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Social computing platforms facilitate interpersonal harms that manifest across online and physical realms such as sexual violence between online daters and sexual grooming through social media. Risk detection AI has emerged as an approach to preventing such harms, however a myopic focus on computational performance has been criticized in HCI literature for failing to consider how users should interact with risk detection AI to stay safe. In this paper we report an interview study with woman-identifying online daters (n=20) about how they envision interacting with risk detection AI and how risk detection models can be designed pursuant to such interactions. In accordance with this goal, we engaged women in risk detection model building exercises to build their own risk detection models. Findings show that women anticipate interacting with risk detection AI to augment - not replace - their personal risk assessment strategies. They likewise designed risk detection models to amplify their subjective and admittedly biased indicators of risk. Design implications involve the notion of personalizable risk detection models, but also ethical concerns around perpetuating problematic stereotypes associated with risk. 

As social Virtual Reality (VR) grows in prevalence, new possibilities for embodied and immersive social interaction emerge, including varied forms of interpersonal harm. Yet, challenges remain regarding defining, identifying, and mitigating said harm in social VR. In this paper, we take an alternative approach to understanding and designing solutions for interpersonal harm in social VR through the lens of consent, which circumvents the lack of consensus and social norms on what should be defined as harm in social VR and reflects the embodied, immersive, and offline-world-like nature of harm in social VR. Through interviews with 39 social VR users, we offer one of the first empirical explorations on how social VR users understand consent as boundaries, (re)purpose existing social VR features for practicing consent as boundary setting, and envision the design of future consent mechanics in social VR to balance protection and interaction expectations to mitigate interpersonal harm as boundary violations in social VR. This work makes significant contributions to CSCW and HCI research by (1) uncovering how social VR users craft novel conceptualizations of consent as boundaries and harm as unwanted boundary violations, and (2) providing three foundational principles for designing future consent mechanics in social VR informed by actual social VR users.