Burnt-out syndrome, also known as burnout, is a growing problem among professionals. So much so that the World Health Organization (WHO) has recognized it this year like an occupational disease at the international level, a recognition for which unions and workers in Spain are also fighting, although the Government has not yet responded to these requests.

Due to the increase in this problem globally, several technology companies are developing software tools to detect the burnout of digital workers through their interactions on professional platforms such as Slack, Microsoft Teams or email. Although, at the moment, they only work in the United States.

How does it work? These tools are installed in the company’s professional software and analyze the messages exchanged by the members of the company through the different digital channels. In theory, they do so anonymously and work with aggregated data, in such a way that company managers can access information about exhaustion or discomfort in a team, but they do not receive data from the specific worker who suffers from it.

One of the companies that is developing this type of software, Autumn, ensures on its website that the minimum size of the groups with which its tool works is four people. In AI Scholaranother company with a similar application, the minimum size is seven workers.

When the system detects symptoms of burnout among team members, it automatically sends notifications to all of them to try to improve the situation, which can include reminders about mental health benefits that the company has or suggestions about taking a vacation. The content of these notifications depends on the company, which is the one that has to provide the solutions. The creators of the software point out that their job is only to track the employee’s discomfort.

The training of the algorithms. The Erudit algorithm was created by a team of psychologists and is based on the Maslach Burnout Inventory, a clinical diagnostic tool used to measure job burnout. The creators of this tool then trained it using random messages from social networks to detect cases of burnout based on the meters of the Maslach Burnout Inventory.

In the case of Autumn, the software has been created from the answers of the workers to different clinical diagnostic surveys that are used to measure depression and anxiety, and later the algorithm has been trained through the interaction of various users. with artificial intelligence.

Concerns about privacy. Despite the fact that these companies insist that their software works with aggregated data that protects the anonymity of the worker, their degree of sophistication raises doubts in this regard. Erudit, for example, has a dashboard with real-time data and metrics that allows you to measure burnout levels, employee morale, the impact of a specific event, and, most worrying of all, the level of engagement.

In this way, with metrics such as the level of commitment, the tools that are sold as an aid to combat burnout could also become a source of information to justify dismissals.

At the moment, the development of this type of software is in very early stages and is only being tested in the United States, at least as far as we know. It would be necessary to see how they would adapt to the much stricter privacy regulations of the European Union. In the case of employee performance monitoring tools, which are already used in Spain, the informed consent of the worker is essential, otherwise it is illegal. For these applications that detect burnout the requirement should be the same.

Image | austin distel

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