The authors examined around 200 research projects to assess the viability of algorithmic management. They identified 16 projects and two platforms that relied on automated management to some extent. They found that projects using AI management tend to be larger and associated with platforms, due to the benefit of shared technology infrastructure. However, they caution that such systems raise ethical and legal questions about worker exploitation and control over data about their skills, motivation, and performance.
Key takeaways:
- Researchers at ESMT Berlin argue that AI can help manage research projects, allowing them to operate at greater scale and efficiency than human stewardship.
- AI-based tools can augment human work by accelerating reviews of scientific literature, identifying research questions, assisting in data processing, and predicting innovative drug compounds.
- Algorithmic management has the potential to improve productivity in scientific research by managing complex, large-scale projects.
- There are ethical and legal questions about exploitation from motivational mechanisms and worker control over data about their skills, motivation, and performance in the context of AI management systems.