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This study aims to investigate how living lab (LL) activities align with responsible research and innovation (RRI) principles, particularly in artificial intelligence (AI)-driven digital transformation (DT) processes. The study seeks to define a framework termed “responsible living lab” (RLL), emphasizing transparency, stakeholder engagement, ethics and sustainability. This emerging issue paper also proposes several directions for future researchers in the field.

The research methodology involved a literature review complemented by insights from a workshop on defining RLLs. The literature review followed a concept-centric approach, searching key journals and conferences, yielding 32 relevant articles. Backward and forward citation analysis added 19 more articles. The workshop, conducted in the context of UrbanTestbeds.JR and SynAir-G projects, used a reverse brainstorming approach to explore potential ethical and responsible issues in LL activities. In total, 13 experts engaged in collaborative discussions, highlighting insights into AI’s role in promoting RRI within LL activities. The workshop facilitated knowledge sharing and a deeper understanding of RLL, particularly in the context of DT and AI.

This emerging issue paper highlights ethical considerations in LL activities, emphasizing user voluntariness, user interests and unintended participation. AI in DT introduces challenges like bias, transparency and digital divide, necessitating responsible practices. Workshop insights underscore challenges: AI bias, data privacy and transparency; opportunities: inclusive decision-making and efficient innovation. The synthesis defines RLLs as frameworks ensuring transparency, stakeholder engagement, ethical considerations and sustainability in AI-driven DT within LLs. RLLs aim to align DT with ethical values, fostering inclusivity, responsible resource use and human rights protection.

The proposed definition of RLL introduces a framework prioritizing transparency, stakeholder engagement, ethics and sustainability in LL activities, particularly those involving AI for DT. This definition aligns LL practices with RRI, addressing ethical implications of AI. The value of RLL lies in promoting inclusive and sustainable innovation, prioritizing stakeholder needs, fostering collaboration and ensuring environmental and social responsibility throughout LL activities. This concept serves as a foundational step toward a more responsible and sustainable LL approach in the era of AI-driven technologies.

Despite all the recent achievements in the field of interactive marketing and artificial intelligence (AI), it is important to consider the ethical implications of these technologies. This paper explains the concept of corporate digital responsibility (CDR) and how it is affected by new advances in AI.

The authors build on the work of Wirtz et al., (2023) and derive several managerial implications for the challenges that AI poses to CDR. CDR refers to a service company's ethical and fair use of data and technology within its digital service ecosystem. It involves establishing standards, protecting customer privacy, conducting external audits and striving for an equitable power dynamic between service firms and their partners.

Despite the risks involved, many companies are not prioritizing good CDR practices. Financial benefits from the collection and use of consumer data, improved customer experience through AI-driven customization and personalization, cost reduction through service automation and the trade-offs between organizational goals and CDR practices can prevent companies from prioritizing good CDR practices.

This is one of the first articles in the service domain to take the concept of CDR and apply it to recent developments in generative AI.

The emergence of powerful AI tools presents opportunities and challenges. Research opportunities include responsible business restructuring, responsible service automation to ensure fairness and human oversight, addressing dehumanization of service delivery, responsible customer profiling to address privacy and discrimination concerns and preventing AI misuse.

This paper aims to present affective computing or Emotion AI in the context of work and how organizational leaders such as managers and human resource (HR) professionals can implement this technology to foster an emotionally healthy workplace.

The authors provide a current overview of affective computing technology through definitions, examples and general use cases. This is in light of the current scrutiny on artificial intelligence (AI) use broadly across society. The authors address this from a research perspective and show how this advanced AI tool can be implemented in organizations for the benefit of employees.

Affective computing or Emotion AI is still relatively unknown, and yet, it is already part of our daily lives. Emotion AI platforms have the potential to be an essential part of HR tools. It is crucial, however, to use this technology in an ethical and responsible manner.

There is little awareness and understanding of use cases of affective computing tools in organizations, particularly for the well-being of the workforce. This paper provides HR leaders, managers and researchers with an overview of the origins of the field and major considerations for responsibly implementing Emotion AI to support employee mental health.

The purpose of this study is to investigate the impact of artificial intelligence (AI) on the human rights issue. This study has also examined issues with AI for business and its civil and criminal liability. This study has provided inputs to the policymakers and government authorities to overcome different challenges.

This study has analysed different international and Indian laws on human rights issues and the impacts of these laws to protect the human rights of the individual, which could be under threat due to the advancement of AI technology. This study has used descriptive doctrinal legal research methods to examine and understand the insights of existing laws and regulations in India to protect human rights and how these laws could be further developed to protect human rights under the Indian jurisprudence, which is under threat due to rapid advancement of AI-related technology.

The study provides a comprehensive insight on the influence of AI on human rights issues and the existing laws in India. The study also shows different policy initiatives by the Government of India to regulate AI.

The study highlights some of the key policy recommendations helpful to regulate AI. Moreover, this study provides inputs to the regulatory authorities and legal fraternity to draft a much-needed comprehensive policy to regulate AI in the context of the protection of human rights of the citizens.

AI is constantly posing entangled challenges to human rights. There is no comprehensive study, which investigated the emergence of AI and its influence on human rights issues, especially from the Indian legal perspective. So there is a research gap. This study provides a unique insight of the emergence of AI applications and its influence on human rights issues and provides inputs to the policymaker to help them to draft an effective regulation on AI to protect the human rights of Indian citizens. Thus, this study is considered a unique study that adds value towards the overall literature.

The purpose of this study is to raise awareness about the ethical implications of artificial intelligence (AI) in the library and information industry, specifically focusing on bias and discrimination. It aims to highlight the need for proactive measures to mitigate these issues and ensure that AI technology is developed and implemented in an ethical and unbiased manner.

This viewpoint paper presents a critical analysis of the ethical implications of bias and discrimination in the library and information industry with respect to AI. It explores current practices and challenges in AI implementation and proposes strategies to address bias and discrimination in AI systems.

The findings of this study reveal that bias and discrimination are significant concerns in AI systems used in the library and information industry. These biases can perpetuate existing inequalities, hinder access to information and reinforce discriminatory practices. This study identifies key strategies such as data collection and representation, algorithmic transparency and inclusive design to address these issues.

This study contributes to the existing literature by examining the specific challenges of bias and discrimination in AI implementation within the library and information industry. It provides valuable insights into the ethical implications of AI technology and offers practical recommendations for professionals to confront and mitigate bias and discrimination in AI systems, ensuring equitable access to information for all users.

This study aims to identify and assess the key ethical challenges associated with integrating artificial intelligence (AI) in knowledge-sharing (KS) practices and their implications for decision-making (DM) processes within organisations.

The study employs a mixed-methods approach, beginning with a comprehensive literature review to extract background information on AI and KS and to identify potential ethical challenges. Subsequently, a confirmatory factor analysis (CFA) is conducted using data collected from individuals employed in business settings to validate the challenges identified in the literature and assess their impact on DM processes.

The findings reveal that challenges related to privacy and data protection, bias and fairness and transparency and explainability are particularly significant in DM. Moreover, challenges related to accountability and responsibility and the impact of AI on employment also show relatively high coefficients, highlighting their importance in the DM process. In contrast, challenges such as intellectual property and ownership, algorithmic manipulation and global governance and regulation are found to be less central to the DM process.

This research contributes to the ongoing discourse on the ethical challenges of AI in knowledge management (KM) and DM within organisations. By providing insights and recommendations for researchers, managers and policymakers, the study emphasises the need for a holistic and collaborative approach to harness the benefits of AI technologies whilst mitigating their associated risks.

India is a fast-growing economy, that has a majority share in the global information technology industry (IT). Rapid urbanisation and modernisation in India have strained its energy sector, which is being reformed to cope. Despite being the global IT heart and having above average research output in the field of artificial intelligence (AI), India has not yet managed to leverage its benefits to the full. This study aims to address the role of AI and information management (IM) in India’s energy transition to highlight the challenges and barriers to its development and use in the energy sector.

The study, through analysis of proposed strategies, current policies, available literature and reports, discusses the role of AI and IM in the energy transition in India, highlighting the current situation and challenges.

The results show dispersed research and development incentives for IT in the Indian energy sector; however, the needed holistic top-down approach is lacking, calling for due attention in this matter. Adaptive and swift actions from policymakers towards AI and IM are warranted in India.

The ongoing transition of the Indian energy sector with the integration of smart technologies would result in increased access to big data. Extracting the maximum benefits from this would require a comprehensive AI and IM policy.

The revolution in AI and robotics must be carried out in line with sustainable development goals, to support climate action and to consider privacy issues – both areas in India must be strengthened.

The paper offers an original discussion on certain applicable solutions regarding the energy transition of AI coming from the Global South; they are based on lessons learned from the Indian case studies presented in this study.

Harnessing the power and potential of Artificial Intelligence (AI) continues a centuries-old trajectory of the application of science and knowledge for the benefit of humanity. Such an endeavor has great promise, but also the possibility of creating conflict and disorder. This chapter draws upon the strengths of the previous chapters to provide readers with a purposeful assessment of the current AI security landscape, concluding with four key considerations for a globally secure future.

This study aims to examine the current state of academic research pertaining to the role played by artificial intelligence (AI) in the achievement of a critical sustainable development goal (SDG) – poverty alleviation and describe the field’s development by identifying themes, trends, roadblocks and promising areas for the future.

The authors analysed a corpus of 253 studies collected from the Scopus database to examine the current state of the academic literature using bibliometric methods.

This paper identifies and analyses key trends in the evolution of this domain. Further, the paper distils the extant literature to unpack the intermediary mechanisms through which AI and related technologies help tackle the critical global issue of poverty.

The corpus of literature used for the analysis is limited to English language studies from the Scopus database. The paper contributes to the extant research on AI for social good, and more broadly to the research on the value of emerging technologies such as AI.

Policymakers and government agencies will get an understanding of how technological interventions such as AI can help achieve critical SDGs such as poverty alleviation (SDG-1).

The primary focus of this paper is on the role of AI-related technological interventions to achieve a significant social objective – poverty alleviation.

To the best of the authors’ knowledge, this is the first study to conduct a comprehensive bibliometric analysis of a critical research domain such as AI and poverty alleviation.