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Safer Algorithmically-Mediated Offline Introductions: Harms and Protective Behaviors

Rivera, Veronica A. and Wilkinson, Daricia and Augusta, Aurelia and Li, Sophie and Redmiles, Elissa M. and Strohmayer, Angelika (2024) — Proc. ACM Hum.-Comput. Interact.

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DOI: 10.1145/3686948 (opens in a new tab)

Country:   United States
Tags:   Algorithmically Mediated Offline Introductions, Dating Scams, Gig Work Safety, Online Dating Safety, Platform Design, Post Digital Safety, Protective Behaviors, Technology Facilitated Harm
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Synopsis

            
This publication examines how algorithmically-mediated offline introductions (AMOIs) create harms that cross online and offline spaces, and it seeks ways to support safety by design. The authors define safety in a multidimensional, context-driven way and focus on two representative AMOI contexts—online dating and in-person gig work—to understand harms that can occur before, during, and after offline meetings. They adopt a mixed-methods approach: a systematic review of 93 prior works to synthesize a taxonomy of harms and protective safety behaviors, followed by a survey of online daters (n=476) and gig workers (n=451) to validate and measure the salience and prevalence of those harms and protections. The goal is to ground design and research directions in empirical evidence about how people try to stay safe in AMOIs. The study identifies four broad harms—physical, emotional, financial, and autonomy-related harms—and pairs them with a set of protective behaviors that users actually employ. The taxonomy highlights behaviors such as self-disclosure, obfuscation, screening and vetting, environmental precautions, covering, emergency alerts, surveillance and documentation, blocking, and reporting. The authors report high rates of screening and diverse obfuscation practices, with differences observed between online daters and gig workers in where and how information is shared or withheld. They argue that safety in AMOIs is constrained by platform opacity and design choices, which shift protective burden onto users and can reproduce inequities across social groups. The paper discusses implications for design, policy, and future work, including the need for transparent reporting mechanisms, collective and decentralized safety practices, and feminist, trauma-aware, and participatory approaches to building safer AMOI infrastructure. It also cautions against overreliance on reactive safety tech and emphasizes educating and involving users, especially marginalized communities, in co-creating safety solutions. The authors acknowledge limitations related to power dynamics, platform incentives, and the evolving nature of AMOIs.

          

        
                  

            
Identified Gaps

            
Prior AMOI research is largely qualitative, fragmented by population or safety topic, and provides limited quantification of threats, behaviors, and their implementation. The paper identifies little to no prior work on online daters' autonomy harms, despite their salience in the survey. It also notes a need to study in-person gig workers' low reported data-privacy concerns and to investigate safety experiences beyond online dating and gig work.

          

        
                  

            
Methods

            
The study systematically reviewed 93 English-language publications across computer and social science databases, using affinity diagramming to develop a taxonomy of AMOI harms and protective behaviors. It then surveyed U.S. online daters (n=476) and in-person gig workers (n=451) who had met platform matches offline. Open-ended safety definitions underwent deductive thematic analysis; protective-behavior prevalence was analyzed descriptively and compared using chi-square tests with Bonferroni-Holm correction. Some questions were re-fielded in 2022.

          

        
                  

            
Limitations

            
The literature search may have omitted relevant AMOI research not retrieved by the search terms, potentially limiting the taxonomy. Survey data are subject to social desirability, under-reporting, and recall bias. Although the samples were recruited to roughly reflect U.S. demographics, they may not capture all ages, cultural backgrounds, or AMOI interaction types. Re-fielding some questions a year later may also reflect changed participant behavior.

          

        
                  

            
Future Work

            
Research should develop and assess proactive, collective safety defenses; threat models for how actors exploit platform features; privacy-preserving and consensual vetting systems; and safer technologies co-created with users, especially marginalized groups. Studies should also examine vulnerability factors, platform trust, identities' effects on protective behavior, and participatory, trauma-aware approaches. Nontechnical options, including regulation and support for anti-violence organizations, should be considered alongside technology.

          

              

    
    

        
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