Discover #goodAI
Research at CHEMISTREE
CHEMISTREE relies on research as an integral part of product development. The focus is on the development of responsible and human-centered AI that supports companies and individuals alike. The approach is based on interdisciplinary collaboration with universities, research institutions and practice partners to create scientifically sound and practical solutions.
A central aspect of this research is the development of what we at CHEMISTREE call #goodAI – artificial intelligence that is transparent, fair and ethical. This requires not only technical excellence, but also a deep understanding of social, legal and economic implications. CHEMISTREE brings these perspectives together and ensures that innovative technologies offer real added value.
Main research areas
CHEMISTREE’s research work focuses on the development of intelligent matching technologies that meet ethical standards and regulatory requirements.
This includes the following areas in particular:
Bias reduction and fairness in algorithmic decision-making systems
Transparency and explainability of AI-supported matching processes
User-centered design and acceptance of AI-supported systems
Regulatory and ethical framework for AI in recruitment
Research projects
CHEMISTREE is the initiator and consortium partner in several research projects dealing with the development, optimization and ethical design of AI-supported technologies. Particular emphasis is placed on scientific foundation, practical implementation and social responsibility. The following projects provide an insight into CHEMISTREE’s current research work.
KIDD – AI & Diversity (2020 – 2024)
The KIDD (Artificial Intelligence & Diversity) project, funded by the Federal Ministry of Labor & Social Affairs, is investigating how AI systems can be used in a non-discriminatory and diversity-promoting manner. It combines scientific analyses with specific practical use cases and develops tools for monitoring and optimizing AI-based decision-making processes.
Core objectives of the CHEMISTREE experimental room
- Development of methods for the identification and correction of bias in AI systems
- Promoting diversity through fair matching processes
- Creation of a framework for non-discriminatory AI-supported
personnel decisions - Integration of control mechanisms to ensure that AI systems respect the social values of equality and equal opportunities
Publications
Our KIDD-Learnings
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AI cockpit (2023 – 2025)
The research project KI-Cockpit (KI-C), funded by the Federal Ministry of Labor and Social Affairs, is concerned with
the transparency and control of AI decisions. The aim is to develop a user-friendly interface that enables companies and HR experts to understand and control algorithmic processes in a targeted manner. This ensures that AI-supported decisions remain comprehensible and trustworthy
Core objectives of the CHEMISTREE Fieldlab
- Development of an intuitive user interface for the
control of AI-supported processes - Providing real-time transparency on AI decision-making
- Implementation of control mechanisms to adjust and correct AI decisions
- Promotion of an interactive feedback system that enables users to influence the algorithms and help shape their development
Publications
Book contribution – AI in human resources 2030: The desired future | Whitepaper – An AI cockpit for employees.
Our KI-C-Learnings
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Studies
CHEMISTREE conducts scientific studies to analyze the impact of AI on decision-making processes and their acceptance in various application areas. By collaborating with renowned research institutions, we gain practical insights that contribute to the further development of fair and transparent AI technologies.
LMU study by CHEMISTREE (2018)
CHEMISTREE is working closely with the Ludwig Maximilian University of Munich to gain scientifically sound insights into the impact of AI in personnel selection. This study examines how algorithmic matching processes influence decision-making and which factors are decisive for high user acceptance.
Focus of the study:
- Analysis of decision-making processes in AI-supported matching systems
- Investigation of bias mechanisms and their reduction
- Evaluation of user acceptance and confidence building in AI processes
- Development of best practices for the use of fair and transparent AI in recruitment
Future Report HR Tech (2024)
In cooperation with the Institute for Innovation & Technology (IIT) and the ZP Europe trade fair, CHEMISTREE is developing the Future Report HR Tech. This study examines current and future developments in the field of HR technology with a particular focus on artificial intelligence. The aim is to provide companies and HR managers with well-founded insights into technological trends, opportunities and challenges.
Focus of the study:
- What role will AI play in the future world of work?
- How can companies shape technological change sustainably?
- What are the ethical and regulatory challenges?
Conferences
CHEMISTREE is actively involved in specialist discussions and knowledge exchange at renowned conferences. The direct dialog with experts from science, industry and practice makes it possible to help shape new developments in AI-supported recruitment and to present current research results. These events offer a platform for interdisciplinary exchange, the identification of new research needs and networking with relevant stakeholders.
AI & People Management Conference (2024)
The AI & People Management Conference was organized by the Max Planck Society and the Münchner Kreis in cooperation with CHEMISTREE in Berlin in February 2024 and was dedicated to the task of creating an interface between artificial intelligence and HR management. CHEMISTREE contributed its expertise to discuss forward-looking approaches for the responsible use of AI in HR processes. The focus was on topics such as transparency, fairness and regulatory frameworks. Insights from research and practice were shared and solutions for the challenges of digital transformation in HR were developed together.
Accompanying contents of the conference
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