbers from 5,000 to 1,500 in the same period.

However, we don’t seem to dwell on this radical shift. Despite the fact that in the case of farming, it was so significant it changed the face of society.

Replacing Man With Machines Can Create a More Valuable, Educated Workforce

Former education secretary Alan Johnson defended the recent change in extending the age of compulsory education in the UK. He referenced the decline in “unskilled” jobs and claimed that young people must be equipped to meet the demands of modern employment.

The decline of “unskilled” jobs isn’t strictly true, as we have already explained. The demand for “unskilled” work in the form of lower-wage jobs has been increasing dramatically.

However, the decline in jobs comes from mid-level work, which did not necessarily require higher education nor a specialised skill to carry out. These are the clerical jobs and sales jobs which have been displaced due to specialist software, automation, and AI. This is where the “gap” is forming, and we will return to this problem shortly.

Automation in the Workplace: How to Bridge the Digital Skills GapWill Automation Replace Jobs and Increase Unemployment-minWill Automation in the Workplace Replace Jobs and Increase Unemployment?

The increase in the use and complexity of technology since the 90s has already displaced many people from work.

This is best explained by David Autor, Ford professor of economics at MIT. He explains how and why there has been this displacement of work and polarisation in the growth areas of work available.

“There’s lots of employment, there’s lots of jobs. But, it’s a different type of work.”

There is no lack of jobs, and there is no threat of running out of jobs. However, there is a lack of middle-skill (middle-wage) jobs due to the polarisation effect Autor describes.

Bringing further technology such as AI and automation into the workforce may exacerbate this effect.

Some work will be replaced with AI, that’s a given. But when artificial intelligence is more successful and more efficient at completing certain tasks, it’s no wonder we want to employ it there. However, it has distinct limitations even where it can work far more productively than humans.

An Example of AI at Work-minAn Example of AI at Work

Take pattern recognition, for example. Artificial intelligence can complete these tasks out with an accuracy rate, admittedly, only marginally higher than that of humans.

For example, the Sketch-a-Net programme was designed to identify objects in drawings, and the computer was able to correctly identify 74.9% of the objects, while humans only managed to identify 73.1%

Meanwhile, the ImageNet challenge was created to test the latest algorithms and how effective they were at object detection and image classification. For years, humans won. But in 2015, Microsoft finally created a deep-learning algorithm that beat the human participants. Within a few months, they created an even more effective algorithm. It had a 3.5% error rate in image classification, whereas humans sat at around 5%.

The error margins between man and machine remain small, but the key difference is the time taken to carry out the same task. If asked to sort large quantities of photos, the algorithm will always be more efficient, taking far less time.

Therefore, it would make sense to employ these algorithms to carry out the work. They’re more productive, and the time saved can be allocated elsewhere to further boost value and productivity.

Automation in the Workplace: How to Bridge the Digital Skills GapAI Can’t Replace Humans for Everything

Image classification is a specific task, however, it is not an entire job role. Not to mention the actual task is very time-consuming and repetitive.

This is representative of the kind of work AI is effective at. The repetitive tasks. Ergo, if your work is easily repeatable and regular, there is the risk AI could be implemented to carry it out instead.

Machines have simply become more efficient, if not more effective, at menial tasks. Typically, they’re both.

This is why those middle skill-level jobs have been in decline. Tasks like sales can now be carried out without human involvement, thanks to specialist sales software like Zendesk, or bespoke solutions.

And while artificial intelligence and automation might be great at sorting vast volumes of data quickly, they are incapable of a lot of things, or simply suck at it.

Robots, AI, and Automation Sucks at Some Stuff

For example, AI cannot have common sense. Nor can it be flexible, or dextrous.

This explains why there is continuing growth for some of these “low-skill” jobs that require human manipulation, work like cooking and cleaning. Robots and AI do not have the required fine motor skills, adaptability, or intuition that are required to complete these tasks effectively. As such it is far less efficient, as well as being more expensive than human labour in these scenarios.

The other side of this is that it should put increasing value on our own humanity within the workplace.

As automation and AI take over the menial tasks, people can be utilised in tasks and processes that are more valuable to the business.

Automation in the Workplace will Increase the Value of Humanity

A great example of this comes in the medical industry. With adequate use of AI, a radiologist won’t have to spend hours sifting through scans to identify anomalies. Instead, an algorithm can carry out the initial investigation with a higher degree of accuracy and taking less time to do it. The radiologist can then use the time saved to better analyse the anomalies found, identify patterns, and dedicate more time to their clinical work. It’s another case of increasing the time available to them which they can use on more valuable work.

Here’s another example. Marketers won’t have to sift social media for instances where their company’s branding has been used, or their company name is mentioned. AI can identify the use of certain images, meaning employees can use their time for more fruitful work, such as the actual human interaction with followers.

Time is the most precious commodity on the planet. It is finite. We can’t print or manufacture more of it, nor buy it. That’s why human invention has focused so much energy into finding these novel ways to save time so that we can use it elsewhere.

This refocusing of time not only provides greater value to the business but to the workforce itself. These benefits are two-fold.

Firstly, the use of AI and automation will benefit employees because the work they will be undertaking will become less mundane, less routine, and more challenging. Thus, creating more exciting and rewarding employment.

Secondly, the increase of time and decreased need for menial work creates the opportunity for upskilling. This is driven by what we discussed above, and the changing value of work. As businesses move employees to new areas, they will then learn new skills.

This Was Already Demonstrated with the Introduction of ATMs

A great real-world example of this is highlighted in David Autor’s Ted talk as he discusses the banking industry and the introduction of ATMs.

The introduction of ATMs meant that fewer cash-handling tasks were being carried out by bank staff. But despite fears that these machines would make the staff redundant, it actually increased their value. Not to mention, the number of people employed as tellers actually increased following the introduction of ATMs. This is bevause it became cheaper for banks to open new branches.

The people were no longer required to carry out cash handling, but they did not lose their jobs. The purpose and role of the employees within the branch changed. They still handle some cash, but their prime function shifted. Instead, they became spokespeople and advisers for the business and selling new products.

It made their work more important, and less banal, as it was centred on driving value for the business. The ATMs freed up their time from the simple, repetitive tasks. This allowed them to upskill, or simply dedicate more time to the more important work they already carried out.

In fact, it wasn’t until the dawn of the smartphone that we saw the decline in bank branch numbers. Ever since the first iPhone was released, branch numbers have steadily declined. Even the relatively new online banking was soon hugely overshadowed by mobile banking.

Automation in the Workplace: How to Bridge the Digital Skills GapThe Digital Skills Gap-minThe Digital Skills Gap

As we mentioned previously, there is a decline in the demand for mid-level jobs. Meanwhile, there is an increasing demand for workers at each end of the worker scale, the low-level and high-level jobs.

This gap is due to increasing efficiency and dependence on digital tools to carry out tasks, such as CRM systems. Additionally, the introduction of new tech like AI and automation in the workplace further increases productivity.

Additionally, the digital world has moved at such a fast pace, that it can be difficult to remain on top of it. Even some millennials struggle, as the ICT lessons they had in school are now entirely inadequate for the modern workplace. Where they learned word processing and the basics of spreadsheets, these skills are necessary but insufficient in most lines of work. More and more workers are being asked for more advanced knowledge, like coding. Or they must be developing expertise in niche fields that have only emerged in the last decade or two, such as UX.

In the case of many older workers, they too will lack adequate digital skills. However, this is also the age group that dominates the higher-levels of companies.

The digital skills shortage affects every age and every gender. And as our technology and methodology continue to improve at a rapid pace, this gap will only widen.

How to Use AI to Help Solve the Digital Skills Shortage

As we have said many times now, the key purpose of most digital advances is to save time.

As AI and automation in the workplace deplete the necessity of human involvement in some tasks, that time saved can be allocated into retraining and upskilling. This will be key to tackling the digital skills gap. Things like giving employees the time and resources to learn how to code, or how to conduct UX research.

For those with specific and specialised digital skills, such as developers, they can have their pick of work. There are more jobs than there are people to fill them, which creates fierce competition. As finding the right talent becomes more difficult, it becomes imperative that companies realise that people are the most valuable asset they have. They must dedicate the adequate time and training to allow their employees to improve and to help solve the shortages.

Of course, another problem of this skills shortage is a shortage of AI programmers. Which means starting to learn about Artificial Intelligence could be a savvy move to try and stay ahead of the curve.

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