Digital technologies are already in use in many areas of the working world. What is changing, and what effect is this having on the digital working world? By supporting innovative research projects, the Policy Lab aims to elicit findings from a range of disciplines and thereby highlight areas where there is a need for action.
- Project: ai:conomics: Artificial Intelligence and the Future of Work: Evidence from Field Experiments and Administrative Data
ai:conomics: Artificial Intelligence and the Future of Work: Evidence from Field Experiments and Administrative Data
What concrete changes do employees experience when Artificial Intelligence (AI) is deployed in their workplace? The Policy Lab Digital, Work & Society is supporting a research project that accompanies the introduction of Artificial Intelligence in companies. The project will make it possible to examine the effects on employees via experiments, as if working under laboratory conditions.
To date, insights into changes in employees’ work situations caused directly by the deployment of AI applications have been few and far between. Yet bringing in AI can lead to significant changes. Among other things, some employee tasks may no longer be required while others may possibly be added. The demands of the workplace may also change accordingly. This research project thus aims to examine the concrete effects of the deployment of AI in companies. The focus here is on the qualifications required and the quality of the work environment, though employee performance is also considered.
To ensure that the findings are as meaningful as possible, the research team is looking directly at operational practice. By conducting field experiments during the introduction of AI applications, the project is able to isolate the effects as if working under laboratory conditions. This is the only way to obtain an analytical comparison between the respective work situations of employees using an AI and colleagues from the same operational area who have yet to experience the introduction of AI.
The cases examined in the course of the project are supplemented by a co-creative process – in part because in many cases, the introduction of AI in companies is still uncharted territory. This creates a cooperative environment for everyone involved with respect to the introduction of AI technology and the accompanying scientific study. The results of the project are thus geared not just towards the scientific community and political decision makers, but also in particular towards practitioners and decision makers in companies along with representatives of the relevant social partners.
Participants in this research project include scientists from Maastricht University and the Institute for Employment Research (IAB), as well as representatives from zukunft zwei GmbH.
- Project leader: Dr. Marie-Christine Fregin (ROA)
- Link to project home page: https://www.aiconomics.eu
- The automation, digitalisation and virtualisation of the working world as a consequence of the COVID-19 crisis
The automation, digitalisation and virtualisation of the working world as a consequence of the COVID-19 crisis
The COVID-19 crisis had a wide range of short-term effects on digitalisation, the economy and the working world. How can the negative consequences of the crisis be moderated or prevented? Might the crisis also present an opportunity for a socially balanced, inclusive transformation of the working world? The Policy Lab Digital, Work & Society is supporting a research project looking at the transformation of the working world in the wake of the pandemic. The project also considers the influence of institutional frameworks and policy interventions over the course of the COVID-19 crisis.
The COVID-19 pandemic impacted the business sector and the world of work in a wide variety of areas. This research project looks primarily at its effects as regards employment, social security systems, social partnerships and investment programmes.
Among other things, the project examines how automation technologies and digitalisation impact business models, production models and the organisation of work, with an eye to the potential for long-term change. Another focal topic is the influence of the COVID-19 crisis on employment arranged via digital platforms. The analysis also takes an international perspective, posing questions relating to the geographical restructuring of value creation chains (e.g. through reshoring).
Participants in this research project include scientists from the Berlin Social Science Center, the Weizenbaum Institute, the Institute for Innovation and Technology (iit) and the Berkeley Roundtable on the International Economy (BRIE). This international project team is also delivering insights into the differences between the labour, social and industrial policies of individual countries.
- Project leaders: Dr. Florian Butollo, Prof. Dr. Martin Krzywdzinski
- Link to project home page: The automation, digitalisation and virtualisation of the working world as a consequence of the COVID-19 crisis | WZB
- Further information: The Berkeley Roundtable on the International Economy
Digitalisation as a consequence of the COVID-19 crisis and its effects on the labour market
Discussions concerning the digitalisation of the working world have become more important than ever in the wake of the COVID-19 crisis. For example, is the crisis causing any permanent changes in the digitalisation process in companies? The Policy Lab Digital, Work & Society is supporting a research project looking at the effects on the labour market of digital innovations arising out of the crisis.
The onset of the COVID-19 pandemic in spring 2020 was an unanticipated event for the economy, the labour market and society. The subsequent COVID-related economic crisis directly triggered profound changes in the working world. In addition to the urgent issue of crisis management, it is worth considering whether the COVID-19 crisis might be a springboard for permanent changes – especially as regards the digitalisation of companies.
Launched at the earliest possible moment, this research project is investigating the lasting consequences for businesses and their employees of digitalisation in the wake of the COVID-19 crisis. Using information about the level of digitalisation in the company prior to the pandemic, it is possible to examine acceleration of this process – such as due to abrupt changes to business models, for instance. Did companies that had been slow to digitalise catch up during the crisis? Did those already in the vanguard step up the pace? Are the more digitalised companies better equipped to weather a crisis, and is the structural transformation in the labour market growing more pronounced? The project has developed an indicator measuring the extent to which a business has been affected by COVID-19 and applies this to drawing differentiated conclusions with respect to policies for the labour market.
Using an analysis of company investments in digital technologies, the project delivers insights into the consequences for employees. Who will need to adapt in completely new ways? Are existing inequalities being reinforced? Are new ones being created? The analysis will take an in-depth look at changes in job content, qualification requirements and training activities, and also at employment structure.
Participants in this research project include scientists from the Leibniz Centre for European Economic Research (ZEW), the Institute for Employment Research (IAB), the Institute of Labor Economics (IZA) and Utrecht University. The project is creating an exceptional foundation of data for research into the digital working world, bringing together evidence in respect of both companies and employees.
- Project leaders: Prof. Dr. Melanie Arntz (ZEW), Dr. Terry Gregory (IZA), Dr. Britta Matthes (IAB)
- Link to project home page: Research at ZEW
- Further information: initial results from the project will be presented at the Annual Meeting of the American Economic Association.
Data quality in artificial intelligence – the KITQAR project researches quality requirements for the data used in AI training, testing and validation and how these may be implemented in practice
AI applications are becoming increasingly data-driven. The quality of the data used is thus crucial to enabling AI systems to perform well, remain secure and avoid discrimination. The Policy Lab Digital, Work & Society is supporting “KITQAR”, a research project aimed at defining data quality requirements specifically in relation to AI applications for use in various sectors and developing possibilities for implementing these from a technical, legal, ethical and social standpoint.
Artificial intelligence is a key technology that in future will form the basis for a wide range of applications at work and in our everyday lives. For the majority of AI applications, data usage is of paramount significance. However, to date there has been no systematic analysis of data quality requirements and how these can be taken into account in the development and use of AI systems.
This project starts by looking at what quality requirements data should meet and how different aspects of data quality can be made measurable and verifiable. It also takes into account the fact that data may be used in a variety of ways – such as for training, testing or validation – during the development of AI systems. The analysis brings together technical, legal, ethical and social perspectives. This is to be followed by a second stage aimed at developing ways of applying these perspectives, also giving consideration to regulatory context. As such, with respect to the topic of data quality, the project will be able to flesh out in concrete terms the European Commission’s proposals regarding the regulation of AI.
Central to the project is its practical relevance. An exemplary model for AI data quality is therefore being developed. As the project proceeds, this test model will be further developed on the basis of various case studies. Stakeholders will also be invited to work together with the project team and test their particular application scenarios using the model; the test model will then subsequently be refined via feedback cycles.
This research project is being led by the VDE (Association for Electrical, Electronic & Information Technologies). Participants in the project include scientists from the European University Viadrina in Frankfurt an der Oder, the University of Tübingen and the Hasso Plattner Institute at the University of Potsdam.
- Project leader: Dr. Sebastian Hallensleben (VDE)