The future of manufacturing: Utopia or dystopia?

Abstract

Digital manufacturing technologies (DMTs) have the potential to transform industry productivity, but their introduction into the workplace is often a complex process, requiring not only technical expertise but also an awareness of ethical and societal challenges surrounding human-system integration. Concerns about the introduction of new technology have been prevalent throughout history, and exploring public perceptions of these technologies can provide insight to help address such cultural anxieties. However, evaluating user perceptions of futuristic technology is difficult, requiring novel approaches to provide context and understanding. To explore users' perceptions of future DMTs, we applied the ContraVision technique in a questionnaire-based study. Participants viewed films, representing fictionalized utopic and dystopic visions of what the future of these DMTs might involve, and a questionnaire probed the perceptions of the technologies afterward. Findings showed that irrespective of the way technology was portrayed, participants had concerns about the ethical and responsible implementation of these tools. Participant responses were analyzed to identify key challenges for policy surrounding DMT implementation in the future of manufacturing.

A human-centered perspective on individual risks for digital innovation management: an integrative conceptual review

“…Under these auspices, scholars have also considered models within ergonomics and human factors literature. This is the case of a number of studies exploring the direct effects and psychosocial risks of digital technology on workers (Marinescu et al, 2023;Papetti et al, 2020;Papetti et al, 2021;Thyl en et al, 2023). Some occupation-specific studies looked at the physical effects of digital technologies on body posture of body techniques and occurrence of musculoskeletal disorders (Cunha et al, 2022;Wixted et al, 2018).…”

“…Several researchers view lack of trust, reluctance to accept and resistance to change as core interrelated determinants extending across the digital technologies, i.e. interaction with Cobots and automated guided vehicles (AGVs) (Ghadimi et al, 2022;Hopko and Metha, 2022;Hopko et al, 2023;Meissner et al, 2020;Marinescu et al, 2023;Panchetti et al, 2023); AI, Cloud computing and Big data (Birkel et al, 2019;Gangwar and Date, 2016;Ghadimi et al, 2022); AR/ VR technologies and smart wearables (Gong et al, 2019).…”

“…Societal aspects. A small number of contributions reported how social acceptability (Kumar et al, 2022) and people's view of technology as utopian or dystopian can determine the probability to accept technologies (Marinescu et al, 2023). Lastly, the extent to which governments support and develop policies to safely regulate the implementation of technologies is regarded as an important driver for the future success of industrial digitalization (Meissner et al, 2020).…”

“…Information-and operational-related technologies such as digital manufacturing, refers to the application of computer systems to the manufacturing products, processes and supply chains (Marinescu et al, 2023). These advanced systems however, can be breached and cause malfunctioning leading to accidents and deaths if not appropriately secured (Kumar et al, 2022).…”

“…Technology-backed manufacturing is on the rise with over 90% of companies worldwide that are using or transitioning to digital manufacturing technology (Fictiv and Dimensional Research, 2022). Internet of Things (IoT), robotics, artificial intelligence (AI), Big data, augmented reality (AR) and Cloud Computing are examples of largely adopted technologies in manufacturing processes (Costantino et al, 2021;Marinescu et al, 2023). The transformation of the manufacturing sector influences and boosts demands in other sectors, prompting businesses and organizations to rapidly invest in digital innovation (Spieske and Birkel, 2021), that is, to invest in the adoption, generation, or recombination of new digital technologies in organizations (see Felicetti et al, 2023;Shukla and Singh, 2023;Troisi et al, 2023).…”