Ghosts in the evaluation machine: ethics, data protection, meta-evaluation, and evaluation quality in the age of artificial intelligence

Abstract Information: The integration of generative artificial intelligence (GenAI) technologies, exemplified by OpenAI's ChatGPT, into evaluation practice presents both groundbreaking opportunities and significant ethical challenges. This evolution in machine learning and AI is changing transdisciplinary evaluation, pushing practitioners, researchers, and organizations to reassess the frameworks guiding quality evaluations in the face of such disruptive technologies. The rapid advancement and application of these tools in Monitoring, Evaluation, Research, and Learning (MERL) Tech practices outpace existing guidelines on their responsible use, underscoring a critical need for updated meta-evaluative standards that address the ethical dimensions of AI-enabled evaluations. This session delves into the juxtaposition of AI safety and AI ethics research camps, emphasizing the latter's focus on the societal and ecological risks posed by current AI technologies, including their potential to perpetuate bias and inequality. It probes into how the data pools underpinning AI tools, reflecting a multitude of human voices and values, affect the integrity of evaluation processes and outcomes. By examining the influence of algorithmic bias and value representation on evaluative quality, this session aims to uncover the voices and values amplified or sidelined by AI in evaluation. Featuring insights from evaluators, data scientists, AI ethicists, and privacy professionals, this multi-paper session explores the theoretical, empirical, and practical aspects of GenAI-enabled evaluation practice. It strives to address pressing questions surrounding the quality of AI-enabled evaluations and offers practical recommendations for evaluators looking to harness technology for enhancing evaluation quality, all while maintaining a steadfast commitment to ethical principles and inclusivity in evaluation practice.