Which data processing systems are used in companies today? What functions does the software available on the market offer? How do these technologies affect workers? To what extent do they change or strengthen the power imbalance between the company and employees? And where is the journey going?

Due to the rapid development of information and communication technologies, the collection of data about employees is becoming more and more part of everyday business life. Comprehensive digital logging of work activities quickly becomes permanent monitoring and control that deeply encroaches on the rights and freedoms of those affected. The opportunities and risks are unevenly distributed. While operational processes are being optimized, employees come under pressure – and under general suspicion. Companies use permanent data acquisition not only to sanction misconduct and to evaluate performance, but increasingly as a basis for partially or fully automated decisions that have a direct impact on the everyday work of employees. The systems used are often complex and non-transparent, the pace of development is high. Ten years ago, for example, it was difficult to predict how much the smartphone would change our everyday lives – including in the world of work.

The present study gives an overview on 150 pages of digital monitoring and control in the workplace and of the processing of personal data about employees in the company. It documents, systematizes and maps relevant technologies, systems and current developments with regard to their effects on employees – across industries and areas of activity, using many case studies and in a form that has so far been missing in the German-speaking area. The study is based on several years of work on the subject and is one of the results of the “Transparent Workforce” project, which was carried out by Cracked Labs in cooperation with the two Austrian unions GPA and PRO-GE and supported by the Work 4.0 digitization fund of the Vienna Chamber of Labor.

At the center of the investigation

The question was: What functions and technical possibilities does software offer that companies can use today, and how is data about employees processed? In some case studies, a deployment in Austria and Germany is legally difficult to imagine. But common systems such as Microsoft 365 or SAP also process data excessively today. Assessments of the data protection and labor law admissibility of the documented examples are largely excluded and could be the subject of a follow-up study. In addition to nine case studies on systems available on the market and two case studies on data practices at Amazon and Zalando, a map was developed that gives a systematic overview of operational data practices and systems. As part of the project, Hans Christian Voigt carried out a smaller study based on interviews with works council members. The result are five case studies on the specific use of data processing systems in Austrian companies.

The full version of the study is available as a PDF download ; a summary can be found below.

For more information see https://crackedlabs.org/daten-arbeitsplatz

Cracked Labs is a small, independent research institute and creative laboratory based in Vienna that deals with the interactions between information technology and society. The non-profit association was founded in 2012 as part of the development of the online game “Data Dealer” and in recent years has developed into a global competence center in areas such as surveillance, data protection, tracking, algorithms, platforms and the economy of personal data.

The post Digital monitoring and control in the workplace. From the expansion of operational data collection to algorithmic management? A study by Cracked Labs, September 2021 appeared first on EMFSA.

https://www.nature.com/articles/d41586-021-00868-5

Kate Crawford

During the pandemic, technology companies have been pitching their emotion-recognition software for monitoring workers and even children remotely. Take, for example, a system named 4 Little Trees. Developed in Hong Kong, the program claims to assess children’s emotions while they do classwork. It maps facial features to assign each pupil’s emotional state into a category such as happiness, sadness, anger, disgust, surprise and fear. It also gauges ‘motivation’ and forecasts grades. Similar tools have been marketed to provide surveillance for remote workers. By one estimate, the emotion-recognition industry will grow to US$37 billion by 2026.

There is deep scientific disagreement about whether AI can detect emotions. A 2019 review found no reliable evidence for it. “Tech companies may well be asking a question that is fundamentally wrong,” the study concluded (L. F. Barrett et al. Psychol. Sci. Public Interest 20, 1–68; 2019).

And there is growing scientific concern about the use and misuse of these technologies. Last year, Rosalind Picard, who co-founded an artificial intelligence (AI) start-up called Affectiva in Boston and heads the Affective Computing Research Group at the Massachusetts Institute of Technology in Cambridge, said she supports regulation. Scholars have called for mandatory, rigorous auditing of all AI technologies used in hiring, along with public disclosure of the findings. In March, a citizen’s panel convened by the Ada Lovelace Institute in London said that an independent, legal body should oversee development and implementation of biometric technologies (see go.nature.com/3cejmtk). Such oversight is essential to defend against systems driven by what I call the phrenological impulse: drawing faulty assumptions about internal states and capabilities from external appearances, with the aim of extracting more about a person than they choose to reveal.

Countries around the world have regulations to enforce scientific rigour in developing medicines that treat the body. Tools that make claims about our minds should be afforded at least the same protection. For years, scholars have called for federal entities to regulate robotics and facial recognition; that should extend to emotion recognition, too. It is time for national regulatory agencies to guard against unproven applications, especially those targeting children and other vulnerable populations.

Read more at: https://www.nature.com/articles/d41586-021-00868-5

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