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Dark patterns are increasingly ubiquitous in digital services and regulation, describing instances where designers use deceptive, manipulative, or coercive tactics to encourage end users to make decisions that are not in their best interest. Research regarding dark patterns has also increased significantly over the past several years. In this systematic review, we evaluate literature (n=79) from 2014 to 2022 that has empirically described dark patterns in order to identify the presence, impact, or user experience of these patterns as they appear in digital systems. Based on our analysis, we identify key areas of current interest in evaluating dark patterns’ context, presence, and impact; describe common disciplinary perspectives and framing concepts; characterize dominant methodologies; and outline opportunities for further methodological support and scholarship to empower scholars, designers, and regulators. 

Numerous methods and tools have been proposed to motivate or support ethical awareness in design practice. However, many existing resources are not easily discoverable by practitioners, and are often framed using language that is not accessible or resonant with everyday practice. In this paper, we present three complementary strands of work with the goal of increasing the ability of design and technology practitioners to locate and activate methods to support ethically-focused work practices. We first constructed a set of empirically-supported “intentions” to frame practitioners’ selection of relevant ethics-focused methods based on interviews with practitioners from a range of technology and design professions. We then leveraged these intentions in the design and iterative evaluation of a website that supports practitioners in identifying opportunities for ethics-focused action. Building on these findings, we propose a set of design considerations to evaluate the practice resonance of resources in supporting ethics-focused practice, laying the groundwork for increased ecological resonance of ethics-focused methods and method selection tools.