Trends and Trajectories in the Software Industry: implications for the future of work

Laato, Samuli; Mäntymäki, Matti; Islam, A. K. M. Najmul; Hyrynsalmi, Sami; Birkstedt, Teemu

doi:10.1007/s10796-022-10267-4

Cited by 17 publications

(11 citation statements)

References 60 publications

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“…We notice that XAI and end user communications needs to be aimed at least towards the following stakeholder groups: laypeople, doctors, other medical professionals, clerks, tellers, actuaries, sales personnel, human resources personnel, administrative staff, management staff, airline employees, security specialists, IT personnel, financial crime specialists, judges, jury members, defendants, prosecutors, attorneys and employees working for technology providers. This large but not exhaustive list corresponds with the reported ubiquitous proliferation of ML across IS (Collins et al, 2021;Laato et al, 2021Laato et al, , 2022.…”

Section: End Users and Application Contexts Of Ai Systemssupporting

confidence: 53%

How to explain AI systems to end users: a systematic literature review and research agenda

Laato

Tiainen

Islam³

et al. 2022

INTR

Self Cite

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PurposeInscrutable machine learning (ML) models are part of increasingly many information systems. Understanding how these models behave, and what their output is based on, is a challenge for developers let alone non-technical end users.Design/methodology/approachThe authors investigate how AI systems and their decisions ought to be explained for end users through a systematic literature review.FindingsThe authors’ synthesis of the literature suggests that AI system communication for end users has five high-level goals: (1) understandability, (2) trustworthiness, (3) transparency, (4) controllability and (5) fairness. The authors identified several design recommendations, such as offering personalized and on-demand explanations and focusing on the explainability of key functionalities instead of aiming to explain the whole system. There exists multiple trade-offs in AI system explanations, and there is no single best solution that fits all cases.Research limitations/implicationsBased on the synthesis, the authors provide a design framework for explaining AI systems to end users. The study contributes to the work on AI governance by suggesting guidelines on how to make AI systems more understandable, fair, trustworthy, controllable and transparent.Originality/valueThis literature review brings together the literature on AI system communication and explainable AI (XAI) for end users. Building on previous academic literature on the topic, it provides synthesized insights, design recommendations and future research agenda.

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Section: End Users and Application Contexts Of Ai Systemssupporting

confidence: 53%

How to explain AI systems to end users: a systematic literature review and research agenda

Laato

Tiainen

Islam³

et al. 2022

INTR

Self Cite

View full text Add to dashboard Cite

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“…Moreover, emerging technologies driving this paradigm are disruptive and smart, affecting not only the way business is conducted, but the very future of work. Laato et al 84 mentioned that a major barrier is cultural lag, which influences overall technology acceptance across the organization, and may hamper future‐of‐work readiness levels. Consequently, the synthesized technology adoption constructs of this study present strong indicators for future of work readiness from an organizational perspective.…”

Section: Discussionmentioning

confidence: 99%

“…60,93 Therefore, upskilling for the future of work is a critical factor to ensure organizational readiness for the 4IR. 84 Human capital is by no means a new concept. However, with this paradigm, new workforce challenges and an entrepreneurial spirit are needed.…”

Section: Toe Organizationmentioning

confidence: 99%

Leveraging technology adoption to navigate the 4IR towards a future‐ready business: A systematic literature review

Kruger,

Steyn

2023

Engineering Reports

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The purpose of this study was to analyze technology adoption constructs that are instrumental for organizations to effectively utilize emerging technologies, enabling them to navigate the complexities and opportunities presented by the fourth industrial revolution (4IR). To achieve this a descriptive research approach was used, guided by a systematic review of literature from 2016 to 2022. Among the 4037 studies initially identified, only 69 were deemed relevant. Meta‐synthesis was then used to systematically identify, categorize, and quantify fundamental constructs inherent in the models from the relevant literature. As a result of this process, 406 constructs were identified across six thematic categories. These were subsequently integrated to develop a conceptual model that can be used to coordinate strategies to harness the potential of the 4IR towards a future‐ready business. Findings show that the role of technology adoption remains pertinent in the ever‐digitized world in which businesses operate and certain constructs are key to explain, support, and predict enterprise‐wide adoption in the 4IR paradigm. Future studies can expand and test the model to promote digital fluency required by business constituents, noting differences across sectors.

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“…As the software industries frequently impart vital technical changes, low-code platforms highlight a high level of concern for data insights and provision of efficient and reliable solutions [143]. Furthermore, the use of cloud services as the dominant computing platform aids in creating rich immersive experiences for learners in the metaverse environment.…”

Section: Low-code Platformsmentioning

confidence: 99%

Advancing Education Through Extended Reality and Internet of Everything Enabled Metaverses: Applications, Challenges, and Open Issues

Jagatheesaperumal¹,

Ahmad²,

Al-Fuqaha³

et al. 2022

Preprint

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Metaverse has evolved as one of the popular research agendas that let the users learn, socialize, and collaborate in a networked 3D immersive virtual world. Due to the rich multimedia streaming capability and immersive user experience with high-speed communication, the metaverse is an ideal model for education, training, and skill development tasks. To facilitate research in this area, we provide a comprehensive review of the various educational use cases and explore how enabling technologies such as Extended reality (XR) and Internet of Everything (IoE) will play a major role in educational services in future metaverses. Secondly, we provide an overview of metaverse-based educational applications focusing on education, training, and skill development and analyze the technologies they are built upon. We identify common research problems and future research directions in the domain. The paper also identifies core ethical considerations of metaverse for education and potential pitfalls. We believe this survey can fully demonstrate the versatility of metaverse-driven education, which could serve as a potential guideline for the researchers.

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Trends and Trajectories in the Software Industry: implications for the future of work

Cited by 17 publications

References 60 publications

How to explain AI systems to end users: a systematic literature review and research agenda

How to explain AI systems to end users: a systematic literature review and research agenda

Leveraging technology adoption to navigate the 4IR towards a future‐ready business: A systematic literature review

Advancing Education Through Extended Reality and Internet of Everything Enabled Metaverses: Applications, Challenges, and Open Issues

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