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Article
Publication date: 3 December 2024

Olusegun Emmanuel Akinwale, Owolabi Lateef Kuye and Indrajit Doddanavar

The emergence of artificial intelligence (AI) which operates through technology and digital workspace has proven to transform organisations in recent times. However, there has…

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Abstract

Purpose

The emergence of artificial intelligence (AI) which operates through technology and digital workspace has proven to transform organisations in recent times. However, there has been key concern over its efficiency among the workforce on how it may replace human intelligence in the contemporary work environment. This study aims to investigate the drawbacks otherwise known as the dark side of AI and its effect on employee quality of work−life and organisational performance through the lens of employee capacity development in reducing its shortcomings.

Design/methodology/approach

This study used a descriptive research design using a cross-sectional survey approach to administer the research instrument to 1,847 customer service officers of banks, customer agents of telecoms, customer care of retail organisations in Nigeria business environment across various units were respondents of this study, however, 862 participants were finally used. A simple random strategy was used to survey the study participants, and existing scales were adopted to form a new research instrument. A partial least square (PLS) based structural equation model (SEM) was adapted to analyse the collected data from the respondents.

Findings

The outcome of the study indicated that AI lacks creativity and has a negative impact on both employee quality of work−life and overall organisational performance. The outcome of the study demonstrated the drawbacks and the dark sides of AI as lack of emotional intelligence, lack of in-depth contextual knowledge, over-reliance on data quality and lack of ethical and moral decision analysis are the possible dark side of AI which adversely affect quality of work−life and overall performance of the organisations. The study concluded that it is difficult to replace human intelligence because of AI’s drawbacks and dark side. AI cannot function effectively beyond what is programmed in the system.

Originality/value

This study has offered a novel trajectory against the efficiency and possible benefits of AI that people are familiar with. It has changed the understanding of the researchers, policymakers and organisations that AI cannot replace human intelligence in the workplace without improvement on those established AI dark sides.

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Article
Publication date: 21 February 2025

Simona Curiello, Enrica Iannuzzi, Dirk Meissner and Claudio Nigro

This work provides an overview of academic articles on the application of artificial intelligence (AI) in healthcare. It delves into the innovation process, encompassing a…

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Abstract

Purpose

This work provides an overview of academic articles on the application of artificial intelligence (AI) in healthcare. It delves into the innovation process, encompassing a two-stage trajectory of exploration and development followed by dissemination and adoption. To illuminate the transition from the first to the second stage, we use prospect theory (PT) to offer insights into the effects of risk and uncertainty on individual decision-making, which potentially lead to partially irrational choices. The primary objective is to discern whether clinical decision support systems (CDSSs) can serve as effective means of “cognitive debiasing”, thus countering the perceived risks.

Design/methodology/approach

This study presents a comprehensive systematic literature review (SLR) of the adoption of clinical decision support systems (CDSSs) in healthcare. We selected English articles dated 2013–2023 from Scopus, Web of Science and PubMed, found using keywords such as “Artificial Intelligence,” “Healthcare” and “CDSS.” A bibliometric analysis was conducted to evaluate literature productivity and its impact on this topic.

Findings

Of 322 articles, 113 met the eligibility criteria. These pointed to a widespread reluctance among physicians to adopt AI systems, primarily due to trust-related issues. Although our systematic literature review underscores the positive effects of AI in healthcare, it barely addresses the associated risks.

Research limitations/implications

This study has certain limitations, including potential concerns regarding generalizability, biases in the literature review and reliance on theoretical frameworks that lack empirical evidence.

Originality/value

The uniqueness of this study lies in its examination of healthcare professionals’ perceptions of the risks associated with implementing AI systems. Moreover, it addresses liability issues involving a range of stakeholders, including algorithm developers, Internet of Things (IoT) manufacturers, communication systems and cybersecurity providers.

Details

European Journal of Innovation Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1460-1060

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