Startup interaction with AI - A multiple case study on startups' ethical navigation when using Generative AI tools

Abstract

Due to the rapid development of Generative AI, there are still large gaps in the research landscape of AI, sustainability, and entrepreneurship. Which makes it hard for businesses to navigate and act responsibly. Both when it comes to adopting Generative AI, assessing social sustainability performance and benchmark progress over time. This master thesis seeks to delve into the intricate relationships between Generative AI, ethics, and startups. By examining the current landscape, ethical frameworks and emerging best practices, this study aims to shed light on how and if startups navigate the challenges of Generative AI and integrate sustainable and ethical principles into their Generative AI strategies. The study also intends to explain how startups plan to develop their navigational initiatives and how they can reach those plans. The research is made with a qualitative approach and multiple case study design. The results of the 15 semi-structured interviews showed that informal and individual navigation initiatives are the most common when ethically navigating Generative AI tools. Furthermore, it is in the startups interests to develop formal navigation initiatives in the future as well as receiving support from external actors to facilitate their ethical navigation. Additionally, the thesis suggests formal ethical practices that startups can implement and highlights the factors affecting the current navigational practices.