The road to a human-centred digital society: opportunities, challenges and responsibilities for humans in the age of machines

Cremer, David De; Narayanan, Devesh; Deppeler, Andreas; Nagpal, Mahak; McGuire, Jack

doi:10.1007/s43681-021-00116-6

Cited by 17 publications

(12 citation statements)

References 10 publications

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“…Pisoni et al [41] emphasized the significance of delivering AI that is suitable for everyone from various fields of knowledge and experience, such as interaction design, pedagogical design, and participatory design, and it shows how recent and future AI advancements can be used to improve and broaden online and in-person accessibility. De Cremer et al [42] also argued that the increasing usage of advanced systems has led us to a fork in the path. De Cremer et al [42] went on to state that intelligent technology producers are gaining the ability to introduce a plethora of things that are significant to human end-users.…”

Section: Empirical Literature Reviewmentioning

confidence: 99%

“…De Cremer et al [42] also argued that the increasing usage of advanced systems has led us to a fork in the path. De Cremer et al [42] went on to state that intelligent technology producers are gaining the ability to introduce a plethora of things that are significant to human end-users. The very same smart technology, according to De Cremer et al [42], is also utilized, deliberately, to degrade and, sometimes, even intentionally hurt the interests of those same end-users.…”

Section: Empirical Literature Reviewmentioning

confidence: 99%

“…De Cremer et al [42] went on to state that intelligent technology producers are gaining the ability to introduce a plethora of things that are significant to human end-users. The very same smart technology, according to De Cremer et al [42], is also utilized, deliberately, to degrade and, sometimes, even intentionally hurt the interests of those same end-users. Consequently, in the lack of a recalibration, technological solutions will, almost surely, represent the interests of technology developers and owners rather than the interests of humanity.…”

Section: Empirical Literature Reviewmentioning

confidence: 99%

“…A human-centred AI strategy aims to establish and implement AI systems in manners that enhance humanity and suit their interests. To achieve this goal, we acknowledge that a human-centred AI strategy should promote and strengthen people's feelings of competency, participation, authority, and well-being [42,47]. The question, now, is what is human-centred AI?…”

Section: The Meaning Of Human-centred Aimentioning

confidence: 99%

“…Figure 6, below, outlines the benefits of human-centred AI to various stakeholders. participation, authority, and well-being [42,47]. The question, now, is what is human-centred AI?…”

Section: The Meaning Of Human-centred Aimentioning

confidence: 99%

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Human-Centered Artificial Intelligence: The Superlative Approach to Achieve Sustainable Development Goals in the Fourth Industrial Revolution

Mhlanga

2022

Sustainability

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Artificial intelligence (AI) is currently being developed by large corporations, and governments all over the world are yearning for it. AI isn’t a futuristic concept; it is already here, and it is being implemented in a range of industries. Finance, national security, health care, criminal justice, transportation, and smart cities are all examples of this. There are countless examples of AI having a substantial impact on the world and complementing human abilities. However, due to the immense societal ramifications of these technologies, AI is on the verge of disrupting a host of industries, so the technique by which AI systems are created must be better understood. The goal of the study was to look at what it meant to be human-centred, how to create human-centred AI, and what considerations should be made for human-centred AI to achieve sustainability and the SDGs. Using a systematic literature review technique, the study discovered that a human-centred AI strategy strives to create and implement AI systems in ways that benefit mankind and serve their interests. The study also found that a human-in-the-loop concept should be used to develop procedures for creating human-centred AI, as well as other initiatives, such as the promotion of AI accountability, encouraging businesses to use autonomy wisely, to motivate businesses to be aware of human and algorithmic biases, to ensure that businesses prioritize customers, and form multicultural teams to tackle AI research. The study concluded with policy recommendations for human-centred AI to help accomplish the SDGs, including expanding government AI investments, addressing data and algorithm biases, and resolving data access issues, among other things.

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Section: Empirical Literature Reviewmentioning

confidence: 99%

Section: Empirical Literature Reviewmentioning

confidence: 99%

Section: Empirical Literature Reviewmentioning

confidence: 99%

Section: The Meaning Of Human-centred Aimentioning

confidence: 99%

“…Figure 6, below, outlines the benefits of human-centred AI to various stakeholders. participation, authority, and well-being [42,47]. The question, now, is what is human-centred AI?…”

Section: The Meaning Of Human-centred Aimentioning

confidence: 99%

See 3 more Smart Citations

Human-Centered Artificial Intelligence: The Superlative Approach to Achieve Sustainable Development Goals in the Fourth Industrial Revolution

Mhlanga

2022

Sustainability

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The self‐regulatory consequences of dependence on intelligent machines at work: Evidence from field and experimental studies

Tang

Koopman

Yam

et al. 2022

Human Resource Management

Self Cite

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Organizations are increasingly augmenting employee jobs with intelligent machines. Although this augmentation has a bright side, in terms of its ability to enhance employee performance, we think there is likely a dark side as well. Draw from self‐regulation theory, we theorize that dependence on intelligent machines is discrepancy‐reducing—enhancing work goal progress, which in turn boosts employees’ task performance. On the other hand, such dependence may be discrepancy‐enlarging—threatening employee self‐esteem, which in turn detracts from employees’ task performance. Drawing further from self‐regulation theory, we submit that employees’ core self‐evaluation (CSE) may influence these effects of dependence on intelligent machines. Across an experience‐sampling field study conducted in India (Study 1) and a simulation‐based experiment conducted in the United States (Study 2), our results generally support a “mixed blessing” perspective of intelligent machines at work. We conclude by discussing the theoretical and practical implications of our work.

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Recruitment chatbot acceptance in a company: a mixed method study on human-centered technology acceptance model

Akram,

Buono,

Lanzilotti

2024

Pers Ubiquit Comput

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This study developed a Human-Centered Technology Acceptance Model (HC-TAM) for recruitment chatbots, integrating aspects of the traditional Technology Acceptance Model (TAM)(Davis in 1989) with a focus on human-centered factors such as transparency, personalization, efficiency, and ethical concerns, alongside the fundamental TAM constructs of perceived ease of use and perceived usefulness. The study shows that the intention to use technology is influenced by their perceptions of its usefulness and ease of use. By extending TAM to include human-centered considerations, this research aimed to capture the diverse factors that significantly influence users’ acceptance of chatbots in the recruitment process. A three-phase study has been carried out, each serving a distinct purpose. (a) Phase 1 focuses on defining primary themes through qualitative interviews with 10 participants, laying the foundation for subsequent research. (b)Building upon this foundation, Phase 2 engages 28 participants in a refined exploration of these themes, ending in a comprehensive landscape of user perspectives. (c) Finally, Phase 3 employs rigorous Structural Equation Modeling for theoretical framework examination, yielding critical constructs and hypotheses. Moreover, Phase 3 encompasses the thorough development of measurement instruments and extensive data collection, involving 146 participants through questionnaires, the study found that the acceptance of recruitment chatbots is significantly enhanced when these systems are designed to be transparent, provide personalized interactions, efficiently fulfill user needs, and address ethical concerns. These findings contribute to the broader understanding of technology acceptance in the context of recruitment, offering valuable insights for developers and designers to create chatbots that are not only technically advanced but also ethically sound, user-friendly, and effectively aligned with human needs and expectations in recruitment settings.

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The road to a human-centred digital society: opportunities, challenges and responsibilities for humans in the age of machines

Cited by 17 publications

References 10 publications

Human-Centered Artificial Intelligence: The Superlative Approach to Achieve Sustainable Development Goals in the Fourth Industrial Revolution

Human-Centered Artificial Intelligence: The Superlative Approach to Achieve Sustainable Development Goals in the Fourth Industrial Revolution

The self‐regulatory consequences of dependence on intelligent machines at work: Evidence from field and experimental studies

Recruitment chatbot acceptance in a company: a mixed method study on human-centered technology acceptance model

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