Web-based study on Chinese dermatologists’ attitudes towards artificial intelligence

Shen, Changbing; Li, Chengxu; Wang, Ziyi; Shen, Xue; Gao, Jing; Ko, Randy; Yan, Jing; Tang, Xin; Yu, Ruixing; Guo, Junhu; Xu, Feng; Meng, Rusong; Cui, Yong

doi:10.21037/atm.2019.12.102

Cited by 24 publications

(23 citation statements)

References 30 publications

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“…The third-place, surprisingly, is about unemployment with 467 responses or 46%. In this regard, this study converges with the academic literature on the perception of AI integration at work in that people are not very concerned about being replaced by AI but more concerned about human-AI interaction (Pinto dos Santos et al, 2019;Sarwar et al, 2019;Shen et al, 2020;Sit et al, 2020). Table 3 shows 52% of the respondents hold a negative view of the AI managers, and 51% rated themselves below average regarding AI knowledge.…”

supporting

confidence: 77%

“…Similarly, Pinto dos Santos et al (2019) surveyed 263 medical students and found although most respondents thought AI could revolutionize (77%) and improve radiology (86%), 83% did not think human physicians would be replaced. Likewise, Shen et al (2020) found nearly 96% conducts 1,228 Chinese dermatologists from 30 provinces and regions in a webbased survey that believed AI roles are to assist with diagnosis and treatment. On the other hand, while a survey of 484 responses of 19 UK universities medical students show that a majority of students (88%) will play an important role in healthcare yet, nearly half the respondents express their concern about job loss in radiology due to AI (Sit et al, 2020).…”

Section: Students' and Professional's Attitude Toward Aimentioning

confidence: 99%

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My Boss the Computer: A Bayesian analysis of socio-demographic and cross-cultural determinants of attitude toward the Non-Human Resource Management

Mantello¹,

Ho²,

Nguyen³

et al. 2021

Preprint

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Human resource management technologies have moved from biometric surveillance to emotional artificial intelligence (AI) that monitor employees’ engagement and productivity, analyze video interviews and CVs of job applicants. The rise of the US$20 billion emotion AI industry will transform the future workplace. Yet, besides no international consensus on the principles or standards for such technologies, there is a lack of cross-cultural research on future job seekers’ attitude toward such use of AI technologies. This study collects a cross-sectional dataset of 1,015 survey responses of international students from 48 countries and 8 regions worldwide. A majority of the respondents (52%) are concerned about being managed by AI. Following the hypothetico-deductivist philosophy of science, we use the MCMC Hamiltonian approach and conduct a detailed comparison of 10 Bayesian network models with the PSIS-LOO method. We consistently find having a higher income, being male, majoring in business, and/or self-rated familiarity with AI correlate with a more positive view of emotional AI in the workplace. There is also a stark cross-cultural and cross-regional difference. Our analysis shows people from economically less developed regions (Africa, Oceania, Central Asia) tend to exhibit less concern for AI managers. And for East Asian countries, 64% of the Japanese, 56% of the South Korean, and 42% of the Chinese professed the trusting attitude. In contrast, an overwhelming majority of 75% of the European and Northern American possesses the worrying/neutral attitude toward being managed by AI. Regarding religion, Muslim students correlate with the most concern toward emotional AI in the workplace (β_Islam_Attitude’s mean =-0.16, sd =0.10; β_Buddhism_Attitude’s mean =-0.05, sd =0.07; β_Christian_Attitude ‘s mean = -0.10, sd= 0.09). When religiosity is higher, the correlation becomes stronger for Muslim and Buddhist students. This paper adds a cross-cultural perspective to the literature, which is currently skewed toward country-specific and profession-specific samples.

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supporting

confidence: 77%

Section: Students' and Professional's Attitude Toward Aimentioning

confidence: 99%

My Boss the Computer: A Bayesian analysis of socio-demographic and cross-cultural determinants of attitude toward the Non-Human Resource Management

Mantello¹,

Ho²,

Nguyen³

et al. 2021

Preprint

View full text Add to dashboard Cite

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“…The survey results showed that almost Chinese dermatologists considered the role of AI in “assisting dermatologists in their daily diagnosis and treatment activities.” AI should be implemented in secondary hospitals and skin tumors in the future. [ 22 ] Our results show that even on the premise that the diagnostic accuracy of Youzhi AI software was reduced, there was no significant difference between its accuracy and the average level of dermatologists, and Youzhi AI software was even better than dermatologists in recognizing the type of skin tumor diagnosed by dermoscopic images. Moreover, the diagnostic accuracy of dermatologists with primary dermoscopic diagnostic ability was not as good as that of Youzhi AI software.…”

Section: Discussionmentioning

confidence: 84%

Diagnostic capacity of skin tumor artificial intelligence-assisted decision-making software in real-world clinical settings

Fei

Shen

et al. 2020

Chinese Medical Journal

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Background Youzhi artificial intelligence (AI) software is the AI-assisted decision-making system for diagnosing skin tumors. The high diagnostic accuracy of Youzhi AI software was previously validated in specific datasets. The objective of this study was to compare the performance of diagnostic capacity between Youzhi AI software and dermatologists in real-world clinical settings. Methods A total of 106 patients who underwent skin tumor resection in the Dermatology Department of China-Japan Friendship Hospital from July 2017 to June 2019 and were confirmed as skin tumors by pathological biopsy were selected. Dermoscopy and clinical images of 106 patients were diagnosed by Youzhi AI software and dermatologists at different dermoscopy diagnostic levels. The primary outcome was to compare the diagnostic accuracy of the Youzhi AI software with that of dermatologists and that measured in the laboratory using specific data sets. The secondary results included the sensitivity, specificity, positive predictive value, negative predictive value, F-measure, and Matthews correlation coefficient of Youzhi AI software in the real-world. Results The diagnostic accuracy of Youzhi AI software in real-world clinical settings was lower than that of the laboratory data ( P < 0.001). The output result of Youzhi AI software has good stability after several tests. Youzhi AI software diagnosed benign and malignant diseases by recognizing dermoscopic images and diagnosed disease types with higher diagnostic accuracy than by recognizing clinical images ( P = 0.008, P = 0.016, respectively). Compared with dermatologists, Youzhi AI software was more accurate in the diagnosis of skin tumor types through the recognition of dermoscopic images ( P = 0.01). By evaluating the diagnostic performance of dermatologists under different modes, the diagnostic accuracy of dermatologists in diagnosing disease types by matching dermoscopic and clinical images was significantly higher than that by identifying dermoscopic and clinical images in random sequence ( P = 0.022). The diagnostic accuracy of dermatologists in the diagnosis of benign and malignant diseases by recognizing dermoscopic images was significantly higher than that by recognizing clinical images ( P = 0.010). Conclusion The diagnostic accuracy of Youzhi AI software for skin tumors in real-world clinical settings was not as high as that of using special data sets in the laboratory. However, there was no significant difference between the diagnostic capacity of Youzhi AI software and the average diagnostic capacity of dermatologists. It can provide assistant diagnostic decisions for dermatologists in the current state.

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“…An overwhelming majority of Chinese dermatologists are favorably disposed to AI and think the role of AI will be in “assisting the daily diagnosis and treatment activities for dermatologists” [ 94 ].…”

Section: Methodsmentioning

confidence: 99%

International Teledermatology Review

2021

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Purpose of Review The use of teledermatology has been evolving slowly for the delivery of health care to remote and underserved populations. Improving technology and the recent COVID-19 pandemic have hastened its use internationally. Recent Findings Some barriers to the use of teledermatology have fallen considerably in the last year. Summary Teledermatology use has increased significantly in recent years in both government-sponsored and private health care systems and individual practices. There are no recognized international practice guidelines and variable use within countries. Many barriers remain to increasing the use of teledermatology.

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Web-based study on Chinese dermatologists’ attitudes towards artificial intelligence

Cited by 24 publications

References 30 publications

My Boss the Computer: A Bayesian analysis of socio-demographic and cross-cultural determinants of attitude toward the Non-Human Resource Management

My Boss the Computer: A Bayesian analysis of socio-demographic and cross-cultural determinants of attitude toward the Non-Human Resource Management

Diagnostic capacity of skin tumor artificial intelligence-assisted decision-making software in real-world clinical settings

International Teledermatology Review

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