The basic understanding of Artificial Intelligence(AI) - from a normative perspective

2021 ◽  
Vol 38 (3) ◽  
pp. 1-25
Author(s):  
Mi-Won Lim
2020 ◽  
Author(s):  
Weihua Yang ◽  
Bo Zheng ◽  
Maonian Wu ◽  
Shaojun Zhu ◽  
Hongxia Zhou ◽  
...  

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.


2021 ◽  
pp. 146144482110227
Author(s):  
Erik Hermann

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.


2019 ◽  
Vol 74 (3) ◽  
pp. 303-320
Author(s):  
Raúl González Fabre

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.


Author(s):  
Viktor Elliot ◽  
Mari Paananen ◽  
Miroslaw Staron

We propose an exercise with the purpose of providing a basic understanding of key concepts within AI and extending the understanding of AI beyond mathematics. The exercise allows participants to carry out analysis based on accounting data using visualization tools as well as to develop their own machine learning algorithms that can mimic their decisions. Finally, we also problematize the use of AI in decision-making, with such aspects as biases in data and/or ethical concerns.


2019 ◽  
Vol 17 (1) ◽  
pp. 51-55 ◽  
Author(s):  
Viktor H. Elliot ◽  
Mari Paananen ◽  
Miroslaw Staron

ABSTRACT We propose an exercise with the purpose of providing a basic understanding of key concepts within AI and extending the understanding of AI beyond mathematics. The exercise allows participants to carry out analysis based on accounting data using visualization tools as well as to develop their own machine learning algorithms that can mimic their decisions. Finally, we also problematize the use of AI in decision-making, with such aspects as biases in data and/or ethical concerns. JEL Classifications: A29; C44; C45; D81; M41.


2021 ◽  
Author(s):  
Bo Zheng ◽  
Maonian Wu ◽  
Shaojun Zhu ◽  
Hongxia Zhou ◽  
Xiulan Hao ◽  
...  

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.


2021 ◽  
Vol 13 (1) ◽  
pp. 46-51
Author(s):  
Fabian Buder ◽  
Koen Pauwels ◽  
Kairun Daikoku

Abstract In our augmented world, many decision situations are designed by smart technologies. Artificial intelligence helps reduce information overload, filter relevant information and limit an otherwise overwhelming abundance of choices. While such algorithms make our lives more convenient, they also fulfill various organizational objectives that users may not be aware of and that may not be in their best interest. We do not know whether algorithms truly optimize the benefits of their users or rather the return on investment of a company. They are not only designed for convenience but also to be addictive, and this opens the doors for manipulation. Therefore, augmented decision making undermines the freedom of choice. To limit the threats of augmented decisions and enable humans to be critical towards the outcomes of artificial intelligence–driven recommendations, everybody should develop “algorithmic literacy.” It involves a basic understanding of artificial intelligence and how algorithms work in the background. Algorithmic literacy also requires that users understand the role and value of the personal data they sacrifice in exchange for decision augmentation.


2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Bo Zheng ◽  
Mao-nian Wu ◽  
Shao-jun Zhu ◽  
Hong-xia Zhou ◽  
Xiu-lan Hao ◽  
...  

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.


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