Position: AI Safety should Balance User-Control Against Provider-Control

In this position paper, we introduce the idea of "model-control", denoting the influence competing stakeholders have over the outputs of an artificial intelligence (AI) model. We adopt a triadic view of AI safety, which treats harms $H_m$ arising intrinsically from the model differently from harms $H_u$ arising from the misuse of that model. This helps us analyse how, in the pursuit of safety, models are deliberately tuned to increase provider-control while sacrificing user-control – the influences model-providers and users have over models respectively. We draw on contemporary examples to illustrate how various stakeholders seek model-control, and find that reducing user-control can lead to adverse impacts. Many stakeholders seek to influence model outputs through model-providers, and with increasing regulatory and commercial pressure in the future, this risk could be exacerbated. User-control and provider-control may or may not align in general, and we show the tradeoff between them empirically using the XSTest benchmark. We end our paper by suggesting that AI safety should not unilaterally prioritise model-providers over users, and that balancing user-control with provider-control could sometimes be a better way to improve AI safety.