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.

scholarly journals Attitudes of Medical Workers Toward Artificial Intelligence in Ophthalmology: A Comparative Survey

2021 ◽  
Author(s):  
Bo Zheng ◽  
Maonian Wu ◽  
Shaojun Zhu ◽  
Hongxia Zhou ◽  
Xiulan Hao ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Medical Ethics ◽  
Acceptance Level ◽  
Electronic Questionnaire ◽  
The People ◽  
Basic Understanding ◽  
Survey Results ◽  
Comparative Survey ◽  
Almost All

Abstract Background: In the development of artificial intelligence in ophthalmology, the ophthalmic AI-related recognition issues are prominent, but there is a lack of research into people's familiarity with and their attitudes toward ophthalmic AI. This survey aims to assess medical workers’ and other professional technicians’ familiarity with, attitudes toward, and concerns about AI in ophthalmology.Methods: An electronic questionnaire was designed through the app Questionnaire Star, and was sent to participants through WeChat, China’s version of Facebook or WhatsApp. The participation was voluntary and anonymous. The questionnaire consisted of four parts, namely the participant’s background, their basic understanding of AI, their attitudes toward AI, and their 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 participants completed the questionnaire, of whom 291 were medical workers and 271 were other professional technicians. About 1/3 of the participants understood AI and 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 AI in ophthalmology would partly replace doctors, with about 59.07% still having a relatively high acceptance level of ophthalmic AI. Meanwhile, among those with AI in ophthalmology application experiences (30.6%), above 70% of participants held a full acceptance attitude toward AI in ophthalmology. The participants expressed medical ethics concerns about AI in ophthalmology. And among the participants who understood AI in ophthalmology, almost all the people said that there was a need to increase the study of medical ethics issues in the ophthalmic AI field.Conclusions: The survey results revealed that the medical workers had a higher understanding level of AI in ophthalmology 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 AI in ophthalmology, and there was a need to strengthen research into medical ethics issues of the field.

scholarly journals Attitudes of medical workers in China toward artificial intelligence in ophthalmology: a comparative survey

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Bo Zheng ◽  
Mao-nian Wu ◽  
Shao-jun Zhu ◽  
Hong-xia Zhou ◽  
Xiu-lan Hao ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Medical Ethics ◽  
Cross Sectional Study ◽  
Cross Sectional ◽  
Acceptance Level ◽  
The People ◽  
Basic Understanding ◽  
Survey Results ◽  
Comparative Survey ◽  
Almost All

Abstract Background In the development of artificial intelligence in ophthalmology, the ophthalmic AI-related recognition issues are prominent, but there is a lack of research into people’s familiarity with and their attitudes toward ophthalmic AI. This survey aims to assess medical workers’ and other professional technicians’ familiarity with, attitudes toward, and concerns about AI in ophthalmology. Methods This is a cross-sectional study design study. An electronic questionnaire was designed through the app Questionnaire Star, and was sent to respondents through WeChat, China’s version of Facebook or WhatsApp. The participation was voluntary and anonymous. The questionnaire consisted of four parts, namely the respondents’ background, their basic understanding of AI, their attitudes toward AI, and their concerns about AI. A total of 562 respondents were counted, with 562 valid questionnaires returned. The results of the questionnaires are displayed in an Excel 2003 form. Results There were 291 medical workers and 271 other professional technicians completed the questionnaire. About 1/3 of the respondents understood AI and ophthalmic AI. The percentages of people who understood ophthalmic AI among medical workers and other professional technicians were about 42.6 % and 15.6 %, respectively. About 66.0 % of the respondents thought that AI in ophthalmology would partly replace doctors, about 59.07 % having a relatively high acceptance level of ophthalmic AI. Meanwhile, among those with AI in ophthalmology application experiences (30.6 %), above 70 % of respondents held a full acceptance attitude toward AI in ophthalmology. The respondents expressed medical ethics concerns about AI in ophthalmology. And among the respondents who understood AI in ophthalmology, almost all the people said that there was a need to increase the study of medical ethics issues in the ophthalmic AI field. Conclusions The survey results revealed that the medical workers had a higher understanding level of AI in ophthalmology than other professional technicians, making it necessary to popularize ophthalmic AI education among other professional technicians. Most of the respondents did not have any experience in ophthalmic AI but generally had a relatively high acceptance level of AI in ophthalmology, and there was a need to strengthen research into medical ethics issues.

scholarly journals Physician Confidence in Artificial Intelligence: An Online Mobile Survey (Preprint)

2018 ◽  
Author(s):  
Songhee Oh ◽  
Jae Heon Kim ◽  
Sung-Woo Choi ◽  
Hee Jeong Lee ◽  
Jungrak Hong ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Online Survey ◽  
Medical Application ◽  
Disease Diagnosis ◽  
Medical Field ◽  
High Quality ◽  
Inadequate Information ◽  
Development Direction ◽  
The Future ◽  
Mobile Survey

BACKGROUND It is expected that artificial intelligence (AI) will be used extensively in the medical field in the future. OBJECTIVE The purpose of this study is to investigate the awareness of AI among Korean doctors and to assess physicians’ attitudes toward the medical application of AI. METHODS We conducted an online survey composed of 11 closed-ended questions using Google Forms. The survey consisted of questions regarding the recognition of and attitudes toward AI, the development direction of AI in medicine, and the possible risks of using AI in the medical field. RESULTS A total of 669 participants completed the survey. Only 40 (5.9%) answered that they had good familiarity with AI. However, most participants considered AI useful in the medical field (558/669, 83.4% agreement). The advantage of using AI was seen as the ability to analyze vast amounts of high-quality, clinically relevant data in real time. Respondents agreed that the area of medicine in which AI would be most useful is disease diagnosis (558/669, 83.4% agreement). One possible problem cited by the participants was that AI would not be able to assist in unexpected situations owing to inadequate information (196/669, 29.3%). Less than half of the participants(294/669, 43.9%) agreed that AI is diagnostically superior to human doctors. Only 237 (35.4%) answered that they agreed that AI could replace them in their jobs. CONCLUSIONS This study suggests that Korean doctors and medical students have favorable attitudes toward AI in the medical field. The majority of physicians surveyed believed that AI will not replace their roles in the future.

Europe

2020 ◽  
pp. 649-666
Author(s):  
Andrea Renda
Keyword(s):  
Artificial Intelligence ◽  
Digital Technology ◽  
Policy Framework ◽  
Expert Group ◽  
Ethical Guidelines ◽  
Ethical Implications ◽  
Strong Focus ◽  
Ethics Guidelines ◽  
Definition Of ◽  
High Level

This chapter assesses Europe’s efforts in developing a full-fledged strategy on the human and ethical implications of artificial intelligence (AI). The strong focus on ethics in the European Union’s AI strategy should be seen in the context of an overall strategy that aims at protecting citizens and civil society from abuses of digital technology but also as part of a competitiveness-oriented strategy aimed at raising the standards for access to Europe’s wealthy Single Market. In this context, one of the most peculiar steps in the European Union’s strategy was the creation of an independent High-Level Expert Group on AI (AI HLEG), accompanied by the launch of an AI Alliance, which quickly attracted several hundred participants. The AI HLEG, a multistakeholder group including fifty-two experts, was tasked with the definition of Ethics Guidelines as well as with the formulation of “Policy and Investment Recommendations.” With the advice of the AI HLEG, the European Commission put forward ethical guidelines for Trustworthy AI—which are now paving the way for a comprehensive, risk-based policy framework.

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.

scholarly journals Use of Artificial Intelligence to understand adults’ thoughts and behaviours relating to COVID-19

2021 ◽  
pp. 175791392097933
Author(s):  
SW Flint ◽  
A Piotrkowicz ◽  
K Watts
Keyword(s):  
Artificial Intelligence ◽  
Online Survey ◽  
Severe Illness ◽  
Free Text ◽  
Community Recovery ◽  
Substantial Impact ◽  
Lifestyle Behaviours ◽  
Artificial Intelligence Methods ◽  
High Concern ◽  
The Impact

Aims: The outbreak of severe acute respiratory syndrome coronavirus 2 (COVID-19) is a global pandemic that has had substantial impact across societies. An attempt to reduce infection and spread of the disease, for most nations, has led to a lockdown period, where people’s movement has been restricted resulting in a consequential impact on employment, lifestyle behaviours and wellbeing. As such, this study aimed to explore adults’ thoughts and behaviours in response to the outbreak and resulting lockdown measures. Methods: Using an online survey, 1126 adults responded to invitations to participate in the study. Participants, all aged 18 years or older, were recruited using social media, email distribution lists, website advertisement and word of mouth. Sentiment and personality features extracted from free-text responses using Artificial Intelligence methods were used to cluster participants. Results: Findings demonstrated that there was varied knowledge of the symptoms of COVID-19 and high concern about infection, severe illness and death, spread to others, the impact on the health service and on the economy. Higher concerns about infection, illness and death were reported by people identified at high risk of severe illness from COVID-19. Behavioural clusters, identified using Artificial Intelligence methods, differed significantly in sentiment and personality traits, as well as concerns about COVID-19, actions, lifestyle behaviours and wellbeing during the COVID-19 lockdown. Conclusions: This time-sensitive study provides important insights into adults’ perceptions and behaviours in response to the COVID-19 pandemic and associated lockdown. The use of Artificial Intelligence has identified that there are two behavioural clusters that can predict people’s responses during the COVID-19 pandemic, which goes beyond simple demographic groupings. Considering these insights may improve the effectiveness of communication, actions to reduce the direct and indirect impact of the COVID-19 pandemic and to support community recovery.

Artificial intelligence and mass personalization of communication content—An ethical and literacy perspective

2021 ◽  
pp. 146144482110227
Author(s):  
Erik Hermann
Keyword(s):  
Artificial Intelligence ◽  
Conceptual Analysis ◽  
Need Satisfaction ◽  
Ethical Challenges ◽  
Social Good ◽  
Communication Content ◽  
Basic Understanding ◽  
Stakeholder Perspective ◽  
Multi Stakeholder ◽  
Mass Personalization

Artificial intelligence (AI) is (re)shaping communication and contributes to (commercial and informational) need satisfaction by means of mass personalization. However, the substantial personalization and targeting opportunities do not come without ethical challenges. Following an AI-for-social-good perspective, the authors systematically scrutinize the ethical challenges of deploying AI for mass personalization of communication content from a multi-stakeholder perspective. The conceptual analysis reveals interdependencies and tensions between ethical principles, which advocate the need of a basic understanding of AI inputs, functioning, agency, and outcomes. By this form of AI literacy, individuals could be empowered to interact with and treat mass-personalized content in a way that promotes individual and social good while preventing harm.

scholarly journals The Youth Labour Market, Populism and the Digitalization of Economies

2019 ◽  
Vol 74 (3) ◽  
pp. 303-320
Author(s):  
Raúl González Fabre
Keyword(s):  
Artificial Intelligence ◽  
Labour Market ◽  
The Political ◽  
Economic Competition ◽  
Youth Labour Market ◽  
Basic Understanding ◽  
Youth Labour

Firstly, a basic understanding of economic competition and its role in the lives of the youth is presented. Then two forces are described which have affected the lowest echelons of the labour competition market during the last decade and the political reactions (xenophobic, anti–system) which ensued. Finally, some ideas are summarized which were presented at the discussion on the competitive impact of artificial intelligence (AI) on the labour market, some of the responses proposed and the basic difficulties that affect them. We conclude that one must expect further political convulsions following infringements of the AI upon the structure of the youth labour market.

Commentary: Beyond Common or Uncommon Morality

2020 ◽  
Vol 29 (3) ◽  
pp. 426-428
Author(s):  
LESLIE FRANCIS
Keyword(s):  
Medical Ethics ◽  
Common Morality ◽  
Medical Professionals ◽  
Ethical Standards ◽  
Overlapping Consensus ◽  
Healthcare Professions

In “Medical Ethics: Common or Uncommon Morality,”1 Rosamond Rhodes defends a specialist view of medical ethics, specifically the ethics of physicians. Rhodes’s account is specifically about the ethics of medical professionals, rooted in what these professionals do. It would seem to follow that other healthcare professions might be subject to ethical standards that differ from those applicable to physicians, rooted in what these other professions do, but I leave this point aside for purposes of this commentary. Rhodes’s view includes both a negative and a positive thesis. The negative thesis is that precepts in medical ethics—understood as the ethics of physicians—cannot be derived from principles of common morality. The positive thesis is two-fold: that precepts in medical ethics must be derived from an account of the special nature of what physicians do, and that this account is to be understood through an overlapping consensus of rational and reasonable medical professionals. While I agree emphatically with, and have learned a great deal from, Rhodes’s defense of the negative thesis, I disagree with both claims in Rhodes’s positive thesis, for reasons I will now explain after a brief observation about the negative thesis.

Infodemic surrounding COVID-19: Can LIS students recognize and categorize “problematic information” types on social media?

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Shamima Yesmin ◽  
S.M. Zabed Ahmed
Keyword(s):  
Social Media ◽  
Online Survey ◽  
Information Science ◽  
Wrong Answer ◽  
Student Groups ◽  
Content Type ◽  
Correct Definition ◽  
Significant Difference ◽  
Definition Of ◽  
And Task

Purpose The purpose of this paper is to investigate Library and Information Science (LIS) students’ understanding of infodemic and related terminologies and their ability to categorize COVID-19-related problematic information types using examples from social media platforms. Design/methodology/approach The participants of this study were LIS students from a public-funded university located at the south coast of Bangladesh. An online survey was conducted which, in addition to demographic and study information, asked students to identify the correct definition of infodemic and related terminologies and to categorize the COVID-related problematic social media posts based on their inherent problem characteristics. The correct answer for each definition and task question was assigned a score of “1”, whereas the wrong answer was coded as “0”. The percentages of correctness score for total and each category of definition and task-specific questions were computed. The independent sample t-test and ANOVA were run to examine the differences in total and category-specific scores between student groups. Findings The findings revealed that students’ knowledge concerning the definition of infodemic and related terminologies and the categorization of COVID-19-related problematic social media posts was poor. There was no significant difference in correctness scores between student groups in terms of gender, age and study levels. Originality/value To the best of the authors’ knowledge, this is the first time an effort was made to understand LIS students’ recognition and classification of problematic information. The findings can assist LIS departments in revising and improving the existing information literacy curriculum for students.

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