The AI revolution

By Christian Heinrich
The force with which artificial intelligence is penetrating nearly all areas of life is awesome. Self-learning systems are fundamentally rearranging everyday work as well. What adjustments do employees and their leaders need to make to master that transformation?
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In industrialization, the development of the steam engine was a game changer replacing tedious manual work by automated processes. The development of electricity, of assembly lines, robots and computers resulted in further radical changes. So, now artificial intelligence is upon us and if we choose to believe the global tech elite and the headlines of the news channels this technology will not just entail radical change but unleash centrifugal forces.

The rotational speed at which AI is radically changing life on our planet is so high that the said global tech elite just recently called for hitting the development brakes. 1,000 individuals signed a corresponding manifest of the Future of Life organization: Apple founder Steve Wozniak, Tesla CEO Elon Musk, deep learning pioneer Yoshua Bengio and several developers from Google’s AI subsidiary DeepMind. Their core demand is that “Powerful AI systems should be developed only once we are confident that their effects will be positive and their risks will be manageable.” The main reason for their concern is that AI programs such as ChatGPT can simulate human interaction and create text, images and even videos based on a few cues. Those are skills that in combination with criminal energy pose a risk to our society particularly since legislation governing the use of AI hardly exists anywhere in the world. Such legislation is urgently needed because the AI genie has long been released from the bottle and may possibly be tamed but not be locked up again.

AI has long arrived in the world of work as well. As translators, as programmers, as analysts – AI is doing some of our work in all kinds of areas. Some people would tend to say that AI is taking work away from us. In fact, some jobs will cease to exist – but other and new professional fields will emerge. Provided that artificial intelligence – and let’s just be optimistic in that regard – is properly deployed in business organizations it can raise not only productivity but also the influence and roles of nearly all employees by a few notches: many an ordinary team member may turn into a kind of team leader controlling the work of the AI system while massively boosting their own output. Join us in peeking at the near future that’s already emerging today and that concerns all of us: the following elements describe how artificial intelligence could shape and change the world of work in the short and medium run or is already doing so.

  1. AI makes machines smarter

Organic farming may become even more organic going forward – thanks to artificial intelligence. Programs are already in the making that automatically analyze lettuce heads in a field in order to provide them with just the right dose of eco-friendly pesticides that they need. Not to even mention feeding machines providing farm animals with the ideal quantity and composition of food, and smart combines that autonomously harvest the grain in the fields. The general rule applies that the more data is being collected, in this case for instance by regularly weighing animals or taking soil samples, the sooner artificial intelligence can be used.

This principle applies to many other fields as well. The more sensors are being used, the more data is being captured and analyzed, the more extensively an artificial intelligence “knows” what’s going on and can act accordingly. However, a wealth of available data is not always a prerequisite for using AI. For instance, simple transfers of documents from one file format to another don’t require any big data analysis but merely the ability to recognize a document and its characteristics and content that exists in a specific format and to subsequently transfer it into another format. In that way, with the help of AI, a major problem of our time can be addressed: the so-called “interoperability” of data, which refers to the challenges of data being equally readable on different systems.

  1. AI as assistants to humans

Not only machines can benefit from AI but so can humans. Here are a few examples of AI uses: For attorneys, AI can sift through archives in a matter of seconds to search for previous judgments on comparable current cases. Translation programs such as DeepL help disentangle Babylonian confusion, thus reducing barriers. In financial institutions, artificial intelligence units develop investment strategies and recommendations. And in the field of human resources, AI units search thousands of job applicant profiles and help find suitable candidates.

Basically, the utilization of artificial intelligence is conceivable almost anywhere. Only the scope of its utilization varies. In a software firm, for instance, AI might be doing the main job: programmers assign programming tasks to an AI system that does the programming while humans just check to see where some fine-tuning may be necessary.

However, experts issue warnings: Because an AI unit is only as good as the data with which it has been fed it’s essential to check the results of such systems for plausibility and validity. The tricky part about that is that current AI systems such as ChatGPT know no doubts. When they’re convinced of knowing an answer they’ll announce it with trust-inspiring self-confidence – even if the answer is completely wrong. Since putting ChatGPT to the test has become a popular pastime the internet is full of such false statements issued by the AI. In addition, the utilization of AI increasingly raises ethical questions. Consequently, AI experts not only need to have technical skills but also act according to ethical principles, norms, values or virtues in order to recognize undesirable or even unlawful developments and to curb them if necessary.

And what about an AI system learning so quickly that it no longer wants to be the horse but become the rider? That’s another question requiring clarification in which we should not allow ourselves to be stripped of the reins.

100 million: That’s how many active users the ChatGPT AI software had after just two months, making the program the fastest-growing computer application in IT history.

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  1. Why AI already has more revolutionary energy than automation

The robotic arm on the factory floor that paints one car after the other without complaining. The copying machine at the office that not only copies individual pages but glues them together into a book. The robo chef that stays cool while cooking up one fast food menu after the other at a hot deep fat fryer. Due to progress in automation, humans over the past decades managed to delegate more and more routine jobs – in other words recurring identical “moves” that are clearly defined and delimited – to machines.

AI dramatically extends the opportunities of delegating – beyond the processes that emphasize purely physical action to those of assistive work including participatory thinking. The reason is that AI can handle tasks for which humans would have to spend months or even years on analyzing information and performing calculations. “The strength of AI systems is their ability to analyze and assess large data volumes,” says Rahild Neuburger, a tenured lecturer and researcher at Ludwig-Maximilians University Munich and member of the Learning Systems platform. “Especially with recurring leadership tasks such as creating and managing duty rosters and shift schedules, assignment of tasks, composition and configuration of teams or budget controls, AI systems can be supportive,” she adds.

Beyond routine business functions, AI can be included in mid- to long-term strategic planning. “AI-supported process mining solutions can map, analyze and sustainably optimize business models and processes, Rahild Neuburger explains. AI-created analyses would enable executives to make relevant operational and strategic decisions in less time, estimates the expert. Such agility decisively promotes a company’s resilience. For Rahild Neuburger it’s clear that, “AI systems are not just a new technology. Due to their ability to learn and to draw conclusions practically on their own, they represent a novel element in the organizational and work-related world.”

  1. How AI is changing our daily work and distribution of tasks

“AI changes daily work in various ways. When smart machines assist humans, job profiles, in particular, change,” says Wilhelm Bauer, Director of the Fraunhofer Institute for Industrial Engineering IAO, who, like Rahild Neuburger, is active in the Learning Systems platform where he co-chairs the Work/Qualification, Human-Machine-Interaction working group.

When AI assists humans, the potential for action of every individual clearly increases. “When companies roll out AI, agile project work becomes more important. This is where social, communicative and self-competencies such as self-initiative, creativity or problem-solving skills are in demand,” says Bauer. “To the extent that independent, problem-finding and problem-solving behavior becomes increasingly important, skills that are required for the diligent performance of uniform routine jobs fade from the spotlight,” he adds.

An example from the field: While warehouse workers used to drive their forklift trucks around the aisles and move articles themselves, AI-controlled vehicles are increasingly doing those simple routine jobs for them now. For warehouse workers, that means that they’ve been promoted to the role of team leaders in a manner of speaking: several AI-controlled forklift trucks can work for them while they just monitor the trucks and lend a helping hand in case of problems. The warehouse workers’ productivity increases – as well as their responsibility and use of self-initiative.

This example shows a basic tendency that emerges as a result of the increased use of AI in the world of work: Humans are going to do less and less work themselves, instead using the freedoms gained for greater delegation, checking, problem solving, becoming creative and interacting. And all of it faster and better than ever before.

What may sound like a sobering truth to some craftspeople who enjoy performing hands-on work themselves is of immense and usually welcome help to others because work is not always as poetic and inspiring as it may sound. Warehouse workers are probably happy about no longer having to drive forklift trucks back and forth.

AI glossary
  • Chatbots
    Systems that can dialogue with humans using natural language – creating a bridge of communication so that AI and humans find it easier to engage in exchanges.
  • Cognitive Advisors
    They can recognize context and correlations in larger data volumes enabling them to perform complex tasks and analyses.
  • Robotic Desktop Automation
    Description of the process in which activities of any level of complexity are fully delegated to an AI system.
  • Machine Vision
    A subsystem of AI in which image context and correlations can be detected and classified. Is used in quality inspections, for example.
  1. How AI changes the job market

Neither industrialization, nor automation nor digitalization have bumped humans out of the world of work. The opposite is true: People have never worked more than today. But, like other technological innovations, AI is going to change the world of work. Some jobs entailing plenty of routine work are going to disappear while new ones will be created. An example is data scientists, i.e., specialists creating and maintaining the high-end data bases without which AI applications cannot operate.

“I’m not worried that we’re going to run out of work due to AI deployment,” says human-machine interaction expert Bauer. Employee know-how will continue to be an important asset going forward. Bauer refers to so-called sector or domain knowledge in that regard and gives an example: “For instance, if you want to use AI in industrial manufacturing you need to have in-depth manufacturing know-how.”

On the face of it, a job that used to be performed by three workers now being done by just one thanks to AI doesn’t sound like a socially compatible proposition. However, in view of the shortage of skills in many sectors, efficient use of human resources is the only possible way to sustain processes in the first place.

Rahild Neuburger cautions that management needs to consider the fact that impending changes might give rise to employee concerns such as the question if AI deployment will lead to external control including fears of losing one’s scope of responsibilities. “Recognizing such fears early on and counteracting them is one of the key prerequisites for a successful rollout of AI systems and exploiting their potential. For starters, that calls for appreciating employees and their concerns; as well as for constructively dealing with the resulting anxieties. Such anxieties may possibly be prevented if the benefits and relieving effects of an AI system as a tool can be successfully highlighted. The clearer the value becomes for every individual combined with the reduction of their fear of losing their job, the greater the receptiveness and acceptance among employees are likely to be,” says the expert.

  1. How are we becoming fit for AI?

Central to successful collaboration with AI systems is the qualification of employees. But how can that be achieved? “Including humane job design in the conceptualization right from the beginning is important,” emphasizes Nadine Müller, who leads the Innovation unit at United Services Trade Union ver.di and is also a member of the Learning Systems platform. Müller considers it to be enormously important that employees have influence on the deployment of AI from the outset – because that would prevent them from developing a feeling of subjection. Ideally, management should not just announce the rollout of an AI system in certain areas or processes of the organization but give employees the opportunity to influence and optimize such a rollout. As a result, employees feel less as victims of an externally driven action but as part of a renewal that they decisively co-determine.

Labor scientist Bauer has observed that employees basically are positively disposed toward AI. He says, “The high intrinsic motivation of many AI users when it comes to acquiring new skills is notable. Excellent career opportunities may also be a crucial factor in that regard. That makes it easier for people to successfully master the learning-related requirements.”

A survey among companies has revealed that current qualification concepts emphasize the integration of on-the-job learning and acting, according to Bauer. That should promote the systematic translation of new experiences into practical application. “AI qualification preferably takes place as task-specific on-the-job training or in the form of in-house seminars. Extensive globally available online training programs support such efforts,” says Bauer.

  1. What AI can do for work-life balance

The deployment of AI technologies by businesses could increase their rates of profitability by an average of 38 percent by 2035, according to Accenture research. That’s another number indicating that AI is going to significantly boost per capita productivity. On the one hand, experience has shown that productivity increases don’t necessarily mean less work in the long run. However, because productivity increases are expected to be so extensive this time around it could be that the number of hours to be worked by people will in fact decrease in general. That would support the current trend of younger employees – particularly those of generation Z born around the turn of the millennium – attaching greater value to good work-life balance. One of the most massive changes caused by AI on the job might be that it gives people more free time.

Christian Heinrich
Author Christian Heinrich
For his research for this story, author Christian Heinrich tried out the ChatGPT AI. At first, he was impressed by the smart and creative answers he received even in response to complex questions such as how to get out of having to do gardening work together with his wife. Then he wanted to demonstrate ChatGPT to his eight-year-old daughter. She asked the chat program what the name of Benni’s magical animal in the children’s book series “Die Schule der magischen Tiere” (“The School of Magical Animals”) was. It was the penguin Oskar, ChatGPT answered confidently. Wrong, it’s Henrietta, the turtle. That was disappointing – yet somehow reassuring. It goes to show that to err is not only human …