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Kristen K. Greene

dblp:86/4184 · DBLP profile ↗
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4ranked-venue papers
1as first author
1since 2021 · last 2024
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Human-computer interaction and ubiquitous computing · 3 · 1 since 2021Artificial intelligence and machine learning · 1 · 1 since 2021Security and privacy · 1 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Human-computer interaction and pervasive computing
2 papers
Usability and user experience research · 63% Interaction techniques and input · 29% Accessibility and assistive technology · 8%

Topics — the 2 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Usability and user experience research › usability evaluation
subjective vs objective usability measures
0.012008
Electronic voting machines versus traditional methods: improved preference, similar performance · CHI 2008
Accessibility and assistive technology › accessible interaction
accessible voting
0.012007
Usability of voting systems: baseline data for paper, punch cards, and lever machines · CHI 2007

Methods — techniques the papers use, named apart from their topics

comparative usability study · 0.1system usability scale · 0.1controlled experiment · 0.1
YearPublicationVenuePosition
2024 Reflection of Its Creators: Qualitative Analysis of General Public and Expert Perceptions of Artificial Intelligence
abstract
The increasing prevalence of artificial intelligence (AI) will likely lead to new interactions and impacts for the general public. An understanding of people’s perceptions of AI can be leveraged to design and deploy AI systems toward human needs and values. We conducted semi-structured interviews with 25 individuals in the general public and 20 AI experts in the United States (U.S.) to assess perceptions of AI across levels of expertise. Qualitative analysis revealed that ideas about humanness and ethics were central to perceptions of AI in both groups. Humanness, the set of traits considered to distinguish humans from other intelligent actors, was used to articulate beliefs about AI’s characteristics. Ethics arose in discussions of the role of technology in society and centered around views of AI as made and used by people. General public and expert participants expressed similar perceptions of AI, but articulated beliefs slightly differently. We discuss the implications of humanness-related beliefs and ethical concerns for AI development and deployment.
Theodore Jensen, Mary Frances Theofanos, Kristen K. Greene, Olivia Williams, Kurtis Goad, Janet Bih Fofang
AIES (1)3
2017 Must I, can I? I don't understand your ambiguous password rules
abstract
Purpose The purpose of this research is to investigate user comprehension of ambiguous terminology in password rules. Although stringent password policies are in place to protect information system security, such complexity does not have to mean ambiguity for users. While many aspects of passwords have been studied, no research to date has systematically examined how ambiguous terminology affects user comprehension of password rules. Design/methodology/approach This research used a combination of quantitative and qualitative methods in a usable security study with 60 participants. Study tasks contained password rules based on real-world password requirements. Tasks consisted of character-selection tasks that varied the terms for non-alphanumeric characters to explore users’ interpretations of password rule language, and compliance-checking tasks to investigate how well users can apply their understanding of the allowed character space. Findings Results show that manipulating password rule terminology causes users’ interpretation of the allowed character space to shrink or expand. Users are confused by the terms “non-alphanumeric”, “symbols”, “special characters” and “punctuation marks” in password rules. Additionally, users are confused by partial lists of allowed characters using “e.g.” or “etc.” Practical implications This research provides data-driven usability guidance on constructing clearer language for password policies. Improving language clarity will help usability without sacrificing security, as simplifying password rule language does not change security requirements. Originality/value This is the first usable security study to systematically measure the effects of ambiguous password rules on user comprehension of the allowed character space.
Kristen K. Greene, Yee-Yin Choong
Inf. Comput. Secur.1
2008 Electronic voting machines versus traditional methods: improved preference, similar performance
abstract
In the 2006 U.S. election, it was estimated that over 66 million people would be voting on direct recording electronic (DRE) systems in 34% of the nation's counties [8]. Although these computer-based voting systems have been widely adopted, they have not been empirically proven to be more usable than their predecessors. The series of studies reported here compares usability data from a DRE with those from more traditional voting technologies (paper ballots, punch cards, and lever machines). Results indicate that there were little differences between the DRE and these older methods in efficiency or effectiveness. However, in terms of user satisfaction, the DRE was significantly better than the older methods. Paper ballots also perform well, but participants were much more satisfied with their experiences voting on the DRE. The disconnect between subjective and objective usability has potential policy ramifications.
Sarah P. Everett, Kristen K. Greene, Michael D. Byrne, Dan S. Wallach, Kyle Derr, Daniel Sandler, Ted Torous
CHI2
2007 Usability of voting systems: baseline data for paper, punch cards, and lever machines
abstract
In the United States, computer-based voting machines are rapidly replacing other older technologies. While there is potential for this to be a usability improvement, particularly in terms of accessibility, the only way it is possible to know if usability has improved is to have baseline data on the usability of traditional technologies. We report an experiment assessing the usability of punch cards, lever machines, and two forms of paper ballot. There were no differences in ballot completion time between the four methods, but there were substantial effects on error rate, with the paper ballots superior to the other methods as well as an interaction with age of voters. Subjective usability was assessed with the System Usability Scale and showed a slight advantage for bubble-style paper ballots. Overall, paper ballots were found to be particularly usable, which raises important technological and policy issues.
Michael D. Byrne, Kristen K. Greene, Sarah P. Everett
CHI2