AI4People

Lütge, Christoph; Poszler, Franziska; Acosta, Aida Joaquin; Danks, David; Gottehrer, Gail; Mihet‐Popa, Lucian; Naseer, Aisha

doi:10.4018/ijt.20210101.oa2

Cited by 10 publications

(8 citation statements)

References 15 publications

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“…Soft governance also includes AI ethics (de Almeida et al, 2021;Cath, 2018), with commonly discussed principles, such as technical robustness, data security, privacy, reliability, transparency, fairness and accountability (de Almeida et al, 2021;Gasser and Almeida, 2017;L€ utge et al, 2021;Winfield and Jirotka, 2018;Wu et al, 2020). Researchers seem to have a consensus that the existing ethical principles should aim to articulate the general human values that AI deployments address and that the principles act as practical guidelines for AI developers ( Oh Eigeartaigh et al, 2020;Whittlestone et al, 2019).…”

Section: Ai Governancementioning

confidence: 99%

“…Governance of artificial intelligence (AI) has been defined as "a system of rules, practices, processes, and technological tools that are employed to ensure an organization's use of AI technologies aligns with the organization's strategies, objectives, and values; fulfills legal requirements; and meets principles of ethical AI followed by the organization" (M€ antym€ aki et al, 2022a). AI has become an object of governance because AI applications are increasingly widespread in many application areas across the private and public sectors (L€ utge et al, 2021;Reddy et al, 2020). As an umbrella term, AI refers to a research field (Zhang and Lu, 2021), a set of information system capabilities of interpreting data, learning and adaptation (Kaplan and Haenlein, 2019), as well as a more general moving frontier of cutting-edge computing (Berente et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

“…Importantly, AI is also becoming prevalent in so-called high-risk application areas (European Commission, 2020), including healthcare (Reddy et al. , 2020), automobiles (Lütge et al. , 2021) and finance (Lee, 2020).…”

Section: Introductionmentioning

confidence: 99%

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AI governance: themes, knowledge gaps and future agendas

Birkstedt

Minkkinen

Tandon

et al. 2023

INTR

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PurposeFollowing the surge of documents laying out organizations' ethical principles for their use of artificial intelligence (AI), there is a growing demand for translating ethical principles to practice through AI governance (AIG). AIG has emerged as a rapidly growing, yet fragmented, research area. This paper synthesizes the organizational AIG literature by outlining research themes and knowledge gaps as well as putting forward future agendas.Design/methodology/approachThe authors undertake a systematic literature review on AIG, addressing the current state of its conceptualization and suggesting future directions for AIG scholarship and practice. The review protocol was developed following recommended guidelines for systematic reviews and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA).FindingsThe results of the authors’ review confirmed the assumption that AIG is an emerging research topic with few explicit definitions. Moreover, the authors’ review identified four themes in the AIG literature: technology, stakeholders and context, regulation and processes. The central knowledge gaps revealed were the limited understanding of AIG implementation, lack of attention to the AIG context, uncertain effectiveness of ethical principles and regulation, and insufficient operationalization of AIG processes. To address these gaps, the authors present four future AIG agendas: technical, stakeholder and contextual, regulatory, and process. Going forward, the authors propose focused empirical research on organizational AIG processes, the establishment of an AI oversight unit and collaborative governance as a research approach.Research limitations/implicationsTo address the identified knowledge gaps, the authors present the following working definition of AIG: AI governance is a system of rules, practices and processes employed to ensure an organization's use of AI technologies aligns with its strategies, objectives, and values, complete with legal requirements, ethical principles and the requirements set by stakeholders. Going forward, the authors propose focused empirical research on organizational AIG processes, the establishment of an AI oversight unit and collaborative governance as a research approach.Practical implicationsFor practitioners, the authors highlight training and awareness, stakeholder management and the crucial role of organizational culture, including senior management commitment.Social implicationsFor society, the authors review elucidates the multitude of stakeholders involved in AI governance activities and complexities related to balancing the needs of different stakeholders.Originality/valueBy delineating the AIG concept and the associated research themes, knowledge gaps and future agendas, the authors review builds a foundation for organizational AIG research, calling for broad contextual investigations and a deep understanding of AIG mechanisms. For practitioners, the authors highlight training and awareness, stakeholder management and the crucial role of organizational culture, including senior management commitment.

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Section: Ai Governancementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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AI governance: themes, knowledge gaps and future agendas

Birkstedt

Minkkinen

Tandon

et al. 2023

INTR

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“…Since this topic is very critical and it limits the development of AVs, recently, ethical guidelines for the automotive sectors have been released by detailing the fundamental requirements and practical recommendations for both industries and policymakers [99]. Particularly, in 2019 seven fundamental requirements were proposed by the High-level Expert Group on Artificial Intelligence, which included "human agency and oversight", "technical robustness and safety", "privacy and data governance, transparency", "diversity, non-discrimination and fairness", "societal and environmental wellbeing" and "accountability".…”

Section: Ethical Issuesmentioning

confidence: 99%

“…Table 6 summarizes the seven requirements by highlighting their key concerns and brief descriptions. Interested readers can refer to [99] for more details. AVs must allow a level of autonomy to the human drivers.…”

Section: Ethical Issuesmentioning

confidence: 99%

Enabling Technologies for Urban Smart Mobility: Recent Trends, Opportunities and Challenges

Paiva

Ahad

Tripathi

et al. 2021

Sensors

128

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The increasing population across the globe makes it essential to link smart and sustainable city planning with the logistics of transporting people and goods, which will significantly contribute to how societies will face mobility in the coming years. The concept of smart mobility emerged with the popularity of smart cities and is aligned with the sustainable development goals defined by the United Nations. A reduction in traffic congestion and new route optimizations with reduced ecological footprint are some of the essential factors of smart mobility; however, other aspects must also be taken into account, such as the promotion of active mobility and inclusive mobility, encouraging the use of other types of environmentally friendly fuels and engagement with citizens. The Internet of Things (IoT), Artificial Intelligence (AI), Blockchain and Big Data technology will serve as the main entry points and fundamental pillars to promote the rise of new innovative solutions that will change the current paradigm for cities and their citizens. Mobility-as-a-service, traffic flow optimization, the optimization of logistics and autonomous vehicles are some of the services and applications that will encompass several changes in the coming years with the transition of existing cities into smart cities. This paper provides an extensive review of the current trends and solutions presented in the scope of smart mobility and enabling technologies that support it. An overview of how smart mobility fits into smart cities is provided by characterizing its main attributes and the key benefits of using smart mobility in a smart city ecosystem. Further, this paper highlights other various opportunities and challenges related to smart mobility. Lastly, the major services and applications that are expected to arise in the coming years within smart mobility are explored with the prospective future trends and scope.

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The Old Moral Dilemma of “Me or You”

Colurcio

Altimari

2021

Lecture Notes in Networks and Systems

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AI4People

Cited by 10 publications

References 15 publications

AI governance: themes, knowledge gaps and future agendas

AI governance: themes, knowledge gaps and future agendas

Enabling Technologies for Urban Smart Mobility: Recent Trends, Opportunities and Challenges

The Old Moral Dilemma of “Me or You”

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