How WEIRD is Usable Privacy and Security Research? (Extended Version)

• URL: http://arxiv.org/abs/2305.05004v2
• Date: Sun, 8 Oct 2023 22:22:22 GMT
• Title: How WEIRD is Usable Privacy and Security Research? (Extended Version)
• Authors: Ayako A. Hasegawa, Daisuke Inoue, Mitsuaki Akiyama
• Abstract summary: We conducted a literature review to understand the extent to which participant samples in UPS papers were from WEIRD countries. Geographic and linguistic barriers in the study methods and recruitment methods may cause researchers to conduct user studies locally.
• Score: 7.669758543344074
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: In human factor fields such as human-computer interaction (HCI) and psychology, researchers have been concerned that participants mostly come from WEIRD (Western, Educated, Industrialized, Rich, and Democratic) countries. This WEIRD skew may hinder understanding of diverse populations and their cultural differences. The usable privacy and security (UPS) field has inherited many research methodologies from research on human factor fields. We conducted a literature review to understand the extent to which participant samples in UPS papers were from WEIRD countries and the characteristics of the methodologies and research topics in each user study recruiting Western or non-Western participants. We found that the skew toward WEIRD countries in UPS is greater than that in HCI. Geographic and linguistic barriers in the study methods and recruitment methods may cause researchers to conduct user studies locally. In addition, many papers did not report participant demographics, which could hinder the replication of the reported studies, leading to low reproducibility. To improve geographic diversity, we provide the suggestions including facilitate replication studies, address geographic and linguistic issues of study/recruitment methods, and facilitate research on the topics for non-WEIRD populations.

Related papers

• Chain of Ideas: Revolutionizing Research Via Novel Idea Development with LLM Agents [64.64280477958283]
  An exponential increase in scientific literature makes it challenging for researchers to stay current with recent advances and identify meaningful research directions. Recent developments in large language models(LLMs) suggest a promising avenue for automating the generation of novel research ideas. We propose a Chain-of-Ideas(CoI) agent, an LLM-based agent that organizes relevant literature in a chain structure to effectively mirror the progressive development in a research domain.
  arXiv  Detail & Related papers  (2024-10-17T03:26:37Z)
• A Survey Forest Diagram : Gain a Divergent Insight View on a Specific Research Topic [2.699900017799093]
  The use of Generative AI for information retrieval and question-answering has become popular for conducting research surveys. This study aims to develop an in-depth Survey Forest Diagram that guides novice researchers in divergent thinking about the research topic.
  arXiv  Detail & Related papers  (2024-07-24T08:17:37Z)
• 15 Years of Algorithmic Fairness -- Scoping Review of Interdisciplinary Developments in the Field [0.0]
  This paper presents a scoping review of algorithmic fairness research over the past fifteen years. All articles come from the computer science and legal field and focus on AI algorithms with potential discriminatory effects on population groups.
  arXiv  Detail & Related papers  (2024-07-23T07:50:01Z)
• SurveyAgent: A Conversational System for Personalized and Efficient Research Survey [50.04283471107001]
  This paper introduces SurveyAgent, a novel conversational system designed to provide personalized and efficient research survey assistance to researchers. SurveyAgent integrates three key modules: Knowledge Management for organizing papers, Recommendation for discovering relevant literature, and Query Answering for engaging with content on a deeper level. Our evaluation demonstrates SurveyAgent's effectiveness in streamlining research activities, showcasing its capability to facilitate how researchers interact with scientific literature.
  arXiv  Detail & Related papers  (2024-04-09T15:01:51Z)
• The State of Pilot Study Reporting in Crowdsourcing: A Reflection on Best Practices and Guidelines [12.782288692460565]
  A lack of details surrounding pilot studies in crowdsourcing research hinders the replication of studies and the reproduction of findings. We conducted a systematic literature review on the current state of pilot study reporting at the intersection of crowdsourcing and HCI research. We formulate a set of best practice guidelines for reporting crowd pilot studies in crowdsourcing research.
  arXiv  Detail & Related papers  (2023-12-13T12:13:40Z)
• A Diachronic Analysis of Paradigm Shifts in NLP Research: When, How, and Why? [84.46288849132634]
  We propose a systematic framework for analyzing the evolution of research topics in a scientific field using causal discovery and inference techniques. We define three variables to encompass diverse facets of the evolution of research topics within NLP. We utilize a causal discovery algorithm to unveil the causal connections among these variables using observational data.
  arXiv  Detail & Related papers  (2023-05-22T11:08:00Z)
• WEIRD FAccTs: How Western, Educated, Industrialized, Rich, and Democratic is FAccT? [8.12219922021227]
  Studies conducted on Western, Educated, Industrialized, Rich, and Democratic (WEIRD) samples are considered atypical of the world's population. This study aims to quantify the extent to which the ACM FAccT conference relies on WEIRD samples.
  arXiv  Detail & Related papers  (2023-05-10T18:52:09Z)
• Language Generation Models Can Cause Harm: So What Can We Do About It? An Actionable Survey [50.58063811745676]
  This work provides a survey of practical methods for addressing potential threats and societal harms from language generation models. We draw on several prior works' of language model risks to present a structured overview of strategies for detecting and ameliorating different kinds of risks/harms of language generators.
  arXiv  Detail & Related papers  (2022-10-14T10:43:39Z)
• Award rate inequities in biomedical research [55.850540873687386]
  The authors performed an analysis of 14,263 biomedical research proposals with proposed start dates between 2010-2022 from the University of Michigan Medical School. There is a clear relationship between race/ethnicity and rates of proposal award. Black/African American and Asian researchers appear disadvantaged across all submission categories relative to White researchers.
  arXiv  Detail & Related papers  (2022-06-14T14:05:39Z)
• Human Factors in Security Research: Lessons Learned from 2008-2018 [8.255966566768484]
  We focus our analysis on the research on the crucial population of experts, whose human errors can impact many systems at once. We analyzed the past decade of human factors research in security and privacy, identifying 557 relevant publications.
  arXiv  Detail & Related papers  (2021-03-24T15:58:05Z)
• Learnings from Frontier Development Lab and SpaceML -- AI Accelerators for NASA and ESA [57.06643156253045]
  Research with AI and ML technologies lives in a variety of settings with often asynchronous goals and timelines. We perform a case study of the Frontier Development Lab (FDL), an AI accelerator under a public-private partnership from NASA and ESA. FDL research follows principled practices that are grounded in responsible development, conduct, and dissemination of AI research.
  arXiv  Detail & Related papers  (2020-11-09T21:23:03Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.