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Generative AI in the world of work (GENKIA)

The diverse applications of AI make it very appealing in the workplace. This research project explores the implications for employees, various business sectors, and the quality of work.

Background

With the release of ChatGPT, the potential of generative artificial intelligence (AI) has become tangible to the general public. AI-based chatbots, such as OpenAI's GPT-4, can be used in a variety of ways: they search, analyse and summarise information. They can also generate and revise ideas, text or code for us. The high technological maturity of these AI applications and their versatility make them extremely important for the world of work. In knowledge-intensive professions, generative AI promises more time for creative activities thanks to efficiency gains. On the negative side, however, its use can also lead to the devaluation of human skills or even their replacement. Questions remain about the possible new skills that workers will need when working with generative AI.

For this reason, the research project ”Generative Artificial Intelligence in the World of Work” (GENKIA) is investigating the significance of generative AI for individuals, organisations and professions. It aims is to capture the experiences of workers with generative AI and to analyse possible impacts on employment and quality of work. We will also explore the conditions under which work processes can be supported by the use of generative AI.

Research Work

Generative AI will have a significant impact on knowledge work in particular. Therefore, the research project focuses on five socially relevant domains in which generative AI systems are already being applied:

  • Marketing
  • Human Resource Management
  • Programming
  • Journalism
  • Public Administration

Objectives

  • Gather detailed insights into the user experience of workers with generative AI    
  • Analyse the impact of generative AI on employment and quality of work   
  • Develop of recommendations for good working practices with generative AI

Levels of Investigation

  • The individual level of employees  
  • The organisational level of the companies  
  • The level of professional fields with collective interests and regulations

Methods

  • Literature and document analysis / qualitative interviews with stakeholders
    Identification of domain-specific applications of generative AI and the associated goals, challenges and impacts.
  • In-depth case studies in German companies
    Investigation of the use of generative AI in organisations. This includes examining the challenges and impacts on coordination, quality and work experience. It will also identify factors that help or hinder the contribution of generative AI to good work.
  • Analysis of online forums
    Analysis of conversations in online forums as part of a netnography to identify strands of discourse in the respective professional fields. This will provide insights into the reception of the technology among users, also in an international context.
  • Experimental study in public administration
    Conducting an experiment in local government agencies in Germany to determine how the use of generative AI can affect the productivity of public servants and the quality of work results.
  • Research syntheses on the effects of generative AI
    Analysing the current state of research on generative AI. As part of several research syntheses, we are developing a systematic literature review on the impact of generative AI on work and employment.

Transfer

We communicate the results of the project to academics, policymakers, businesses, public institutions and the general public in ways tailored to each target group. In addition to scientific formats, these include blog articles, policy dialogues and public events. The focus is on the timely transfer of initial project results into the political discourse on the design and regulation of generative AI, in close coordination with the think tank Policy Lab Digital, Work & Society of the BMAS.

Podcast - AI-generated

In this AI-generated podcast, the goals of the research project “Generative AI in the world of work” (GENKIA) are presented and discussed.

Listen now:

Big Tech Versus the Common Good

This policy brief is based on findings from the research project Generative AI in the World of Work (GENKIA). It discusses how the global race for artificial intelligence exacerbates power and resource inequalities, prioritizes the profit interests of major tech corporations, and remains largely beyond democratic oversight.
Florian Butollo, Esther Görnemann

Big Tech kontra Gemeinwohl

Dieser Policy Brief basiert auf Ergebnissen des Forschungsprojekts Generative KI in der Arbeitswelt (GENKIA). Die Autor:innen diskutieren, wie der globale Wettlauf um Künstliche Intelligenz Macht- und Ressourcenungleichheiten verschärft, die Profitinteressen großer Tech-Konzerne priorisiert und bislang einer demokratischen Kontrolle entzogen bleibt.
Florian Butollo, Esther Görnemann

The Symbiosis of Generative AI and Work

The proliferation of generative AI applications (GAI) in the workplace has prompted considerable speculation regarding the future of work. In this paper, we examine the relationship between GAI and work, drawing on theoretical considerations and preliminary empirical insights. Our theses also function as hypotheses for the research project GENKIA, wherein we investigate the transformations in work across programming, journalism, marketing, human resource management, and public administration.
Florian Butollo, Christine Gerber, Esther Görnemann, Lea Greminger, Ann Katzinski, Marlene Kulla, Mareike Sirman-Winkler, Justus Spott

Die Symbiose von generativer KI und Arbeit

Die Verbreitung von generativen KI-Anwendungen (GKI) in der Arbeitswelt führt zu weitläufigen Spekulationen über die Zukunft der Arbeit. In diesem Policy Brief formulieren wir auf Grundlage theoretischer Überlegungen und erster empirischer Eindrücke Thesen über das Verhältnis von GKI und Arbeit, die zugleich als Hypothesen des Forschungsprojekts GENKIA dienen, in denen wir die Veränderungen von Arbeit in Programmierung, Journalismus, Marketing, Personalmanagement und öffentlicher Verwaltung empirisch untersuchen.
Florian Butollo, Christine Gerber, Esther Görnemann, Lea Greminger, Ann Katzinski, Marlene Kulla, Mareike Sirman-Winkler, Justus Spott

Duration: 1 April 2024  - 30 September 2026

Funding: Federal Ministry of Labour and Social Affairs (BMAS)

Cooperation Partner: WZB Berlin Social Science Center, Alexander von Humboldt Institute for Internet and Society (HIIG)