The influence of media use on public perceptions of artificial intelligence in China: Evidence from an online survey

2019 ◽  
pp. 026666691989341
Author(s):  
Di Cui ◽  
Fang Wu
Keyword(s):  
Artificial Intelligence ◽  
Risk Perception ◽  
Pilot Study ◽  
Online Survey ◽  
Media Use ◽  
Public Perceptions ◽  
Policy Support ◽  
Personal Relevance ◽  
Negatively Associated ◽  
Benefit Perception

With support from government and business, artificial intelligence is growing quickly in China. However, little is known of how media use shapes the Chinese public’s perception of artificial intelligence. Based on a national online survey (N = 738), this pilot study explored the linkages between media use and people’s risk perception, benefit perception, and policy support of artificial intelligence. Results showed that respondents perceive artificial intelligence as more beneficial than risky. Newspaper use was negatively associated with benefit perception and policy support, whereas television and WeChat use positively predicted both. Analyses of interaction effects showed that personal relevance could partly mitigate the influence of media use.

scholarly journals The Role of Discrete Emotions in Risk Perception and Policy Support during Public Health Crises: The Moderation Effect of SNS Dependency

2021 ◽  
Vol 18 (21) ◽  
pp. 11654
Author(s):  
Soohee Kim
Keyword(s):  
Public Health ◽  
Risk Perception ◽  
Online Survey ◽  
Positive Impact ◽  
Public Perceptions ◽  
Policy Support ◽  
Network Services ◽  
Moderation Effect ◽  
The Impact

People often experience strong emotions during public health crises. This study examines how these emotions shape the perception of risk and support for policies to address the risk. In particular, this study explores the moderating effects of social network services (SNS) use in the process, considering that SNS have become a prominent communication platform during crises. Using a nationwide online survey conducted on the issue of fine dust air pollution in South Korea, this study found that feelings of anxiety, anger, and sadness about the risk issue were positively related to risk perception and policy support, while the relative effects of these emotions varied. Furthermore, the results demonstrated that reliance on SNS for learning (i.e., SNS learning dependency) moderated the influence of anxiety: the positive impact of anxiety was greater among those who used SNS for learning, while no such effects were found among those who used SNS for play or entertainment (i.e., SNS entertainment dependency). The implications of this study are discussed in terms of the distinct role emotions play in public responses to risks and the importance of considering the impact of SNS on public perceptions and judgments in this era of social media.

Living with Autonomy: Public Perceptions of an AI-Mediated Future

2021 ◽  
pp. 0739456X2098452
Author(s):  
Eva Kassens-Noor ◽  
Mark Wilson ◽  
Zeenat Kotval-Karamchandani ◽  
Meng Cai ◽  
Travis Decaminada
Keyword(s):  
Artificial Intelligence ◽  
Autonomous Vehicles ◽  
Intelligent Systems ◽  
Research University ◽  
Online Survey ◽  
New Technology ◽  
Autonomous Systems ◽  
Public Perceptions ◽  
Major Research ◽  
The People

The arrival of autonomous systems powered by artificial intelligence (AI) offers new possibilities for life, yet the focus tends to be more on the technology than the people it serves. Planners should consider the likely reception awaiting emerging intelligent systems. Using an online survey of 3,249 faculty, staff, and students at a major research university, we tested perceptions of autonomy, including domotics and autonomous vehicles. Embracing the new technology with variations in attitude associated with age, gender, and familiarity with new technology, people’s openness to AI-enabled devices applies if they remain a tool to support work and not replace human-centered interactions.

scholarly journals Changes in Sex Life among People in Taiwan during the COVID-19 Pandemic: The Roles of Risk Perception, General Anxiety, and Demographic Characteristics

2020 ◽  
Vol 17 (16) ◽  
pp. 5822 ◽  
Author(s):  
Nai-Ying Ko ◽  
Wei-Hsin Lu ◽  
Yi-Lung Chen ◽  
Dian-Jeng Li ◽  
Yu-Ping Chang ◽  
...  
Keyword(s):  
Risk Perception ◽  
Sexual Activity ◽  
Health Care Providers ◽  
Online Survey ◽  
Survey Study ◽  
Care Providers ◽  
Factors Affecting ◽  
Negatively Associated ◽  
General Anxiety ◽  
Activity Frequency

This study used data collected from an online survey study on coronavirus disease 2019 (COVID-19) in Taiwan to examine changes in sex life during the pandemic and the factors affecting such changes. In total, 1954 respondents were recruited from a Facebook advertisement. The survey inquired changes in sex life during the pandemic, including satisfaction with the individual’s sex life, frequency of sexual activity, frequency of sex-seeking activity, and frequency of using protection for sex. The associations of change in sex life with risk perception of COVID-19, general anxiety, gender, age, and sexual orientation were also examined. For each aspect of their sex life, 1.4%–13.5% of respondents reported a decrease in frequency or satisfaction, and 1.6%–2.9% reported an increase in frequency or satisfaction. Risk perception of COVID-19 was significantly and negatively associated with frequencies of sexual and sex-seeking activities. Higher general anxiety was significantly and negatively associated with satisfaction of sex life and frequencies of sexual and sex-seeking activities. Sexual minority respondents were more likely to report decreased satisfaction with sex life and frequencies of sexual activity and sex-seeking activities during COVID-19. Health care providers should consider these factors when developing strategies for sexual wellness amid respiratory infection epidemics.

Attitudes of Medical Workers Toward Artificial Intelligence in Ophthalmology: A Comparative Survey (Preprint)

2020 ◽  
Author(s):  
Weihua Yang ◽  
Bo Zheng ◽  
Maonian Wu ◽  
Shaojun Zhu ◽  
Hongxia Zhou ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Medical Ethics ◽  
Online Survey ◽  
Medical Professionals ◽  
Medical Field ◽  
Acceptance Level ◽  
Professional Workers ◽  
Basic Understanding ◽  
Comparative Survey ◽  
Definition Of

BACKGROUND Artificial intelligence (AI) is widely applied in the medical field, especially in ophthalmology. In the development of ophthalmic artificial intelligence, some problems worthy of attention have gradually emerged, among which the ophthalmic AI-related recognition issues are particularly prominent. That is to say, currently, there is a lack of research into people's familiarity with and their attitudes toward ophthalmic AI. OBJECTIVE This survey aims to assess medical workers’ and other professional technicians’ familiarity with AI, as well as their attitudes toward and concerns of ophthalmic AI. METHODS An electronic questionnaire was designed through the Questionnaire Star APP, an online survey software and questionnaire tool, and was sent to relevant professional workers through Wechat, China’s version of Facebook or WhatsApp. The participation was based on a voluntary and anonymous principle. The questionnaire mainly consisted of four parts, namely the participant’s background, the participant's basic understanding of AI, the participant's attitude toward AI, and the participant's concerns about AI. A total of 562 participants were counted, with 562 valid questionnaires returned. The results of the questionnaires are displayed in an Excel 2003 form. RESULTS A total of 562 professional workers completed the questionnaire, of whom 291 were medical workers and 271 were other professional technicians. About 37.9% of the participants understood AI, and 31.67% understood ophthalmic AI. The percentages of people who understood ophthalmic AI among medical workers and other professional technicians were about 42.61% and 15.6%, respectively. About 66.01% of the participants thought that ophthalmic AI would partly replace doctors, with about 59.07% still having a relatively high acceptance level of ophthalmic AI. Meanwhile, among those with ophthalmic AI application experiences (30.6%), respectively about 84.25% of medical professionals and 73.33% of other professional technicians held a full acceptance attitude toward ophthalmic AI. The participants expressed concerns that ophthalmic AI might bring about issues such as the unclear definition of medical responsibilities, the difficulty of ensuring service quality, and the medical ethics risks. And among the medical workers and other professional technicians who understood ophthalmic AI, 98.39%, and 95.24%, respectively, said that there was a need to increase the study of medical ethics issues in the ophthalmic AI field. CONCLUSIONS Analysis of the questionnaire results shows that the medical workers have a higher understanding level of ophthalmic AI than other professional technicians, making it necessary to popularize ophthalmic AI education among other professional technicians. Most of the participants did not have any experience in ophthalmic AI, but generally had a relatively high acceptance level of ophthalmic AI, believing that doctors would partly be replaced by it and that there was a need to strengthen research into medical ethics issues of the field.

Living machines in our cultural imagination

2018 ◽  
Author(s):  
Michael Szollosy
Keyword(s):  
Artificial Intelligence ◽  
Science Fiction ◽  
Public Perceptions ◽  
Human Condition ◽  
Cultural Imagination ◽  
The Public ◽  
The Enlightenment ◽  
The Future ◽  
Public Imagination ◽  
The Human Condition

Public perceptions of robots and artificial intelligence (AI)—both positive and negative—are hopelessly misinformed, based far too much on science fiction rather than science fact. However, these fictions can be instructive, and reveal to us important anxieties that exist in the public imagination, both towards robots and AI and about the human condition more generally. These anxieties are based on little-understood processes (such as anthropomorphization and projection), but cannot be dismissed merely as inaccuracies in need of correction. Our demonization of robots and AI illustrate two-hundred-year-old fears about the consequences of the Enlightenment and industrialization. Idealistic hopes projected onto robots and AI, in contrast, reveal other anxieties, about our mortality—and the transhumanist desire to transcend the limitations of our physical bodies—and about the future of our species. This chapter reviews these issues and considers some of their broader implications for our future lives with living machines.

scholarly journals The effect of risk communication on preventive and protective Behaviours during the COVID-19 outbreak: mediating role of risk perception

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Seyed Taghi Heydari ◽  
Leila Zarei ◽  
Ahmad Kalateh Sadati ◽  
Najmeh Moradi ◽  
Maryam Akbari ◽  
...  
Keyword(s):  
Risk Perception ◽  
Risk Communication ◽  
Structural Equation ◽  
Online Survey ◽  
Equation Modeling ◽  
Mediating Role ◽  
Positive Effects ◽  
Global Pandemic ◽  
And Control ◽  
New Evidence

Abstract Background The COVID-19 outbreak is a global pandemic, during which the community preventive and protective behaviors play a crucial role in the containment and control of infection. This study was designed to contribute to the existing knowledge on how risk communication (RC) and risk perception (RP) affect protective and preventive behaviors (PPB) during the COVID-19 outbreak. Methods The required data were extracted from a national online survey of Iranian adults aged 15 and older during March 15–19, 2020 (n=3213). Data analysis was performed using structural equation modeling. Results The study findings reveal that RC has direct and indirect positive effects on PB. Furthermore, this study also provides new evidence indicating that RP mediates the relationship between RC and PB and there is a two-way relationship between RC and RP. These interactions may have impact on risk communication strategies which should be adopted during this pandemic. Conclusion The study findings have remarkable implications for informing future communications as well as interventions during this ongoing outbreak and subsequent national risk events.

scholarly journals The Interplay of Online Network Homogeneity, Populist Attitudes, and Conspiratorial Beliefs: Empirical Evidence From a Survey on German Facebook Users

2020 ◽  
Author(s):  
Manuel Cargnino
Keyword(s):  
Social Networking ◽  
Empirical Evidence ◽  
Social Networking Sites ◽  
Online Survey ◽  
Process Information ◽  
Negatively Associated

Abstract Social networking sites are suspected to impede the communication between members of different political camps and thereby increase network homogeneity. This homogeneity can be a result of humans’ tendency to process information in confirmatory ways—a characteristic which is also ascribed to populist citizens and those who hold conspiratorial beliefs. It is hypothesized that populist views and conspiratorial beliefs are associated with higher exposure to like-minded information within Facebook. An online survey with German Facebook users (N = 469) revealed that populist attitudes are positively associated with conspiratorial beliefs but negatively associated with homogeneity. Conspiratorial beliefs are unrelated to homogeneity. Findings are discussed in the light of extant research.

Endoscopic prediction of submucosal invasion in Barrett’s cancer with the use of Artificial Intelligence: A pilot Study

Endoscopy ◽  
2020 ◽  
Author(s):  
Alanna Ebigbo ◽  
Robert Mendel ◽  
Tobias Rückert ◽  
Laurin Schuster ◽  
Andreas Probst ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Deep Learning ◽  
Pilot Study ◽  
White Light ◽  
Submucosal Invasion ◽  
Learning System ◽  
Endoscopic Images ◽  
Barrett’S Cancer ◽  
Significant Difference ◽  
Sensitivity Specificity

Background and aims: The accurate differentiation between T1a and T1b Barrett’s cancer has both therapeutic and prognostic implications but is challenging even for experienced physicians. We trained an Artificial Intelligence (AI) system on the basis of deep artificial neural networks (deep learning) to differentiate between T1a and T1b Barrett’s cancer white-light images. Methods: Endoscopic images from three tertiary care centres in Germany were collected retrospectively. A deep learning system was trained and tested using the principles of cross-validation. A total of 230 white-light endoscopic images (108 T1a and 122 T1b) was evaluated with the AI-system. For comparison, the images were also classified by experts specialized in endoscopic diagnosis and treatment of Barrett’s cancer. Results: The sensitivity, specificity, F1 and accuracy of the AI-system in the differentiation between T1a and T1b cancer lesions was 0.77, 0.64, 0.73 and 0.71, respectively. There was no statistically significant difference between the performance of the AI-system and that of human experts with sensitivity, specificity, F1 and accuracy of 0.63, 0.78, 0.67 and 0.70 respectively. Conclusion: This pilot study demonstrates the first multicenter application of an AI-based system in the prediction of submucosal invasion in endoscopic images of Barrett’s cancer. AI scored equal to international experts in the field, but more work is necessary to improve the system and apply it to video sequences and in a real-life setting. Nevertheless, the correct prediction of submucosal invasion in Barret´s cancer remains challenging for both experts and AI.

scholarly journals Diabetes knowledge, risk perception, and quality of life among South Asian caregivers in young adulthood

2020 ◽  
Vol 8 (2) ◽  
pp. e001268
Author(s):  
Angela Koipuram ◽  
Sandra Carroll ◽  
Zubin Punthakee ◽  
Diana Sherifali
Keyword(s):  
Quality Of Life ◽  
Risk Perception ◽  
South Asian ◽  
Online Survey ◽  
Educational Interventions ◽  
Cross Sectional Study ◽  
Cross Sectional ◽  
Significant Difference ◽  
Design And Methods

IntroductionPersons of South Asian descent have a higher prevalence of type 2 diabetes mellitus (T2DM). The management of T2DM in the South Asian community has required the support of adult children, potentially impacting the quality of life, diabetes-related knowledge, and risk perception among these caregivers.Research design and methodsTo investigate diabetes-related knowledge, quality of life, risk perception, and actual risk of developing diabetes among South Asian young adults whose parents are living with T2DM. A cross-sectional study was conducted (n=150). An online survey was administered. Data were analyzed with descriptive and inferential statistics.ResultsThere was a statistically significant difference in diabetes-related knowledge between males and females (p<0.001). Males (in comparison to females) had a lower risk perception of developing diabetes (p=0.06). Further, risk perception and diabetes-related knowledge were positively associated with caregiver’s physical health (p=0.002).ConclusionFindings highlight the importance of providing gender-specific and culturally tailored diabetes educational interventions.

scholarly journals A survey of clinicians on the use of artificial intelligence in ophthalmology, dermatology, radiology and radiation oncology

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jane Scheetz ◽  
Philip Rothschild ◽  
Myra McGuinness ◽  
Xavier Hadoux ◽  
H. Peter Soyer ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
New Zealand ◽  
Radiation Oncology ◽  
Online Survey ◽  
New Technology ◽  
Medical Liability ◽  
Healthcare Outcomes ◽  
Medical Workforce ◽  
Artificial Intelligence Technology ◽  
Workforce Needs

AbstractArtificial intelligence technology has advanced rapidly in recent years and has the potential to improve healthcare outcomes. However, technology uptake will be largely driven by clinicians, and there is a paucity of data regarding the attitude that clinicians have to this new technology. In June–August 2019 we conducted an online survey of fellows and trainees of three specialty colleges (ophthalmology, radiology/radiation oncology, dermatology) in Australia and New Zealand on artificial intelligence. There were 632 complete responses (n = 305, 230, and 97, respectively), equating to a response rate of 20.4%, 5.1%, and 13.2% for the above colleges, respectively. The majority (n = 449, 71.0%) believed artificial intelligence would improve their field of medicine, and that medical workforce needs would be impacted by the technology within the next decade (n = 542, 85.8%). Improved disease screening and streamlining of monotonous tasks were identified as key benefits of artificial intelligence. The divestment of healthcare to technology companies and medical liability implications were the greatest concerns. Education was identified as a priority to prepare clinicians for the implementation of artificial intelligence in healthcare. This survey highlights parallels between the perceptions of different clinician groups in Australia and New Zealand about artificial intelligence in medicine. Artificial intelligence was recognized as valuable technology that will have wide-ranging impacts on healthcare.

Sign in / Sign up

Export Citation Format

Share Document