[AISWorld] Announcing the publication of volume 12 issue 2 of AIS Transactions on Human-Computer Interaction (THCI)

[Nah, Fiona]

Announcing the Publication of
Volume 12 Issue 2 of AIS Transactions on Human-Computer Interaction (THCI)
(http://https://aisel.aisnet.org/thci/)

THCI is ranked "A" in the 2019 Australian Business Deans Council (ABDC) Journal Quality List - https://abdc.edu.au/research/abdc-journal-list/. 

The June 2020 issue of THCI comprises three papers. 

The first paper entitled "Do We Truly Sacrifice Truth for Simplicity: Comparing Complete Individual Randomization and Semi-Randomized Approaches to Survey Administration" by Eleanor Loiacono and E. Vance Wilson reports the findings from their study that compared complete randomization versus partially individualized randomization of survey items to assess potential tradeoffs between them. 

In the second paper entitled "Exacerbating Mindless Compliance: The Danger of Justifications during Privacy Decision Making in the Context of Facebook Applications" by Reza Ghaiumy Anaraky, Bart Knijnenburg, and Marten Risius, the authors examined mindless compliance by studying the effect of two types of justifications-normative versus rationale-based-on framing- and default-induced compliance in social media. 

The third paper by Lionel Robert Jr., Gaurav Bansal, and Christoph Lütge is a panel report from the 2019 pre-ICIS SIGHCI workshop that addresses human-computer interaction challenges and opportunities for fair, trustworthy, and ethical artificial intelligence and presents research questions based on eight themes.  

You can download the papers from this issue and other issues by visiting the AIS E-Library (http://aisel.aisnet.org/) or the direct links below. You can also go directly to the journal at http://aisel.aisnet.org/thci/. 

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In this issue (Volume 12, Issue 2)

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Paper 1:

Loiacono, E., & Wilson, E. V. (2020). Do we truly sacrifice truth for simplicity: Comparing complete individual randomization and semi-randomized approaches to survey administration. AIS Transactions on Human-Computer Interaction, 12(2), 45-69. DOI: 10.17705/1thci.00128

Available at: https://aisel.aisnet.org/thci/vol12/iss2/1/ 

Abstract:

Human-computer interaction researchers have long used survey methodologies. However, debate remains about the potential for participants to provide biased responses to subsequent items based on previously viewed items. In this research, we investigate the effects of survey item ordering that researchers have not studied previously. Grounded in previous exploratory item-ordering studies using an HCI online survey, we investigate bias in more detail. In addition, we use an adult sample population so that we can extend our results more broadly as compared to previous research. We employed two distinct randomizing survey approaches: 1) complete item randomization for each respondent (random), which presents items to each respondent in a completely randomized order; and 2) partially individualized item randomization (grouped), which presents constructs in the same order in a survey but randomizes items in each construct for each respondent. Our results suggest researchers should use fully randomized survey instruments in HCI research whenever possible since grouped ordering of any kind increases bias and statistical inflation, which can influence results' veracity. Additionally, we did not appear to find any significant increase in the participants' frustration or fatigue to be associated with the random treatment.

Paper 2:

Anaraky, R. G., Knijnenburg, B. P., & Risius, M. (2020). Exacerbating mindless compliance: The danger of justifications during privacy decision making in the context of Facebook applications. AIS Transactions on Human-Computer Interaction, 12(2), 70-95. DOI: 10.17705/1thci.00129

Available at: https://aisel.aisnet.org/thci/vol12/iss2/2/

Abstract:

Online companies exploit mindless compliance during users' privacy decision making to avoid liability while not impairing users' willingness to use their services. These manipulations can play against users since they subversively influence their decisions by nudging them to mindlessly comply with disclosure requests rather than enabling them to make deliberate choices. In this paper, we demonstrate the compliance-inducing effects of defaults and framing in the context of a Facebook application that nudges people to be automatically publicly tagged in their friends' photos and/or to tag their friends in their own photos. By studying these effects in a Facebook application, we overcome a common criticism of privacy research, which often relies on hypothetical scenarios. Our results concur with previous findings on framing and default effects. Specifically, we found a reduction in privacy-preserving behaviors (i.e., a higher tagging rate in our case) in positively framed and accept-by-default decision scenarios. Moreover, we tested the effect that two types of justifications-information that implies what other people do (normative) or what the user ought to do (rationale based)-have on framing- and default-induced compliance. Existing work suggests that justifications may increase compliance in a positive (agree-by-) default scenario even when the justification does not relate to the decision. In this study, we expand this finding and show that even a justification that is opposite to the default action (e.g., a justification suggesting that one should not use the application) can increase mindless compliance with the default. Thus, when companies abide by policy makers' requirements to obtain informed user consent through explaining the privacy settings, they will paradoxically induce mindless compliance and further threaten user privacy.

Paper 3:

Robert, L. P., Gaurav, B., & Lütge, C.  (2020). ICIS 2019 SIGHCI Workshop Panel Report: Human-Computer Interaction Challenges and Opportunities for Fair, Trustworthy and Ethical Artificial Intelligence. AIS Transactions on Human-Computer Interaction, 12(2), pp. 96-108. DOI: 10.17705/1thci.00130

Available at: https://aisel.aisnet.org/thci/vol12/iss2/3/

Abstract:

Artificial Intelligence (AI) is rapidly changing every aspect of our society-including amplifying our biases. Fairness, trust and ethics are at the core of many of the issues underlying the implications of AI. Despite this, research on AI with relation to fairness, trust and ethics in the information systems (IS) field is still scarce. This panel brought together academia, business and government perspectives to discuss the challenges and identify potential solutions to address such challenges. This panel report presents eight themes based around the discussion of two questions: (1) What are the biggest challenges to designing, implementing and deploying fair, ethical and trustworthy AI?; and (2) What are the biggest challenges to policy and governance for fair, ethical and trustworthy AI? The eight themes are: (1) identifying AI biases; (2) drawing attention to AI biases; (3) addressing AI biases; (4) designing transparent and explainable AI; (5) AI fairness, trust, ethics: old wine in a new bottle?; (6) AI accountability; (7) AI laws, policies, regulations and standards; and (8) frameworks for fair, ethical and trustworthy AI. Based on the results of the panel discussion, we present research questions for each theme to guide future research in the area of human-computer interaction.

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Call for Papers

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THCI is one of the journals in the AIS (Association for Information Systems) e-library at http://aisel.aisnet.org/thci. THCI is a high-quality peer-reviewed international scholarly journal on Human-Computer Interaction. As an AIS journal, THCI is oriented to the Information Systems community, emphasizing HCI/UX applications in business, managerial, organizational, and cultural contexts. However, it is open to all related communities that share intellectual interests in HCI phenomena and issues. The editorial objective is to enhance and communicate knowledge about the interplay among humans, information, technologies, and tasks in order to guide the development and use of human-centered Information and Communication Technologies (ICT) and services for individuals, groups, organizations, and communities.

To increase awareness and readership, THCI is still freely available to the public, which is beneficial to the authors and the community. You can find information related to all aspects of THCI at its website (http://aisel.aisnet.org/thci), including how to submit manuscripts for publication consideration. We would like to thank the AIS Council (http://www.aisnet.org/) for its continued support of the journal. And, as always, we are happy to announce that we have published the journal on time for every issue, and are building a strong case for a solid impact factor when released by SSCI and Scopus in the near future. The quality of THCI is affirmed by its inclusion as an "A" journal in the Australian Business Deans Council (ABDC) journal quality list.

Topics of interest to THCI include but are not limited to the following:

*   Behavioral, cognitive, motivational and affective aspects of human and technology interaction

*   User task analysis and modeling; fit between representations and task types

*   Digital documents/genres; human information seeking and web navigation behaviors; human information interaction; information visualization

*   Social media; social computing; virtual communities

*   Behavioral information security and information assurance; privacy and trust in human technology interaction

*   User interface design and evaluation for various applications in business, managerial, organizational, educational, social, cultural, non-work, and other domains

*   Integrated and/or innovative approaches, guidelines, and standards or metrics for human centered analysis, design, construction, evaluation, and use of interactive devices and information systems

*   Information systems usability engineering; universal usability

*   Impact of interfaces/information technology on people's attitude, behavior, performance, perception, and productivity

*   Implications and consequences of technological change on individuals, groups, society, and socio-technical units

*   Software learning and training issues such as perceptual, cognitive, and motivational aspects of learning

*   Gender and information technology

*   The elderly, the young, and special needs populations for new applications, modalities, and multimedia interaction

*   Issues in HCI education

The language for the journal is English. The audience includes international scholars and practitioners who conduct research on issues related to the objectives of the journal. The publication frequency is quarterly: 4 issues per year to be published in March, June, September, and December. The AIS Special Interest Group on Human-Computer Interaction (SIGHCI, http://sighci.org/) is the official sponsor of THCI.

Please continue to check the AIS THCI home page (http://aisel.aisnet.org/thci/) to see what is brewing! If you have an idea for a special issue, please drop us a line any time.

Sincerely,

Fiona Fui-Hoon Nah, Editor-in-Chief

Gregory D. Moody, Managing Editor
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Fiona Fui-Hoon Nah, Ph.D.
Editor-in-chief, AIS Transactions on Human-Computer Interaction 
Professor of Business & Information Technology 
Missouri University of Science and Technology
101 Fulton Hall
301 W 14th Street
Rolla, MO 65409
Tel: 573-341-6996
Email: nahf at mst.edu
URL: http://people.mst.edu/faculty/nahf/