Sung-Yueh Perng, Associate Professor (Institute of Science, Technology and Society)

Algorithmic decarbonisation refers to the global, emerging trend of leaning on digital innovation, specifically those powered by artificial intelligence (AI) and other high computing capabilities, to know, plan and facilitate carbon reduction measures. While government strategies and science and engineering research that feature ‘computing for net zero’ (The Royal Society, 2020), there is a clear need for social sciences research to (1) produce a deeper understanding of the growing tendency of algorithmic decarbonisation and (2) unpick techno-solutionist approaches that can produce negative consequences at both local and global scales. As Crawford (2021) demonstrates, data and digital technologies can be harmful, have unintended consequences or maintain and amplify structural inequalities. Further, the process of digitalisation itself is highly extractive and resource intensive, relying heavily on rare earth minerals, and requiring significant energy to run associated technologies and cloud computing infrastructures. The purpose of this research project is to further examine algorithmic decarbonisation by (1) introducing the concept of ‘liveliness’, in Mackenzie’s (2017) sense, to continue and refine the empirical research; (2) examining how social, political and ethical considerations are complicated as the trend of algorithmic decarbonisation deepens and multiplies; and (3) inviting Professor Adrian Mackenzie, a world-renowned philosopher and social scientist on machine learning, algorithms and AI, for a research and exchange visit to contribute to the development of the project and engage with the wider research communities interested in the social and ethical impacts of algorithms and AI.

Sharon Tsai-Hsuan Ku, Assistant Professor (Institute of Science, Technology and Society)

The shortage of chip talent has become the most pressing challenge in the global semiconductor industry today. However, what exactly is “chip talent”? What knowledge, skills, labor, and even cultural traits should a chip engineer possess to be considered as a qualified workforce? This project contextualizes chip engineering education and workforce training in the global chip supply chain, exploring the following research questions:

• What social narratives, metaphors and sociotechnical imaginaries of semiconductor and microchip industry are mobilized and embedded in engineering education policy and practice in Taiwan and the US?
• What historical, political, cultural, ideological, and diplomatic conditions have shaped the cultivation and global mobility of chip talent in Taiwan and the US?
• How do these factors impact chip engineering education, professional identity formation, and engineering culture in Taiwan and the US?

This project contains two research and one teaching components, summarized as follows:

1. Lab ethnography and historiography: Through collaborating with Professor Wu Chong-yu, the former president of National Yang Ming Chiao Tung University and a pioneer in Taiwan’s chip design research, we trace the history and educational practice of 307 Chip Design Laboratory, the cradle of Taiwan’s chip design talent he established in 1978, to examine the history of chip design development in Taiwan, the corresponding university-industry networks and the engineering workforce training from then to now.
2. Chip education curriculum comparison: We selected four universities that offer Chip talent training programs—National Yang Ming Chiao Tung University, National Taiwan University, Virginia Tech. and Purdue University—and compare their curriculum design and student enrollment channels. This analysis aims to explore the similarities and differences in chip talent development and related educational policies between Taiwan and the U.S., in order to understand the political, economic, cultural, and ideological factors behind the cultivation of chip workforce in global supply chain.
3. NYCU-VT Engineering Humanities Global Classroom: By collaborating with engineering educators from Virginia Tech in the U.S., we create a Global Classroom to integrate social issues regarding the development and deployment of global supply chain into the curriculum. This enables students from both sides to collectively explore supply chain practice from cross-cultural perspectives. Students’ learning outcomes are analyzed to understand the differences and similarities between the US and Taiwanese students in terms of their views on chip engineering professionalism, ethics, and work cultures.

Mei-Ling Chien, Professor(Department of Humanities and Social Sciences)

The townships of Baoshan, Emei, and Beipu in Hsinchu County were historically part of the same pioneering settlement area. Due to their similar geographical, economic, and social development trajectories, they were collectively referred to as the “Three Townships of Daxi.”

This research project focuses on Emei Township, exploring the work, daily lives, and community practices of Hakka women from different generations and backgrounds. The study includes interviews with five Hakka women and one man, each with unique life experiences that brought them to Emei. Some interviewees were born there, others moved after marriage, and some returned to their hometown after retirement. Their birth years range from the mid-1950s to the early 2000s, spanning an age range from their 20s to their 70s. This wide generational scope highlights diverse life experiences and narratives.

Through oral history interviews, this research aims to examine how the rapid development of Hsinchu Science Park since the 1980s has shaped the surrounding Hakka communities, the individual responses to these changes, and the social resilience displayed in the transformation of their hometowns. Interviewees from various occupational backgrounds provide diverse perspectives on the development of the science park, while also sharing their personal memories and experiences in Emei.

These life narratives reveal valuable insights into how Hakka women navigate personal, familial, and communal transformations, seeking self-identity development. Ultimately, the study illustrates the resilience of the local Hakka community.

Chen-Chao Tao, Professor(Institute of Communication Studies)

The selection of “brain rot” as Oxford Word of the Year 2024 reflects contemporary society’s concerns about cognitive decline potentially caused by excessive digital media use. In an era dominated by short-form video platforms, led by TikTok and its competitors such as Instagram Reels and YouTube Shorts, machine learning algorithms create personalized recommendation systems that generate highly engaging user experiences. However, as AI systems continuously optimize user engagement and time spent on media platforms, does this algorithm-driven information acquisition truly promote meaningful cognitive interaction? Based on Human-Centered design principles, this research examines two core features of short-form video platforms: Algorithm-driven content and Scrollability, investigating their impacts on users’ attention allocation, emotional arousal, and memory formation. Departing from previous research approaches that emphasized Uses and Gratifications Theory or Flow Theory, this study focuses on users’ cognitive processing in an AI algorithm-dominated digital environment, particularly examining the paradoxical state where high immersion coexists with “absent-minded scrolling,” and its effects on actual memory retention and content comprehension. The findings will contribute to rethinking human-computer interaction design in the AI era, providing empirical evidence for developing digital environments more conducive to human cognitive development.

Wei-Ping Chen, Assistant Professor (Institute of Communication Studies)

This research investigates the impact of algorithms on users and their broader sociocultural implications, with particular focus on how social media users interpret and respond to algorithmic recommendation systems, and how these mechanisms shape digital experiences and social relationships. The study employs a qualitative methodology combining in-depth interviews and digital ethnography, targeting users born between 1981-2006 with extensive social media experience.

By examining mainstream platforms including Facebook, Instagram, TikTok, YouTube, and Netflix, the research analyzes how users comprehend and interact with algorithmic mechanisms across different digital environments. The research objectives are threefold: 1) examining users’ perceived relationships with algorithms, 2) analyzing algorithmic influence on social behaviors and interpersonal interactions, and 3) investigating algorithms’ impact on emotional connections and identity construction. Through systematic examination of these dimensions, the study will illuminate how algorithms shape contemporary digital culture while considering the critical balance between technological advancement and humanistic values. The findings aim to inform recommendations for algorithmic governance and user rights protection. By adopting a user-centric perspective, this research explores how algorithms fundamentally influence digital life practices. The insights gained will contribute to both theoretical understanding and practical policymaking regarding platform governance. Importantly, the study bridges the gap between technological progress and human-centered design by examining the intricate relationships between users, algorithms, and digital platforms. The research will advance our understanding of algorithmic influence in modern digital society while providing actionable insights for developing more equitable and user-oriented digital environments.

Chih-Hsiung Chen, Professor(Institute of Technology Law)

Generative AI, from development to application, requires extensive amounts of data. The process—from data collection during development to data processing during application—inevitably raises conflicts between privacy protection and the encouragement of innovation, exposing the inadequacies of existing data governance frameworks. In collaboration with Professor Christoph Sorge from Saarland University in Germany, our team has conducted a cross-national study focusing on the use of sensitive biomedical data in generative AI applications. This research serves as a pilot study to address the regulatory gaps or conflicts in data utilization within the biomedical field.

This study represents Taiwan’s first legal analysis of generative AI use in medical institutions, covering the stages from training to application. Utilizing methods such as international conferences, cross-border exchanges, and literature analysis, the study concludes that generative AI algorithms themselves do not fall under the jurisdiction of personal data protection laws. However, during the training and application output stages, considerations of personal data law are necessary. These considerations include the legality of data sources for training, contractual supervision of external AI companies during the training process, and feedback mechanisms for correcting training outcomes.

Since many generative AI applications in hospitals do not qualify as medical devices, they lack oversight mechanisms from regulatory bodies. Therefore, the study recommends that the government establish quality assurance mechanisms by referencing international precedents. Among the three types of AI centers announced by Taiwan in the second half of this year, the “Responsible AI Center” is expected to serve as the foundation for AI governance frameworks within hospitals.

Chien-Chung Lin, Professor(Institute of Technology Law)

In recent years, due to the heightened conflicts in U.S.-China relations, technology export control has become focus of competition, alongside with the conflicts in the sea (including the long-term offshore conflict between China and the Philippines) and airspace (reconnaissance balloons and low-altitude satellites). In terms of geopolitics and industrial structure, Taiwan is not immune to the impact of rising related conflicts. What may be affected includes the cutting-edge semiconductor industry, and inevitably will expand to the artificial intelligence (AI) industry in the future.

Regarding export controls, this project surveys the status of Taiwan’s relevant regulations and the direction of U.S. regulations. This project also explores the relevant implementation, and examines the anticipated goals and its cost-effectiveness calculations. Overall, the purpose of this project is to address the risks of high-tech industries in international conflicts, echoing the pilot project’s overarching themes of “Legal governance of new technology” and “Risks of high-tech industries in international conflicts.” (Risks of high-tech industries in international conflicts).” The contents include: 1. Current export control toolkits; 2. Assessment of the status of export control and implementation; 3. The criticism from the technology industry and impact assessment.

Hsin-Ning Su, Professor(Institute of Management of Technology)

This research project focuses on examining how gender differences influence the integration of technologies and innovation processes within high-tech industries, particularly the semiconductor sector. In an era where globalization and technological advancements are increasingly interconnected with sociocultural dynamics, gender, as a key aspect of social structure, significantly shapes technological innovation. Despite its importance, current scholarly attention to this issue remains limited. By leveraging data from the United States Patent and Trademark Office (USPTO), this study systematically analyzes the innovation behaviors of male and female inventors in the semiconductor field, aiming to uncover how gender differences contribute to technological progress and industrial evolution. The research assesses the impact of gender diversity in teams on the efficiency of technological integration and innovation, while also exploring how gender diversity facilitates interdisciplinary technological collaboration. This work aims to bridge theoretical gaps in innovation management, technological development, and interdisciplinary integration while offering empirical insights to support gender equality in high-tech sectors. Ultimately, it seeks to enhance understanding of the interplay among gender, technological progress, and societal transformation, providing valuable theoretical and practical guidance for industry and policy development.

Sirirat Sae Lim, Associate Professor(Institute of Management of Technology)

As international collaboration becomes increasingly complex,  semiconductor companies face challenges such as technological restrictions, unequal resource distribution, and high market dependence, threatening the stability and resilience of their supply chains. While existing research has explored the impact of geopolitical tensions on global supply chains, studies focusing on Taiwan’s semiconductor industry remain lacking. This study constructs a theoretical framework based on six dimensions: political, economic, social, technological, legal, and environmental. This study used in-depth interviews with eight experts in the semiconductor industry, identified key risk sources and highlighted geopolitical tensions and technological restrictions as factors contributing to supply chain vulnerabilities. This study proposes resilience-based strategies to mitigate these risks. First, employing engineering resilience. It recommends establishing contingency plans to minimize supply chain disruption durations and, second, leveraging ecological resilience. It suggests implementing supplier diversification strategies to reduce reliance on single markets and, third, enhance social resilience. It emphasizes fostering upstream and downstream collaboration and data sharing to improve overall risk management capabilities. Furthermore, the study advocates for accelerating technological self-reliance through research and development, expanding cooperation with emerging markets, and calls on the government to support the formation of industry alliances and the development of emergency policies. This research offers strategic supply chain management recommendations to bolster Taiwan’s semiconductor companies’ risk resilience, enhance their competitive advantages, and strengthen Taiwan’s leading position in the global semiconductor market.

Shih-Hsin Chen, Associate Professor(Institute of Management of Technology)

This study investigates the development and challenges of the AI-driven healthcare ecosystem, proposing governance models and policy recommendations from a human-centered inclusive innovation perspective. The project outcomes include the publication of one journal article, 13 international conference papers, one book chapter, and one policy brief, alongside collaborations with six leading international academic institutions, resulting in two joint international research proposals. Employing a multi-level perspective and an innovation cycle framework, Taiwan’s smart healthcare ecosystem is examined as a dynamic system that includes technological innovation, product development, and application promotion. The findings reveal Taiwan’s potential in integrating AI-driven diagnostic technologies, wearable devices, and telemedicine platforms, though challenges remain in ensuring accessibility for rural and underserved populations. Inclusive policy frameworks are important to fostering equitable healthcare resource distribution. While some enterprises have adopted sustainable service models that integrate innovation with social responsibility, the study highlights the need for robust institutional designs and implementation mechanisms, such as enhanced privacy protection, strengthened data governance capabilities, and collaborative governance environments between the public and private sectors. Policy tools and cross-sector coordination are recommended to advance the sustainable development of smart healthcare ecosystems, bridging the digital divide and promoting fairness in healthcare access while realizing human-centered values.

Chi-Wen Chen, Professor(Department of Nursing)

Children with rare diseases and their parents often face significant anxiety due to the challenges of treatment and daily life, leading to strained parent-child relationships. This study aimed to evaluate the feasibility and acceptability of social robot interventions for children with rare diseases and their parents, as well as their impact on parent-child relationships, stress, and anxiety. A single-group pretest-posttest design was conducted, recruiting seven pairs of children aged 8–19 with rare diseases and their parents from a medical center in northern Taiwan. The intervention involved parent-child interactions with the social robot PARO in four 30-minute sessions held biweekly. Feasibility, acceptability, parent-child relationships, stress, and anxiety were assessed in immediate post-intervention, and qualitative interviews explored their experiences with PARO. Quantitative results indicated a 100% retention and participation rate, with parents experiencing a significant reduction in anxiety post-intervention. Qualitative results revealed that the effectiveness of interactions with PARO was influenced by parent-child roles and their level of closeness. However, the stress-relief effects and novelty of PARO diminished with repeated use. Participants generally expressed a desire for PARO to exhibit more responsive behaviors and emotional expressions to enhance its therapeutic appeal. In conclusion, this study provides preliminary evidence supporting the feasibility and effectiveness of social robot interventions. Future research will involve a larger sample size to further validate the utility of PARO and offer insights for academic research and clinical applications.