[AISWorld] Four new articles published in the Australasian Journal of Information Systems

[Ajis Editor]

Dear Colleagues,

The Australasian Journal of Information Systems (AJIS) has just published
four new articles in its Research Article section of its volume 28:

*(Why) Do We Trust AI?: A Case of AI-based Health Chatbots*

Ashish Viswanath Prakash, Saini Das

ashish at iimtrichy.ac.in

doi: https://doi.org/10.3127/ajis.v28i0.4235


Automated chatbots powered by artificial intelligence (AI) can act as a
ubiquitous point of contact, improving access to healthcare and empowering
users to make effective decisions. However, despite the potential benefits,
emerging literature suggests that apprehensions linked to the distinctive
features of AI technology and the specific context of use (healthcare)
could undermine consumer trust and hinder widespread adoption. Although the
role of trust is considered pivotal to the acceptance of healthcare
technologies, a dearth of research exists that focuses on the contextual
factors that drive trust in such AI-based Chatbots for Self-Diagnosis
(AICSD). Accordingly, a contextual model based on the trust-in-technology
framework was developed to understand the determinants of consumers’ trust
in AICSD and its behavioral consequences. It was validated using a free
simulation experiment study in India (N = 202). Perceived anthropomorphism,
perceived information quality, perceived explainability, disposition to
trust technology, and perceived service quality influence consumers’ trust
in AICSD. In turn, trust, privacy risk, health risk, and gender determine
the intention to use. The research contributes by developing and validating
a context-specific model for explaining trust in AICSD that could aid
developers and marketers in enhancing consumers’ trust in and adoption of
AICSD.

#
ArtificialIntelligence#HealthChatbot#TrustinTechnology#Explainability#Contextualization#FreeSimulationExperiment

*Sociotechnical perspectives of digital technologies in sustainable mining*

Warren Gabryk, Rennie Naidoo

wgabryk at tuks.co.za

doi: https://doi.org/10.3127/ajis.v28i0.4369

This paper adopts an interpretive case study approach to understand the
role of digital technologies in addressing seemingly contradictory
sustainability goals in mining. The sociotechnical model of information
systems was used as a framework to guide the analysis of twenty-five
in-depth interviews with globally dispersed digital technology experts
working collaboratively at an industry-leading hi-tech mining solutions
company. The sociotechnical-led thematic analysis findings highlight the
trade-offs experts face in balancing narrow technological imperatives and
economic outcomes with broader sustainability goals. The analysis moves
beyond the technological and economic to a harmonious perspective of
social, human, environmental, and technological interactions. A visual
thematic map is presented to aid practitioners in designing and optimally
implementing digital technologies to simultaneously address the United
Nations Sustainable Development Goals while prioritising business
sustainability. We conclude by drawing from the proposed sociotechnical
perspectives approach for digital sustainability to provide scholars with
possible pathways for future responsible information systems research.

#
Casestudy#Digitalmining#Digitalsustainability#Sociotechnical#Sustainabledevelopmentgoals#Thematicanalysis

*Machine Learning Based Decision-Making: A Sensemaking Perspective*

Jingqi (Celeste) Li, Morteza Namvar, Ghiyoung P. Im, Saeed Akhlaghpour

m.namvar at business.uq.edu.au

doi: https://doi.org/10.3127/ajis.v28i0.4781

The integration of machine learning (ML), functioning as the core of
various artificial intelligence (AI)-enabled systems in organizations,
comes with the assertion that ML models offer automated decisions or assist
domain experts in refining their decision-making. The current research
presents substantial evidence of ML’s positive impact on business and
organizational performance. Nonetheless, there is a limited understanding
of how decision-makers participate in the process of generating ML-driven
insights and enhancing their comprehension of business environments through
ML outcomes. To enhance this engagement and understanding, this study
examines the interactive process between decision-makers and ML experts as
they strive to comprehend an environment and gather business insights for
decision-making. It builds upon Weick’s sensemaking model by integrating
ML’s pivotal role. By conducting interviews with 31 ML experts and ML
end-users, we explore the dimensions of sensemaking in the context of ML
utilization for decision-making. Consequently, this study proposes a
process model which advances the organizational ML research by
operationalizing Weick’s work into a structured ML-driven sensemaking model.
This model charts a pragmatic pathway, outlining the interaction sequence
between decision-makers and ML tools as they navigate through recognizing
and utilizing ML, exploring opportunities, assessing ML model outcomes, and
translating ML models into action, thereby advancing both the theoretical
framework and its practical deployment in organizational contexts.

#MachineLearningML#decisionmaking#sensemaking

*“Use” as a Conscious Thought: Towards a Theory of “Use” in Autonomous
Things*

Gohar Khan, A Karim Feroz

karim.feroz at mga.edu

doi: https://doi.org/10.3127/ajis.v28i0.44611

The way users perceive and use information systems artefacts has been
mainly studied from the notion of behavioral beliefs, deliberate cognitive
efforts, and physical actions performed by human actors to produce certain
outcomes. The next generation of information systems, however, can sense,
respond, and adapt to environments without necessitating similar cognitive
efforts, physical contact, or explicit instructions to operate. Therefore,
by leveraging theories of consciousness and technology use, this research
aims to advance an alternative understanding of the "use" associated with
the next generation of IS artefacts that do not require deliberate
cognitive efforts, physical manipulation, or explicit instructions to yield
outcomes. The theory and proposed model were refined and validated through
the burst detection technique, IS expert involvement (n=10), a pilot study
(n=130), and end-user surveys (n= 119). Structural equating modelling
techniques were employed to test the theory. We show that unlike the
manually operated IS artefacts, the “use” of a fully autonomous artefact is
a *conscious thought* rather than a *physical activity* of operating a
system to produce certain outcomes. We argue that, unlike the traditional
notions of use associated with manually operated technologies, *conscious
use* is not characterized solely by behavioral beliefs stemming from
logical and reflective cognitive and physical efforts (e.g., effort
expectancy). We propose the notion of conscious use within the context of
fully autonomous entities and empirically validate its measure.
Additionally, we offer recommendations for future research directions in
this area. The conceptualization of this new theory for fully autonomous IS
artefacts adds significant academic value to the literature given the
convergence of AI-based machine learning systems and cognitive computing
systems.

#autonomousthings#conscioususe#consciousthoughts#scaledevelopment





Thank you for your continuing interest in our work.

Best regards

Professor Karlheinz Kautz

Editor-in-Chief, Australasian Journal of Information Systems

http://journal.acs.org.au/index.php/ajis/
<https://l.facebook.com/l.php?u=http%3A%2F%2Fjournal.acs.org.au%2Findex.php%2Fajis%2F%3Ffbclid%3DIwAR1phvAd05QiLHM-gAdaxAFrU62wJbYdzKtYi_KLDTNvFN3EfWawW7jguO0&h=AT1q3wRQcAomQQHoubVNDckJD4JngJjJrsL79LnTH6jaUiUhTGqw4dTnfkzSnRH1kd7ieD-40Bdf2V0ABZtDbhprv_Y76StTogpJS3kv9OEsyIPg70aNRLsUuCoccKe9EREJtHVXueAr7WntOA&__tn__=-UK-R&c%5b0%5d=AT1VNWTIdyDW_4n09hY9qOcNvQlggHsRoU2cSuHJdalTTGif1LKLDq2kRZrjGZJ9UbofDVq5b_hHnrEFhmxsWaQYSAI0L-JgYyO8SSfYOUlYOvPpu6ILijISyK48LzX_E6EvgvrYjuXrZ1miiOOKd3jUBIaN-bS1CZZ7TJJwgom5Pb2QCGpb9ZHulN5WvCQUI6Jpl2OH3MKd>