The Impact of Information Technology in the workforce

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Introduction

Digitalisation and machines are all around us. In addition to pleasures of better communication and access to intellectual richness of the world, digitalisation is also bringing problems. Addiction, separation from the real life, echo chambers of social media, anonymousness as fertilizer for anger and radicalisation to name a few. Above all looms a growing anticipation of a miracle or disaster the technology is bringing to the employment landscape. If you are an optimist, you are looking forward to the 3 day working weeks and increasing leisure time. If you are an pessimist, you are scared of grim future of unemployment and sustenance provided by our silicon overlord or their capitalist owners. How is it going to be?

Just little bits of history repeating

Digitalisation and machines are not the first and most probably will not remain the last radical revolution impacting human employment and civilization. All started with invention of fire, which facilitate radical change in human evolution and cultural change. Fire provided early humans with source of warmth, protection from wilderness and new methods of cooking food. Fire allowed early humans to conquer the world and gave basis for technological advancement. Fire changed us slowly - the technology of fire was adopted over hundreds of thousands of years and we only know for sure that the modern human had fire in widespread use 125,000 years ago . Back then things were rough - masters of the new technology prospered, and hominid species and human tribes without the technology went extinct.

Fast forward 126,500 years to modern 18th century and the fire brought along a new technological revolution - the 18th century saw the invention and proliferation of the steam engine into wide industrial use . The steam engine started the First Industrial Revolution - within just few generations hand production methods were replaced with machines. Although the First Industrial Revolution brought never-seen access to food and goods, as evidenced by rapid population growth, and raise of the middle-class it was not an easy period for peasants and craftsmen whose skills lost value and market power overnight as new factories were built. We can only imagine the changes fire brought to early humans, but difficulties, riots and wars caused by people made miserable by the First Industrial Revolution are well studied and carved into history books .

The Second Industrial Revolution with is mass manufacture of steel and chemicals brought the same challenges to the 20th century when established scholars, John Maynard Keynes among them defined and started popularising the concept of “technological unemployment” which means “...unemployment due to our discovery of means of economising the use of labour outrunning the pace at which we can find new uses for labour…” And although technological unemployment is widely seen as a sign of rapid economic development and only a temporary condition, it is surely not fun to feel the progress wiping your employment, self-esteem and sustenance. Thus from human perspective anxiety and anger of people fallen behind the curve and desperately waiting - sometimes years, sometimes decades - for the next wave to lift them up is more than understandable. From this moral, humanitarian and pragmatic point of view - growing equality tended to cause social unrest and trigger wars - the social scientist and politicians discovered the need for social transfers from the rich (taxes) to the poor (social welfare).

How many of us will lose the job to the Information Age?

Now humanity is in Information Age or Information Revolution from head to toe. Earlier paragraphs demonstrated that the technology has replace species, humans and employees for thousands of year. Yet the phenomena of machine-human substitution geared up with the Industrial Revolutions has substantially increased with the Information Age. At first the Information Age created new jobs and created a new science-based professional and technical class on jobs (managerial, research & development, design, healthcare). Gradually the technology started to take over jobs from employees resulting in shift of income from labour to business capital and wage stagnation or reduction for employees . The technological development and adoption speeding up at the pace of the Moore’s law has lead to widespread understanding that the technology and automations is capable to disrupt the employment with a same brutal strength as did steam and industrialisation.

How many of us may be adversely impacted by the advancement of technology? How many of us will lose their current work? Nobody knows the development and impact of technology for sure and estimates vary a lot. Very commonly cited 2013 study by Oxford claims that 47 % of US jobs are in the high risk category, meaning that associated occupations are potentially automatable over some unspecified number of years, perhaps as soon a decade or two . Luckily other studies do not draw such a grim picture. Yet even OECD claim that in its 21 member countries 9 % of jobs are automatable, whereas they have established substantial heterogenities across OECD countries -  for instance, while the share of automatable jobs is 6 % in Korea, the corresponding share is 12 % in Austria . Add this to OECD average unemployment rate of 5.2 % and you look at possibly 11-17 % of workforce living on social welfare and being frustrated at the collapse of their hopes and dreams. McKinsey has evaluated that ca 51 % of current work activities are technically automatable and depending on the pace of adoption 400-800 million jobs worldwide could be automated by 2030 .

True, studies also calm the fears and argue that the estimated share of “jobs at risk” must not be equated with expected unemployment rate for three reasons. First, the technological feasibility is just a part of the equation. Adoption of new technologies is a slow process, due to economic, legal and social barriers preventing the adoption of technology at the pace technology evangelist are preaching . New technology is just very expensive to implement and sometime labor is still cheaper, more flexible or has other benefits Second, once the new technologies are adopted, employees can adjust to changing conditions by switching to other tasks tasks, thus not resulting in full technological unemployment. Third, technological revolution inevitably generates additional jobs through demand for new technologies and through higher competitiveness. Based on these reasons OECD is maintaining a relatively sanguine view and argues that automation and digitalisation are unlikely to destroy large numbers of jobs. However, even they admit that a winds of change are blowing and hitting especially hard low qualified workers and people not ready to adopt with new technologies. These people will bear the brunt of the adjustment costs as the automatibility of their jobs is higher compared to highly qualified workers .

What is the mysterious automation threatening us?

The last two decades, humanity has witnessed significant advances in the field of artificial intelligence (AI) and robotics. Future progress is expected to be even more impressive, and soon the development of technology will transform the workflow around the world.

However, recent surveys show a high level of anxiety about automation and other technological trends, highlighting widespread concerns about their impact (Pew Research Center, 2017). Nowadays, there are two opposing views: on the one hand, the impending achievements in the field of AI and robotics mean the end of people's work, on the other hand there is no reason to worry that this time will be different, because technological breakthroughs in the past ultimately increased the demand for labor and wages. Despite these expectations and worries, humanity is still far from understanding how automation and robotics in particular affect the labor market and productivity.

It is impossible to deny the fact that technological development and automation have major implications for labour markets. Assessing its impact will be crucial for developing policies that promote efficient labour markets for the benefit of workers, employers and societies as a whole.

The impact of technology leads to an increase in the relative demand in well-paid skilled jobs, which usually require non-standard cognitive skills, and an increase in the relative demand for in low-paid, least-skilled jobs, which usually require unusual manual skills.

At the same time, the demand for "middling" jobs, which usually require routine manual and cognitive skills, will fall. Researchers call this process job polarization. This process is observed in the United States and in European countries such as France, Germany, Italy, Spain, Sweden and the United Kingdom. In all these countries, the number of high-education jobs such as managers, engineers and medical workers is increasing, while the number of middle-education jobs (clerks, machine operators, assemblers) is declining. By contrast, there are a growing number of professions in the services sector with a low level of education, such as store workers, who are non-standard and difficult to replace with automation. The key conclusion is that the technology was included in a subset of the main work tasks previously performed by middle-level employees, which led to significant changes.

The quality of human capital also plays a crucial role. The ability of individuals to use the technological advances for the benefit of their work requires the development of certain skills in working with digital technologies through well-developed policies. This underlines the importance of using appropriate tools to ensure that workers are well-prepared to use the destructive power of digital technology. Rapid technological progress and innovation can affect employment in two main ways: • by directly displacing workers from tasks they were previously performing (displacement effect) • by increasing the demand for labour in industries or jobs that arise or develop due to technological progress (productivity effect).

Based on these assumptions, the real question arises: which of the two effects of the labor market - displacement or productivity - will dominate in the era of artificial intelligence (AI)? The first approach to answer this question is to study the impact of technological breakthroughs on labor markets during previous industrial revolutions. For example, the introduction of cars in daily life has led to a reduction in the number of jobs associated with horses, but new industries have also emerged, which had a positive effect on employment. The automobile industry itself grew rapidly, creating many new jobs, but other sectors also grew due to the growing number of vehicles on the roads, and many new jobs appeared in the motel and fast-food industry to serve motorists and truckers. The Economist (2016) reports on further case studies that show similar patterns. In general, past industrial revolutions suggest that in the short term, the displacement effect may dominate. But in the long run, when markets and society are fully adapted to the severe shocks of automation, the productivity effects can dominate and have a positive impact on employment. However, how reliable is this approach? Researchers at the McKinsey Global Institute believe that the destruction of society caused by artificial intelligence occurs 10 times faster and 300 times the scale of the industrial revolution of the late 18th and early 19th centuries, and therefore has an effect of about 3000 times. In addition, the main engine of technical progress in the era of artificial intelligence is the continuous development of deep machine learning methods that use the function and complexity of the human brain as a model for design. Machines are trained to be smart, which may have additional implications for the workforce.

What are those industries where humans could be replaced by AI and machines?

So where is the current technology capable to support or even outplay us, humans? The starting point is to understand that every occupation, even the most complicated and artistic one, in fact everything that we do, every process can be cut into several general activities - from predictable physical work, to data collection, to managing others. And technical feasibility to replacing these activities with technology is very different. McKinsey & Company made an extensive study of different professions and impact by technology. And their findings are not surprising: more predictable the activity is, the more susceptible the activity is for automation. Predictable physical work, very high probability of being replaced. Managing other people - can you imagine being managed by Apple's Siri - at the moment not very susceptible. According to the McKinsey & Company study up to 50 % of work can be replaced by the machines. But this does not mean that 50 % of occupations disappear, rather it means that machines will enter to occupations in various degree and change it, but together with people. Let's have look at a possible transformation on the lawyer profession as an example? You can see that legal profession itself is not a solid chunk of art of lawyering. It actually consist of many-many different activities - some technical, some very creative and artistic. Some of these are highly susceptible for technological change - data collection, data processing  - and there are activities which are extremely difficult to replace with machines - interaction with other humans. So this kind of thinking for the future on the example of Legal industry gives us a chance to understand the future workflow processes possible automation. As well as realizing which benefits advanced technologies could create and which rights parts of our work could be replaced with machines. Harvard Business Review has showed once again that the suggestions by McKinsey & Company are in line with what is happening in practice in the real life today. Here are just a few testimonies, which are happening today; a robotic process automation (automating business processes), cognitive analytics (gaining insight through data analysis), and a cognitive engagement (engaging with customers & employees).

Robotic process automation

Let's consider these processes in more detail. Firstly, robotic process automation - RPA is more advanced than earlier business-process automation tools, because the “robots” (that is, code on a server) act like a human inputting and consuming information from multiple IT systems. Tasks include:

• Taking data from one system, and using it elsewhere, no learning functionality;
• Mainly back office administrative and financial activities
• Measuring time worked on a document and automatically prefills timecards in billing system,
• Automated searches across large volumes of documents.

All these processes automation guarantee so to say “lowest hanging fruit” (highest return on investment)  as well as speed and quality. It can be assumed that robotic process automation would quickly put people out of work. But according to HBR review conclusions the replacement of administrative staff was neither the main goal nor the overall result. Only a few projects have led to a reduction in the number of employees, and in most cases, the tasks in question have already been transferred to external workers. As technology advances, robotic automation projects in the future may lead to some job loss, especially in the outsourcing industry of offshore business processes. Obviously  If you can outsource the task, you can automate it.

Cognitive insight via data analysis

cognitive insight via data analysis - advanced technology which allows to analysis of large volumes of data, applying cognitive skills and algorithms getting better at their job. These machine-learning applications are being used to:

• Predict what a particular customer can buy;
• Identify credit fraud in real time and identify insurance claims;
• Analysis of warranty data to identify problems with the safety or quality;
• Automate custom digital ad targeting;
• Provide insurers with more accurate and detailed actuarial modeling.

Cognitive Insight applications are typically used to improve performance on tasks that can only be performed by machines — tasks such as buying software for an ad that includes such high-speed data analysis and automation that they haven't been humanly available for a long time — so they generally do not pose a threat to human work.

Cognitive engagement

cognitive engagement - engaging employees and customers using natural language processing chatbots, intelligent agents.This category includes: • Helping in IT support, predicting the questions and answers; internal HR support the same way; • product and service recommendation systems for retailers that enhance personalization, engagement, and sales; • medical treatment recommendation systems that help providers create individualized care plans. According to study, companies tend to use cognitive interaction technology more often to interact with employees than with customers. In the same time the most advanced enterprises are launching customer service, but mainly for testing. Nobody has switched from actual people to machines in customer services. Harvard Business review further looked at what has been the expected outcome. According to that reduction of headcount is the least important one. Even with robotic process automation only few had target of reducing cost. So the main goal is not cost optimization, but rather quality, reliability, avoidance of errors.

So what's next?

Harvard Business review further looked at what has been the expected outcome. According to that reduction of headcount is the least important one. Even with robotic process automation only few had target of reducing cost. So the main goal is not cost optimization, but rather quality, reliability, avoidance of errors. Main is to release the creative potential of the people, helping people to make better decisions. It is about adding quality of the existing services, improving the lives of our people - one way or another. So, as we can see, the use of this technology does not threaten our existence. There are plenty of opportunities to improve our services to clients, make our work more fun and interesting, more rewarding and meaningful. And we just cannot value based on our current needs - also future employees and future clients will love to work in fun and forward looking environment.