The place of artificial intelligence in the future of work

We are at the pinnacle of the digital society, and digital transformation marks a social paradigm shift that will lead us to a new social order in which information and communication technologies serve as an intermediary to increase people’s productivity in all areas, including work. Digital transformation relies heavily on recent disciplines such as technology. cloudsinternet of things, telecommunications and artificial intelligence (AI).

There is a lot of talk about whether the last jobs will take people, and a lot of fear that all this dizzying technological progress that we have seen in recent years entails.

However, we are very, very far from the fact that artificial intelligence can completely replace people in their activities. Yes, it is true that it will take a bigger place in the technical assistance space. In other words, we will have more AI-based systems that will accompany us in our daily tasks – at work or not – and will contribute to the development of many activities.

We will have smart tools that can do some of them for us because they are repetitive or because they are heavy and low cognitive. Others will simply be simplified because the intelligent system will help us do them together. The greater the cognitive complexity of a task, the more difficult it will be for AI to handle it alone, and this is the protection of our workspace.

Take an example: GPS

GPS is today a well-known and widely used tool for any movement by land, sea and air. We hardly even remember what it was like to travel the world without those devices – handheld or attached to a vehicle – that we consult before we go on a trip and that make us real co-pilots, carry us – without getting anything. lost our way – to places we’ve never been. and so do they.

These are AI systems that solve one of the oldest problems in the field: scheduling. They are able to plot the necessary route to get from where we are to where we want to be, respecting the planes of the terrain without forcing us to cross between buildings or walk down the street in the opposite direction. And they do it on the basis of position sensors and satellite communications.

Have you ever stopped to think about what having GPS meant for the trucking sector? Or for bus rental companies with a driver? Consider for a moment how many drivers have stopped getting lost on the road, wasting time and money on their companies. On the other hand, GPS doesn’t drive and, however complex it may be, doesn’t eliminate the need for a driver and doesn’t reduce the company’s driver fleet.

This is an example of how intelligent systems complement work activities, help improve service quality or productivity, and can lead to job transformation.

In this case, the impact is that the driver is less stressed, he is no longer lost, the shipments arrive at the scheduled time, global deliveries can be better planned because there is less uncertainty, and in the end, all this leads to an increase in the quality of service and improving the well-being of the employee. And, even more, it improves the perception of the client and the positioning of the company.

Benefits of Automation

Other AI systems are completely autonomous and perform tasks on their own, much like robotic vacuum cleaners do when they are about to sweep a house. Or smart forklifts that place goods in warehouses. If rooms sweeping well, it may not be necessary for one person to do the task, and this may have some effect on employment as a domestic worker. But it is much more likely that you will have to learn how to operate a vacuum cleaner. reasonable and that while the robot is vacuuming, it is devoting itself to some other task.

Artificial intelligence has a huge potential to automate some low-level cognitive tasks and can completely replace humans in some of them (for example, sweeping or arranging shelves). But professions carry more tasks that machines, no matter how smart, are very likely not to cover.

What will happen is that the task that the machine takes on (or part of the task that it takes on) will free up time that can be devoted to other areas. You can give some related to different levels of responsibility in the labor hierarchy. The transformation will affect all categories and will allow, among other things:

• Spend more time and get better at the harder parts of the job.

• You will have more time to communicate with colleagues and achieve team cohesion.

• Put more energy into working with the client to better understand their needs and assessments and thus gain more knowledge to improve the product.

• Increasing customer loyalty through better service.

• Open the space for reflection needed to put the situation into perspective, make better decisions, and determine the best strategies.

In short, what should happen is that the time freed up by using intelligent machines can be used to improve the quality of work or service, and people can concentrate on tasks that machines cannot. empathic relationships with colleagues and clients, or better care for the team, which must necessarily lead to better work results.

ethical considerations

On the other hand, there are endless AI-based systems that consume huge amounts of data to get user profiles, learn about their tastes, needs and habits. They can also be used in a production environment so you can, for example:

• Avoid accidents on the construction site because artificial vision sensors anticipate human-machine collision.

• Returning a product because it is no longer offered to a specific customer profile.

• Reduce the impact of sick leave on the team because we expect one of the members to have a heart problem.

It is true that there are many ethical considerations about how and when personal data should be used in AI applications, especially in the work environment, but there are also mechanisms to take advantage of these opportunities without violating the ethical principles promulgated by the European Commission, which proposes development of non-invasive and human-centered AI. In any case, this type of application allows you to increase safety and well-being at work, which again leads to an overall improvement in the organization.

On the other hand, recent advances in natural language or voice processing are also a great opportunity to make many tasks easier or empower some people. Let’s think about, for example:

• Voice assistants that read instructions in repair shops with poor lighting.

• Information seekers who allow us to solve, from the comfort of our desks, problems that we would not solve alone (they are already widely integrated into the working reality of many people).

• Automatic translation tools that allow you to work with foreign clients.

• An overall improvement in the organization through the ability to reduce the management of incidents or emergencies through preventive maintenance systems.

Smarter systems, less human specialization

Digital transformation is driven by strong injections of artificial intelligence into organizations and their processes, it changes the way people work and provides important enablers to make tasks easier by freeing people from lower cognitive level activities, which in turn frees them from time and stress.

In the coming years, we will see a significant transformation of organizations: some tasks will disappear and others more technology-related will appear, although this change will not always be associated with job loss. While this paradigm shift is taking place, we must ensure that the people most at risk of digital exclusion are not left behind because they do not know how to handle technology in their workplace.

While this is the responsibility of everyone, it is interesting to note that at the same time there are changes in the interaction of intelligent systems with people, and less and less specialization is required to use them. Today, many people use GPS, rumbaautomatic translation system or voice assistant without having much technical knowledge.

It is to be expected that interfaces will continue to be simplified, which is a key factor in the overall improvement of the world of work.

This article was originally published in issue 121 of Fundación Telefónica Telos.

Karina Gibert, professor and director of the Center for Smart Data and Artificial Intelligence Research

This article was originally published on The Conversation. Read the original.

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