Humans are not Machines - Anthropocentric Human-Machine Symbiosis for Ultra-Flexible Smart Manufacturing

Lu, Yuqian; Adrados, Juvenal Sastre; Chand, Saahil; Wang, Lihui

doi:10.36227/techrxiv.14132528.v4

Cited by 7 publications

(6 citation statements)

References 41 publications

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“…In recent years, this perspective has become particularly popular, eschewing AutoML as an outright replacement for human roles. Instead, the purposes of AutoML are increasingly seen as augmenting the capabilities of users [183] and countering the constraints/limitations of human cognition [158]. Naturally, it is still the role of domain experts to precisely define/constrain a problem and its context, as the presently hypothesised form of an AutonoML system has neither individual agency nor a versatile understanding of concept.…”

Section: Roles and Modes When Human Involvement Is No Longer Requiredmentioning

confidence: 99%

The Roles and Modes of Human Interactions with Automated Machine Learning Systems

Khuat¹,

Kedziora²,

Gabrys³

2022

Preprint

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As automated machine learning (AutoML) systems continue to progress in both sophistication and performance, it becomes important to understand the 'how' and 'why' of human-computer interaction (HCI) within these frameworks, both current and expected. Such a discussion is necessary for optimal system design, leveraging advanced data-processing capabilities to support decision-making involving humans, but it is also key to identifying the opportunities and risks presented by ever-increasing levels of machine autonomy. Within this context, we focus on the following questions: (i) How does HCI currently look like for state-of-the-art AutoML algorithms, especially during the stages of development, deployment, and maintenance? (ii) Do the expectations of HCI within AutoML frameworks vary for different types of users and stakeholders? (iii) How can HCI be managed so that AutoML solutions acquire human trust and broad acceptance? (iv) As AutoML systems become more autonomous and capable of learning from complex open-ended environments, will the fundamental nature of HCI evolve? To consider these questions, we project existing literature in HCI into the space of AutoML; this connection has, to date, largely been unexplored. In so doing, we review topics including user-interface design, human-bias mitigation, and trust in artificial intelligence (AI). Additionally, to rigorously gauge the future of HCI, we contemplate how AutoML may manifest in effectively open-ended environments. This discussion necessarily reviews projected developmental pathways for AutoML, such as the incorporation of reasoning, although the focus remains on how and why HCI may occur in such a framework rather than on any implementational details. Ultimately, this review serves to identify key research directions aimed at better facilitating the roles and modes of human interactions with both current and future AutoML systems.

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Section: Roles and Modes When Human Involvement Is No Longer Requiredmentioning

confidence: 99%

The Roles and Modes of Human Interactions with Automated Machine Learning Systems

Khuat¹,

Kedziora²,

Gabrys³

2022

Preprint

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“…Industry workers are considered "investments" rather than "costs". (Lu et al, 2021). Lean construction encircles similar principles and core values.…”

Section: The Need For a Novel Human-centricmentioning

confidence: 99%

“…Industry 5.0 is considered a shift in perspective, where the same technology used in I4.0 is now designed and used to serve people and societies meeting the needs of industry workers. Industry workers are considered "investments" rather than "costs" (Lu et al, 2021)…”

mentioning

confidence: 99%

The Need for a Human Centric Approach in C4.0 Technologies

Noueihed¹,

Hamzeh²

2022

Proc. 30th Annual Conference of the International Group for Lean Construction (IGLC)

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Construction industry is amidst a radical shift towards digitalization. The promising benefits of Construction 4.0 (C4.0) are yet to be harvested; however, the implications of the C4.0 technologies are still being explored after adoption. Among the various impacts of adoption are social impacts, which have been overlooked in this fast-paced revolution despite their grave consequences on the industry and the people involved. This paper explores the literature on the social impacts of these technologies and tackles artificial intelligence as a specific case. This study compares different findings, analyzes them, and reflects on how practitioners need to consider a more humane approach when implementing new technologies.

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“…The well-being of workers will be a new opportunity in HCSM, and workers will move from being seen as a "cost" to an "investment" [57]. This change means that the future HMI technology will consider the needs and diversity of workers.…”

Section: Opportunitiesmentioning

confidence: 99%

Review of Human-Machine Interaction Towards Industry 5.0: Human-Centric Smart Manufacturing

Yang

Liu

et al. 2022

Volume 2: 42nd Computers and Information in Engineering Conference (CIE)

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Human-centric smart manufacturing (HCSM) is one of the essential pillars in Industry 5.0. Hence, human-machine interaction (HMI), as the centre of the research agenda for the advances of smart manufacturing, has also become the focus of Industry 5.0. As Industry 5.0 proposed three core concepts of human-centric, sustainable and resilient, the design orientation of HMI needs to change accordingly. Through understanding the state-of-the-art of HMI research, the technology roadmap of HMI development in the smart manufacturing paradigm can be shaped. In this paper, the focus is to review how HMI has been applied in smart manufacturing and predict future opportunities and challenges when applying HMI to HCSM. In this paper, we provide an HMI framework based on the interaction process and analyse the existing research on HMI across four key aspects: 1) Sensor and Hardware, 2) Data Processing, 3) Transmission Mechanism, and 4) Interaction and Collaboration. We intend to analyse the current development and technologies of each aspect and their possible application in HCSM. Finally, potential challenges and opportunities in future research and applications of HMI are discussed and evaluated, especially considering that the focus of design in HCSM shifts from improving productivity to the well-being of workers and sustainability.

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Humans are not Machines - Anthropocentric Human-Machine Symbiosis for Ultra-Flexible Smart Manufacturing

Cited by 7 publications

References 41 publications

The Roles and Modes of Human Interactions with Automated Machine Learning Systems

The Roles and Modes of Human Interactions with Automated Machine Learning Systems

The Need for a Human Centric Approach in C4.0 Technologies

Review of Human-Machine Interaction Towards Industry 5.0: Human-Centric Smart Manufacturing

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