Which Jobs Can be Taken Over by Artificial Intelligence?

We believe that the skills that mainly revolve around making predictions may be replaceable by machines. Is your job one of them? This blog article presents four implications of AI in the world of work, showing who needs to fear for their job and who can relax in the long run.

Machine learning represents a subfield of artificial intelligence that cannot replace all aspects of human intelligence but instead focuses on the area of making predictions. In short, predictions in the statistical sense use existing data to fill in missing information for the future.

Predictions accompany us in our everyday lives. These could be seen in weather forecasts, traffic predictions or from the arrival of an online order. But in the business environment, predictions are only helpful if they are incorporated into decision making. A prediction has no value if no decision is made based on it.

A prediction has no value if no decision is made based on it.

Moreover, making predictions is only one part of the iterative decision-making process. In addition, other skills are necessary to make an informed decision. For example, the bases for the data must be correct. Past information must therefore be available in an organized and consistent manner. It also still requires the ability to act on a decision and judgment, which means evaluating the benefits associated with different outcomes. Therefore, it is essential to understand that decisions involve various tasks, one of which is making predictions.

We would like to take a closer look at the influence that AI-supported predictions have on various fields of work and which areas of competence are actually at risk as a result.

1. Replacement

One possible consequence of the use of AI in the world of work is one that many may be afraid of: the complete replacement of humans by machines. . Artificial intelligence has already taken over human related tasks. Where people today still perform purely predictive tasks, such as forecasting demand, they will probably be replaced by artificial intelligence very soon. However, this does not mean that the use of AI will eliminate complete jobs, but merely that individual task areas can be performed more efficiently by computers.

At the same time, other tasks that historically have not been considered predictive tasks will be transformed into predictive tasks as machine learning improves and the quality-adjusted cost of prediction continues to decline.

An example of this can be seen in human resources. Applicants are often pre-filtered by an algorithm based on their resume, cover letter, LinkedIn profile, and even interview transcripts. Even in the case of upcoming promotions, intelligence systems calculate in advance which potential candidates would perform better in higher positions.

This is probably the best-known and most widespread consequence of AI in the world of work. In addition to replacing old and entirely new job roles, AI can also ensure that skills change to benefit employees.

2. Automation

Often, it makes more sense to have individual parts of a task performed by machines. This may be because certain tasks may be too dangerous for humans to complete. Utilizing machines minimizes the potential dangers for humans. The automation of non-complex decision-making tasks can increase productivity and decrease injuries and overall costs.

A well-known example of task automation leading to increased efficiency are robotic cleaners. By using predictions and sensors, the robot can calculate the best cleaning path through an unknown space and react to surprise obstacles to make short-term decisions based on altered calculations.

Does this mean that human cleaners will soon be obsolete? Probably not. This is because even if simple tasks such as vacuuming or mopping floors can already be replaced by machines today, human supervisors will still be needed in the long term to check the robots’ work and take over more complex tasks.

We maintain that jobs that are at risk are those that mainly involve predicting things but not the decision-making roles in the company.

3. Improvement

We have already seen that individual tasks can be fully automated. But even those tasks for which this is not possible can benefit from using AI-powered computers.

One possible use case are bail hearings in the U.S court. Here, judges make many decisions every day about whether defendants should spend the time until trial at home or in jail. In doing so, they must consider whether the defendant would flee or re-offend if temporarily released. The use of artificial intelligence could significantly improve the productivity of judges in this regard. This is not because computers should take over these decisions entirely. Instead, algorithms trained with a vast amount of historical data could help make better and more reliable decisions. Judges alone could never keep that much data in mind.

In this case, the judge’s job would not become obsolete, even in the long run. But at the same time, both the judicial system and society would benefit from using AI systems here.

The same is true for sales forecasting. Based on historical sales data, predictions about customer behaviour are made, and the sales team can use this information as support. Will salespeople be replaced? No.

4. Creation of new decision-making tasks

The use of AI systems can also create new decision-making tasks in old job fields at one point or another in the company, or even wholly new jobs whose need previously remained undiscovered.

The new possibilities offered by machine learning are leading to innovations in a wide range of industries.

Imagine an algorithm that can predict fluctuations in the glucose levels of diabetes patients. This could make it easier for people to control their levels and save them from serious complications or hospitalization.

At the same time, this creates a gap in the skills that needs to be filled by new jobs. These include monitoring sensors, analyzing and evaluating data, and providing individual advice to patients on diet and fitness habits.

In part, the uncertainty makes certain activities economically infeasible. The increased certainty provided by AI-assisted predictions opens up new opportunities and tasks.


Predictions by AI – Conclusion

You could see that the use of machine learning applications can lead to more than just substituting human workers.
To be able to assess whether and to what extent your job is at risk from this development, ask yourself the following question: “Does the core competency of my job involve making predictions?” If you answer “No” or “Only partially” to this question, your job is secure in the long term and may not be replaced by a computer. And perhaps you, too, will be one of the people who benefit from the use of artificial intelligence, enabling you to pursue new and exciting tasks in your field of work.


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