Collection 

Digital design and cognitive decision-making in the context of technological innovation: focus on social equality

Social equality is one of the most important talking points in global social science research. The global outbreak of COVID-19 caused major societal changes. All aspects of life, including work, study and other services, are irreversibly moving towards digitization and informatization, and have become a new economic growth point and a hot spot for livelihood development. However, differences in access to resources, opportunities and outcomes in society are exacerbated by persistent inequalities in income, geography, gender, ethnicity, disability, class and religion, both within and between countries. The gap is particularly prominent in relation to digital resources related to life, education and medical care. Balancing social equity and technological innovation under different factors is the key to social harmony and sustainable development. Furthermore, the promotion of social equality is an important determinant of technological innovation.

Although domestic and foreign researchers have conducted many discussions on issues related to digital technology and social equality, there remain numerous problems that need to be resolved urgently. These include: the fact that digital design and cognitive decision-making to address social equality issues is not yet systematic; the lack of research on cognitive decision-making methods and digital design of different factors that affect social inequality; and the lack of scientific and standardised methods for research on phenomena affecting social inequality. Finally, against the background of digital technology transformation, there is insufficient research on how to balance social inequality.

This Collection, therefore, welcomes a wide range of perspectives, including interdisciplinary methods, focusing on social equality. The focus is to explore research on theoretical methods, standards, policies and regulations, practices and applications related to the process of promoting social equality from a diverse perspective, including but not limited to survey analysis, cognitive decision-making, evaluation decision-making, digital technology innovation design, etc. Additionally, perspectives may include, but are not limited to, one or more, of the following topics:

  • Disabled needs and digital design
  • Digital product design and decision-making related to the learning, life and medical care of the disabled
  • Decision-making cognition for the treatment or management of mental health issues
  • Digital art design and awareness of mood disorders in the elderly
  • Mental health issues among socially anxious users and digital therapeutic healing product design strategy
  • Digital education and educational equity for special needs students
  • Learning environment development for special needs students in the context of digital education
  • Decision-making cognition and student discrimination/bias issues in the context of digital education
  • Adaptability of emerging digital education in poor areas Interlingual and intercultural communication for special needs students in the context of digital education
  • Criminal psychology and cognitive intervention decision-making in particular contexts
  • Family and school scenarios (e.g., bullying)
  • Juvenile delinquency and left-behind children
  • Legal cognition and policy intervention for special needs groups
  • Digital design and cognitive decision-making in religious groups
  • Digital design and gender equality Assistive technology (at) Intelligent health management Metaverse intelligent life Intelligent monitoring assistance
  • Caring for the disadvantaged
  • Product and service design
  • Public health and social equity
  • Cognitive ability and active health
  • Active ageing
  • Social inclusion
  • Active activities

This Collection supports and amplifies research related to SDG 9 and SDG 10.

Human head with a luminous brain network. Digital brain, Analysis information, Cyber mind, Deep and Machine learning, Consciousness, Artificial intelligence, Technology background concept.

Editors

  • Zhe Li  &

    Zhe Li

    Osaka University, Japan

  • Shih-Wen Hsiao

    National Cheng Kung University, Taiwan

Articles