Public attitude and media governance of biometric information dissemination in the era of digital intelligence

Theoretical framework
The theory of Risk Society holds that risk is a social reality in the era of globalization41. Zhang42 believed that in the digital age, this theory applies the idea of risk control to a constructive interpretation of social norms and plays a role in stopping risks before they grow, thereby reducing technological uncertainty and possible undesirable consequences. Based on the Technology Acceptance Model (TAM), Diffusion of Innovations theory (DOI), and Unified Technology Acceptance and Use Theory (UTAUT), Caroline et al. synthesized the variables in the DOI, TAM, and UTAUT models in their work. Additionally, they took specific factors such as perceived risk, trust, privacy concerns, and innovation into account. The study discovered that, aside from innovation, the most crucial drivers explaining the acceptance and recommendation of biometrics stem from trust and privacy protection rather than elements in traditional acceptance models36. However, the current study only focused on one type of biometric system, namely iris scanning, while the inclusion of different types of biometrics might be confusing and may lead to different results. Simultaneously, the sample size and age range are limited, and their study did not include the elderly group, which may drastically impact the results. On this basis, this study incorporated more biometric types into investigation and constructed a new structural equation model (SEM) with an expanded sample size.
In our study, five major factors were included:
(1) Perceived availability.
In the present study, perceived availability is incorporated into our framework as an individual’s subjective assessment of the facility with which they can access and utilize biometric technology services. It often addresses users’ perceptions of the accessibility of technological tools, digital content, or support systems43. It is distinct from actual availability, emphasizing the psychological and situational factors that shape perceptions rather than objective conditions44,45,46.
(2) Perceived trust.
Within the realm of communication, perceived trust is incorporated into our framework as an individual’s subjective conviction or confidence regarding the reliability, integrity, and competence of biometric technology services. In the cognitive dimension, trust is grounded in an evaluation of an entity’s attributes, including trustworthiness, expertise, and predictability. On the emotional level, trust encompasses a sense of security and confidence within a relationship or interaction. Furthermore, perceived trust can vary significantly across different contexts, such as e-commerce47, information technology acceptance48 and Internet relationships49.
(3) Perceived risks.
In the field of communication, perceived risks are included in our framework as an individual’s subjective evaluation of potential negative outcomes or uncertainties associated with biometric technology services52,53,54,55.
(4) Perceived attitudes.
In the current study, the dichotomy of technological optimism/prudence constructed the binary nature of perceived attitudes of biometrics53. Technological optimism is the belief that technology will bring about positive societal change, improve quality of life, and resolve complex global challenges.Individuals with this orientation generally perceive technological advancements as beneficial and view them as key drivers of economic growth, social progress, and innovation46,47,48,49,50,51,52,53,54.While technological prudence is included as a more cautious, skeptical, or risk-averse stance toward technology of people56. Individuals or groups exhibiting technical prudence are concerned about the potential risks and negative consequences of technological advancements, such as privacy violations, job displacement, or environmental harm57. Technical prudence is associated with a critical view of technology, emphasizing the need for regulation, ethical considerations, and the careful evaluation of risks before widespread adoption. A more cautious approach is evident in discussions about AI ethics, data privacy, and the environmental impact of emerging technologies58.
(5) Behavioral intention.
Behavioral intention refers to an individual’s planned or intended behavior, often measured in the context of adopting new technologies or engaging with systems59. In the field of biometric systems, behavioral intention involves users’ willingness to use or interact with biometric authentication methods60,61,62,63,64,65,66 based on their perceived ease of use, trust, and security concerns. It plays a key role in predicting actual usage behavior, such as adopting biometric technologies for security or identification purposes.
The questionnaire design (see Sect. 4.3) in the current study is based on the modification of three essential documents, i.e., the 2020 National Survey of Civic Scientific Literacy in China67, Awareness, Acceptance and Willingness to Buy Genetically Modified Foods in Urban China68, and Provisions on Security Management in the Application of Facial Recognition Technology (Trial) (Draft for Comment)69. This study begins by proposing a series of research questions and hypotheses aimed at understanding the public’s perceptions and attitudes toward biometrics. Specifically, it investigates the relationship of perceived availability (PA), perceived trust (PT), perceived risks (PR), technological optimism (TOp), technological prudence (TP), and behavioral intentions (BI) to biometric information.
Research questions and hypotheses
Based on the framework illustrated in the previous section, we propose four research questions (RQs) for the current study:
RQ1: Does the availability of biometric technologies bring about perceived trust (PT) or perceived risks (PR) in the public?
RQ2: How and to what extent do the public’s perceived trust (PT) and perceived risk (PR) of technology affect the use and popularity of biometrics (BI)?
RQ3: How will the public’s different emotional attitudes towards biometrics (technological optimism, TOp, or technological prudence, TP) affect the behavioral intention (BI) of public?
RQ4: What are the possible measures to be taken to increase public trust (PT) in technology and effectively manage the risks (PR) associated with the dissemination of biometric information?
Accordingly, six research hypotheses (RHs) are raised as follows:
Previous studies have highlighted that familiarity with and ease of access to biometric technologies play a crucial role in enhancing public trust. For instance, Miltgen et al.36 demonstrated that perceived usefulness and ease of use positively correlate with users’ trust in such technologies. As biometrics have become increasingly embedded in everyday activities, their usefulness is widely recognized and self-evident. Consequently, this study employs the variable of perceived availability (PA) to better capture people’s perceptions of biometric technologies.
RH1: The perceived availability (PA) of biometric technologies positively influences perceived trust (PT) in these technologies.
While increased availability fosters trust, it simultaneously raises awareness of potential risks. As Miltgen et al.36 noted, the increased exposure to biometric systems can lead to heightened privacy concerns and perceived risks due to frequent media coverage on data breaches and misuse.
RH2: The perceived availability (PA) of biometric technologies positively impacts perceived risks (PR) associated with their use.
Trust in technology has been identified as a significant driver for its adoption. The trust model highlights that higher levels of trust lead to a stronger willingness to adopt and recommend biometric systems, particularly when users perceive minimal privacy infringement70.
RH3: Perceived trust (PT) in biometric technologies positively affects behavioral intention (BI) to use these technologies.
Perceived risks, especially those related to privacy and data security, are critical deterrents for technology adoption51. Empirical evidence suggests that users are hesitant to adopt biometric technologies when they associate them with potential risks of misuse or unauthorized access52.
RH4: Perceived risks (PR) of biometric technologies negatively affect the behavioral intention (BI) to use these technologies.
Technological optimism is often linked to high levels of trust in technological solutions and a willingness to embrace new technologies, particularly in domains such as healthcare, education, and sustainability55. Optimistic attitudes towards technology can mitigate concerns over risks and enhance behavioral intentions. Miltgen et al.36 identified optimism as a mediator that reduces the psychological barriers associated with adopting disruptive innovations like biometrics.
RH5: Technological optimism (TOp) positively influence the behavioral intention (BI) to use biometric technologies.
While prudence can protect users from potential risks, excessive caution may limit their willingness to engage with emerging technologies. According to Miltgen et al.36, prudent users are less likely to adopt biometric systems due to amplified concerns over data protection.
RH6: Technical prudence (TP) negatively affect the behavioral intention (BI) to use biometric technologies.
Questionnaire design and data collection
The questionnaire used in the current study is listed as Table 1. The significance of this questionnaire lies in its role in developing a comprehensive scale to examine the public’s perception, trust, risk awareness, emotional attitudes toward the technology, and behavioral intentions regarding the dissemination of biometric information. This study aims to identify user-related factors and, building on existing theories, propose enhanced strategies to effectively manage the risks associated with biometric information dissemination.
The questionnaire was designed and distributed via the online survey platform Wenjuanxing (www.wjx.cn). The platform was chosen for its widespread usage and robust data management features, which facilitated efficient distribution and collection. The survey included questions assessing participants’ perceptions, trust, risk awareness, emotional attitudes, and behavioral intentions regarding biometric information dissemination. A financial incentive of 5 CNY was offered to each participant upon successful completion of the survey, significantly enhancing the response rate.
This study adhered strictly to the ethical guidelines outlined in the Declaration of Helsinki and was approved by the Science and Ethics Committee at University of Chinese Academy of Sciences (UCAS). All procedures complied with relevant regulations, and informed consent was obtained from all participants before the survey. To ensure privacy, personal identities were anonymized during data collection and throughout the data analysis process.
Participants were recruited through multiple online channels, including social media platforms (Xiaohongshu and Weibo), community groups (WeChat groups), and email lists. This ensured a diverse demographic representation. To maximize participation, the survey link was accompanied by a clear introduction outlining the research purpose, confidentiality assurances, and details about the monetary reward.
A total of 2,000 questionnaires were distributed. Responses were monitored in real-time to track progress and detect anomalies. By the end of the data collection period, 1,913 responses were received, yielding a response rate of approximately 96%.
Upon completion of the data collection, the responses underwent a rigorous three-step screening process to ensure data quality: Firstly, incomplete questionnaires were automatically flagged and excluded; secondly, responses completed in an unreasonably short time were considered invalid, as they likely did not reflect genuine engagement; thirdly, surveys exhibiting clear response patterns (e.g., selecting the same option for all questions) were discarded.
In the end, this screening process resulted in 1,862 valid responses, with a validity rate of about 97%.
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