Journal of Beijing University of Posts and Telecommunications(Social Sciences Edition) ›› 2024, Vol. 26 ›› Issue (3): 11-22.doi: 10.19722/j.cnki.1008-7729.2024.0030

Previous Articles     Next Articles

Digital Identity Recognition: Conflicts of Law, Ethics and Technology in Future Human-machine Interaction

  

  1. School of Law(Weihai), Shandong University, Weihai 264209, China
  • Received:2024-03-05 Online:2024-06-30 Published:2024-06-30

Abstract: Digital identity no longer solely pertains to the question of “Who am I”, but rather involves the question of “Who am I perceived to be”. The convergence of digital and virtual identities makes individual identities more fluid, but it also triggers conflicts between identities in the virtual and real worlds. Identity authentication plays a crucial role in human-computer interaction, where the potential bias of machine learning and inequality of digital identity demand more attention. With the rise of the digital economy, identity data is becoming a new symbol of power, embroiling individuals, governments, and corporations in power struggle. The legal field, facing the challenges of digital identity, must keep pace with rapid development of technology while also balance the conflict between identity authentication and privacy rights. Digital identity recognition also touches on issues of digital ethics, so people should reevaluate the relationship between technology and identity, clarify whether the purpose of technology is to serve humanity or replace it, and how to redefine “human” in human-computer interaction. Advancing towards a more human-centered digital identity requires the collaborative progress of technology, law, and ethics, as well as in-depth cooperation and research across various disciplines. In facing unknown challenges, there is a need to expand from the individual question of “Who am I” to the collective question of “Who are we” to foster a positive outlook on the future relationship among technology, identity and humanity.

Key words: digital identity recognition, algorithmic bias, digital ethics, digital divide, human-machine interaction 

CLC Number: