Bridging the Liability Gap: Ethical Frameworks for AI Outputs in Scholarly Inquiry
DOI:
https://doi.org/10.54878/ss6dym23Keywords:
AI accountability, liability frameworks, ethical AI, research integrity, scholarly inquiry, risk governanceAbstract
The use of AI in scholarly research presents a critical gap in terms of accountability and liability for the potentially erroneous, biased, and non-reproducible research outputs that can emerge from the use of these black box algorithms. The research problem that this paper aims to address is as follows: in the context of AI-assisted research processes and methodologies, how can the researchers and review boards place responsibility for the outcomes? The main research statement is that using comprehensive ethical frameworks for AI in scholarly research can help to close this gap and allow researchers to use the potential that AI offers them. The current guidelines set forth by the institutions do not provide sufficient detail regarding how to incorporate such ethical frameworks into the various types of research. Furthermore, examples from higher education and other institutions reveal that the current reliance on AI to reach conclusions within scholarly research is avoiding necessary scrutiny.References
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