Measuring the practice of shared-decision making (OPTION12): An Investigation into Open-sourced Smaller LLMs (OS-sLLMs) for Better Privacy and Sustainability
arXiv:2607.06127v1 Announce Type: new Abstract: We present LLM4SDM, the first study of open-source smaller language models (OS-sLLMs) for automated assessment of shared decision making (SDM) using the Observer OPTION12 framework. Unlike previous work that relies on large commercial models and the shorter OPTION5 instrument, our study focuses on privacy-preserving locally deployable models and Dutch melanoma consultation transcripts. Using expert-annotated clinical consultations, we evaluate three general-domain and two medical-domain OS-sLLMs during a development-phase pilot study. Results sho
The increasing availability and performance of smaller language models, coupled with growing concerns over data privacy, are driving research into locally deployable AI solutions.
This development signals a move towards more privacy-preserving and sustainable AI applications, potentially reducing reliance on large commercial models and enabling sensitive data processing on-device or locally.
The focus is shifting from exclusive use of large, cloud-based commercial models to exploring the utility and privacy benefits of smaller, open-source, and locally deployable alternatives, particularly for specific applications like healthcare.
- · Open-source AI developers
- · Healthcare providers seeking data privacy
- · European AI research institutions
- · Users concerned about data sovereignty
- · Large commercial LLM providers (for specific use cases)
- · Cloud-dependent AI architectures
Increased adoption of OS-sLLMs for domain-specific applications where data sensitivity or sovereignty is paramount.
A more fragmented but specialized AI ecosystem emerges, with diverse models optimized for specific local or private computational environments.
National or regional governments may prioritize and fund the development of local AI capabilities for critical sectors, fostering digital sovereignty.
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