Beyond Release: Access Considerations for Generative AI Systems
Fuente:
arXiv
Gespeichert in:
| Hauptverfasser: | , , , , , , |
|---|---|
| Format: | Preprint |
| Veröffentlicht: |
2025
|
| Schlagworte: | |
| Online-Zugang: | |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| _version_ | 1866915236631543808 |
|---|---|
| author | Solaiman, Irene Bommasani, Rishi Hendrycks, Dan Herbert-Voss, Ariel Jernite, Yacine Skowron, Aviya Trask, Andrew |
| author_facet | Solaiman, Irene Bommasani, Rishi Hendrycks, Dan Herbert-Voss, Ariel Jernite, Yacine Skowron, Aviya Trask, Andrew |
| contents | Generative AI release decisions determine whether system components are made available, but release does not address many other elements that change how users and stakeholders are able to engage with a system. Beyond release, access to system components informs potential risks and benefits. Access refers to practical needs, infrastructurally, technically, and societally, in order to use available components in some way. We deconstruct access along three axes: resourcing, technical usability, and utility. Within each category, a set of variables per system component clarify tradeoffs. For example, resourcing requires access to computing infrastructure to serve model weights. We also compare the accessibility of four high performance language models, two open-weight and two closed-weight, showing similar considerations for all based instead on access variables. Access variables set the foundation for being able to scale or increase access to users; we examine the scale of access and how scale affects ability to manage and intervene on risks. This framework better encompasses the landscape and risk-benefit tradeoffs of system releases to inform system release decisions, research, and policy. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2502_16701 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Beyond Release: Access Considerations for Generative AI Systems Solaiman, Irene Bommasani, Rishi Hendrycks, Dan Herbert-Voss, Ariel Jernite, Yacine Skowron, Aviya Trask, Andrew Computers and Society Artificial Intelligence Generative AI release decisions determine whether system components are made available, but release does not address many other elements that change how users and stakeholders are able to engage with a system. Beyond release, access to system components informs potential risks and benefits. Access refers to practical needs, infrastructurally, technically, and societally, in order to use available components in some way. We deconstruct access along three axes: resourcing, technical usability, and utility. Within each category, a set of variables per system component clarify tradeoffs. For example, resourcing requires access to computing infrastructure to serve model weights. We also compare the accessibility of four high performance language models, two open-weight and two closed-weight, showing similar considerations for all based instead on access variables. Access variables set the foundation for being able to scale or increase access to users; we examine the scale of access and how scale affects ability to manage and intervene on risks. This framework better encompasses the landscape and risk-benefit tradeoffs of system releases to inform system release decisions, research, and policy. |
| title | Beyond Release: Access Considerations for Generative AI Systems |
| topic | Computers and Society Artificial Intelligence |
| url | https://arxiv.org/abs/2502.16701 |