WG Objectives
ERIP builds global expertise to address the transformative cross-disciplinary impact of data and AI on research culture (values, processes, structures, perceptions) supported by data and AI integrity for the ethical development of AI in research and institutional assessment framed in human-centric quantitative and qualitative metrics/indicators for data/AI research activities.
ERIP’s mission is to develop policy, guidance, and tools for advancing research assessment that promote the role of, and define the ethical and integrity characteristics of, a responsible culture for the assessment of data and AI in research, fostering responsibility, transparency, and societal benefit.
- To develop ethics and research integrity guidance for research assessment involving data and AI;
- To promote responsible data and AI practices by advocating for responsible assessment practices that prioritize integrity, responsibility, and societal benefit, while mitigating the potential risks and harms associated with data and AI-driven research;
- To foster stakeholder engagement through facilitated dialogue and collaboration among researchers, policymakers, funding agencies, and other actors to ensure diverse perspectives in the development and implementation of ethical research assessment policies;
- To provide a toolkit of educational resources to raise awareness and help implement best practices in research assessment for data and AI; and
- To engage in outreach to shape policy and institutional change, promoting a culture of responsible data and AI research.
ERIP engages the following three focal points in its deliverables:
- Methods and tools to ensure the research ethics and integrity of scientific outputs with the advancing use of data and the impact of AI;
- Methods and tools to evaluate digital contributions to science/knowledge in research program and assessment procedures; and
- Innovative methodologies for employing data ecosystems and AI models for research assessment in digital environments.
ERIP is designed as a flexible community-based working group structure to accommodate the diverse needs, expertise, and perspectives of members, allowing for fair representation and meaningful contributions across time zones and adaptive to the workloads of the experts. The outputs are constructed on the basis of open and transparent inter-institutional, inter-actor, cross-cultural, and multi-regional research and discussion.