Can large language models help solve the cost problem for the right to explanation?
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View abstract on PubMed
Summary
This summary is machine-generated.Automated decision systems create a cost problem for explanations. Large language models may offer solutions but introduce significant ethical concerns regarding explainability.
Area Of Science
- Artificial Intelligence
- Ethics in Technology
- Decision Systems
Background
- A consensus exists on the moral right to explanations for automated decision systems.
- Providing explanations for high-stakes automated decisions presents a significant cost challenge.
- This challenge, termed the 'cost problem,' impacts organizations using these systems.
Purpose Of The Study
- To investigate the potential of large language models (LLMs) in addressing the cost problem of automated decision explanations.
- To evaluate the feasibility and ethical implications of using LLMs for generating decision explanations.
Main Methods
- Exploratory analysis of large language models' capabilities in generating explanations.
- Conceptual examination of the ethical trade-offs involved.
Main Results
- Large language models show promise in potentially overcoming the cost problem associated with explanations.
- The use of LLMs for this purpose may incur serious ethical costs.
Conclusions
- LLMs present a potential pathway to mitigate the financial burden of providing explanations for automated decisions.
- The ethical implications, including fairness and transparency, require careful consideration and further research.
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