scholarly journals A nationwide survey on the perceptions of general surgeons on artificial intelligence

2022 ◽  
Author(s):  
Frank J. Voskens ◽  
Julian R. Abbing ◽  
Anthony T. Ruys ◽  
Jelle P. Ruurda ◽  
Ivo A. M. J. Broeders
Keyword(s):  
Artificial Intelligence ◽  
Ethical Issues ◽  
Current Knowledge ◽  
Nationwide Survey ◽  
Web Based ◽  
Area Of Interest ◽  
Study Results ◽  
Dutch Association ◽  
General Surgeons ◽  
Surgical Field

Aim: Artificial intelligence (AI) has the potential to improve perioperative diagnosis and decision making. Despite promising study results, the majority of AI platforms in surgery currently remain in the research setting. Understanding the current knowledge and general attitude of surgeons toward AI applications in their surgical practice is essential and can contribute to the future development and uptake of AI in surgery. Methods: In March 2021, a web-based survey was conducted among members of the Dutch Association of Surgery. The survey measured opinions on the existing knowledge, expectations, and concerns on AI among surgical residents and surgeons. Results: A total of 313 respondents completed the survey. Overall, 85% of the respondents agreed that AI could be of value in the surgical field and 61% expected AI to improve their diagnostic ability. The outpatient clinic (35.8%) and operating room (39.6%) were stated as area of interest for the use of AI. Statistically, surgeons working in an academic hospital were more likely to be aware of the possibilities of AI (P = 0.01). The surgeons in this survey were not worried about job replacement, however they raised the greatest concerns on accountability issues (50.5%), loss of autonomy (46.6%), and risk of bias (43.5%). Conclusion: This survey demonstrates that the majority of the surgeons show a positive and open attitude towards AI. Although various ethical issues and concerns arise, the expectations regarding the implementation of future surgical AI applications are high.

scholarly journals Exploring the Characteristics and Behaviors of Nurses Who Have Attained Microcelebrity Status on Instagram: Content Analysis

10.2196/16540 ◽  
2020 ◽  
Vol 22 (5) ◽  
pp. e16540
Author(s):  
Hanna Kerr ◽  
Richard Booth ◽  
Kimberley Jackson
Keyword(s):  
Social Media ◽  
Content Analysis ◽  
Policy Development ◽  
Current Knowledge ◽  
Web Based ◽  
Area Of Interest ◽  
Social Media Platforms ◽  
Media Platform ◽  
And Behaviors ◽  
Use Of Social Media

Background Instagram is a social media platform that enables users to share images and videos worldwide. Some nurses have used Instagram to document their experiences as a nurse and have subsequently gained microcelebrity status—that is, a user who purposefully seeks to amass a substantive Web-based following and has become recognized as a niche area of interest. Objective This study aimed to identify the characteristics and behaviors of microcelebrity nurses who act as influencers on Instagram and use their nursing profile to gain attention and presence on the Web. Methods A qualitative, exploratory, nonparticipatory content analysis of media and text generated by a purposeful sample of 10 registered nurses who use Instagram and sustain a definable microcelebrity status was conducted. In this study, manifest and latent data were examined to gain an understanding of the characteristics and behaviors of nurses who have attained microcelebrity status on Instagram. Results Data analysis revealed 5 themes of Instagram posts: (1) engaging Instagram users, (2) educational opportunities and insights, (3) nursing-related humor, (4) emotions experienced by nurses, and (5) media and narratives including patient details or work context. Messages were primarily positive in nature; however, multiple potential privacy, ethical, and professional issues were noted throughout the posted content. Conclusions The findings of this study help to expand the current knowledge related to the use of social media platforms such as Instagram, especially in regard to the emergence of nurses who use this form of technology to achieve or maintain a microcelebrity status. This study calls for additional research on nurses’ attainment of microcelebrity status on social media as well as further policy development to adequately prepare nurses to navigate social media.

scholarly journals Exploring the Characteristics and Behaviors of Nurses Who Have Attained Microcelebrity Status on Instagram: Content Analysis (Preprint)

2019 ◽  
Author(s):  
Hanna Kerr ◽  
Richard Booth ◽  
Kimberley Jackson
Keyword(s):  
Social Media ◽  
Content Analysis ◽  
Policy Development ◽  
Current Knowledge ◽  
Web Based ◽  
Area Of Interest ◽  
Social Media Platforms ◽  
Media Platform ◽  
And Behaviors ◽  
Use Of Social Media

BACKGROUND Instagram is a social media platform that enables users to share images and videos worldwide. Some nurses have used Instagram to document their experiences as a nurse and have subsequently gained microcelebrity status—that is, a user who purposefully seeks to amass a substantive Web-based following and has become recognized as a niche area of interest. OBJECTIVE This study aimed to identify the characteristics and behaviors of microcelebrity nurses who act as influencers on Instagram and use their nursing profile to gain attention and presence on the Web. METHODS A qualitative, exploratory, nonparticipatory content analysis of media and text generated by a purposeful sample of 10 registered nurses who use Instagram and sustain a definable microcelebrity status was conducted. In this study, manifest and latent data were examined to gain an understanding of the characteristics and behaviors of nurses who have attained microcelebrity status on Instagram. RESULTS Data analysis revealed 5 themes of Instagram posts: (1) engaging Instagram users, (2) educational opportunities and insights, (3) nursing-related humor, (4) emotions experienced by nurses, and (5) media and narratives including patient details or work context. Messages were primarily positive in nature; however, multiple potential privacy, ethical, and professional issues were noted throughout the posted content. CONCLUSIONS The findings of this study help to expand the current knowledge related to the use of social media platforms such as Instagram, especially in regard to the emergence of nurses who use this form of technology to achieve or maintain a microcelebrity status. This study calls for additional research on nurses’ attainment of microcelebrity status on social media as well as further policy development to adequately prepare nurses to navigate social media.

The Oxford Handbook of Ethics of AI

2020 ◽  
Keyword(s):  
Artificial Intelligence ◽  
Ethical Issues ◽  
Rapid Development ◽  
Data Driven ◽  
International Human Rights Law ◽  
Human Knowledge ◽  
Human Rights Law ◽  
Ai Ethics ◽  
And Behavior ◽  
Control Complex

This book explores the intertwining domains of artificial intelligence (AI) and ethics—two highly divergent fields which at first seem to have nothing to do with one another. AI is a collection of computational methods for studying human knowledge, learning, and behavior, including by building agents able to know, learn, and behave. Ethics is a body of human knowledge—far from completely understood—that helps agents (humans today, but perhaps eventually robots and other AIs) decide how they and others should behave. Despite these differences, however, the rapid development in AI technology today has led to a growing number of ethical issues in a multitude of fields, ranging from disciplines as far-reaching as international human rights law to issues as intimate as personal identity and sexuality. In fact, the number and variety of topics in this volume illustrate the width, diversity of content, and at times exasperating vagueness of the boundaries of “AI Ethics” as a domain of inquiry. Within this discourse, the book points to the capacity of sociotechnical systems that utilize data-driven algorithms to classify, to make decisions, and to control complex systems. Given the wide-reaching and often intimate impact these AI systems have on daily human lives, this volume attempts to address the increasingly complicated relations between humanity and artificial intelligence. It considers not only how humanity must conduct themselves toward AI but also how AI must behave toward humanity.

Ethics of Artificial Intelligence in Transport

2020 ◽  
pp. 667-683
Author(s):  
Bryant Walker Smith
Keyword(s):  
Artificial Intelligence ◽  
Ethical Issues ◽  
Ethical Question ◽  
Power Dynamics ◽  
Automated Vehicles ◽  
Automated Driving ◽  
The U.S ◽  
Policy Solutions

This chapter highlights key ethical issues in the use of artificial intelligence in transport by using automated driving as an example. These issues include the tension between technological solutions and policy solutions; the consequences of safety expectations; the complex choice between human authority and computer authority; and power dynamics among individuals, governments, and companies. In 2017 and 2018, the U.S. Congress considered automated driving legislation that was generally supported by many of the larger automated-driving developers. However, this automated-driving legislation failed to pass because of a lack of trust in technologies and institutions. Trustworthiness is much more of an ethical question. Automated vehicles will not be driven by individuals or even by computers; they will be driven by companies acting through their human and machine agents. An essential issue for this field—and for artificial intelligence generally—is how the companies that develop and deploy these technologies should earn people’s trust.

scholarly journals Knowledge, Attitude, and Practices on Antimicrobial Use and Antimicrobial Resistance among Poultry Drug and Feed Sellers in Bangladesh

2021 ◽  
Vol 8 (6) ◽  
pp. 111
Author(s):  
Md. Abul Kalam ◽  
Md. Abdul Alim ◽  
Shahanaj Shano ◽  
Md. Raihan Khan Nayem ◽  
Md. Rahim Badsha ◽  
...  
Keyword(s):  
Antimicrobial Resistance ◽  
Current Knowledge ◽  
Rank Order ◽  
Antimicrobial Use ◽  
Poultry Production ◽  
Attitudes And Practices ◽  
12Th Grade ◽  
Study Results ◽  
Knowledge Attitudes And Practices ◽  
Drug Sellers

Poultry production has boomed in Bangladesh in recent years. The poultry sector has contributed significantly to meet the increased demand for animal source proteins in the country. However, increased use of antimicrobials and antibiotics appeared to be a significant threat to food safety in the poultry sector. The poultry drug and feed sellers are at the frontline position involving selecting and delivering the antimicrobials to the poultry farmers. Studies assessing the poultry drug and feed sellers’ knowledge, attitudes, and practices (KAPs) are limited. The current study aimed to assess the community poultry drug and feed sellers’ KAPs of antimicrobial use (AMU) and antimicrobial resistance (AMR) in some selected areas of Bangladesh. We determined the respondents’ (drug and the feed sellers) KAPs of AMU and AMR using a tested and paper-based questionnaire. The study demonstrated that most respondents have insufficient knowledge, less positive attitudes, and inappropriate practices regarding AMU and AMR. The factor score analysis further showed that the type of respondents and their years of experience, level of education, and training on the drug were the significant factors impacting the current knowledge, attitudes, and practices of AMU and AMR. The adjusted logistic regression analysis revealed that the drug sellers who completed their education up to 12th grade and had training on the drug had adequate knowledge of AMU and AMR. The data also showed that the drug sellers belong to the age group 31–35 and 36–40 years and who completed 12th grade had good attitudes on the same. Likewise, the analysis further determined that drug sellers belonging the age category 18–25 and 26–30 years, and interestingly, the respondents who completed education up to 12th grade, had better practices. Spearman’s rank-order correlation revealed a positive association between each pair of the KAPs scores for the respondents. The correlation was fair between knowledge–attitudes, knowledge–practices, and attitudes–practices. Based on the current study results, we recommend educational interventions and appropriate training for the poultry drug and feed sellers to raise awareness and to upgrade their current knowledge on the appropriate use of antimicrobials. This will ultimately lead to reducing the chances of developing AMR in the poultry sectors of the country.

scholarly journals Artificial intelligence for good health: a scoping review of the ethics literature

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Kathleen Murphy ◽  
Erica Di Ruggiero ◽  
Ross Upshur ◽  
Donald J. Willison ◽  
Neha Malhotra ◽  
...  
Keyword(s):  
Public Health ◽  
Artificial Intelligence ◽  
Global Health ◽  
Population Health ◽  
Health Systems ◽  
Scoping Review ◽  
Industrial Revolution ◽  
Ethical Issues ◽  
Grey Literature ◽  
Ethical Implications

Abstract Background Artificial intelligence (AI) has been described as the “fourth industrial revolution” with transformative and global implications, including in healthcare, public health, and global health. AI approaches hold promise for improving health systems worldwide, as well as individual and population health outcomes. While AI may have potential for advancing health equity within and between countries, we must consider the ethical implications of its deployment in order to mitigate its potential harms, particularly for the most vulnerable. This scoping review addresses the following question: What ethical issues have been identified in relation to AI in the field of health, including from a global health perspective? Methods Eight electronic databases were searched for peer reviewed and grey literature published before April 2018 using the concepts of health, ethics, and AI, and their related terms. Records were independently screened by two reviewers and were included if they reported on AI in relation to health and ethics and were written in the English language. Data was charted on a piloted data charting form, and a descriptive and thematic analysis was performed. Results Upon reviewing 12,722 articles, 103 met the predetermined inclusion criteria. The literature was primarily focused on the ethics of AI in health care, particularly on carer robots, diagnostics, and precision medicine, but was largely silent on ethics of AI in public and population health. The literature highlighted a number of common ethical concerns related to privacy, trust, accountability and responsibility, and bias. Largely missing from the literature was the ethics of AI in global health, particularly in the context of low- and middle-income countries (LMICs). Conclusions The ethical issues surrounding AI in the field of health are both vast and complex. While AI holds the potential to improve health and health systems, our analysis suggests that its introduction should be approached with cautious optimism. The dearth of literature on the ethics of AI within LMICs, as well as in public health, also points to a critical need for further research into the ethical implications of AI within both global and public health, to ensure that its development and implementation is ethical for everyone, everywhere.

Artificial Intelligence and Ethics in Dentistry: A Scoping Review

2021 ◽  
pp. 002203452110138
Author(s):  
C.M. Mörch ◽  
S. Atsu ◽  
W. Cai ◽  
X. Li ◽  
S.A. Madathil ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Scoping Review ◽  
Ethical Issues ◽  
Data Extraction ◽  
Cochrane Library ◽  
Data Sets ◽  
Ethical Challenges ◽  
Internal Validation ◽  
Neural Learning ◽  
Learning Techniques

Dentistry increasingly integrates artificial intelligence (AI) to help improve the current state of clinical dental practice. However, this revolutionary technological field raises various complex ethical challenges. The objective of this systematic scoping review is to document the current uses of AI in dentistry and the ethical concerns or challenges they imply. Three health care databases (MEDLINE [PubMed], SciVerse Scopus, and Cochrane Library) and 2 computer science databases (ArXiv, IEEE Xplore) were searched. After identifying 1,553 records, the documents were filtered, and a full-text screening was performed. In total, 178 studies were retained and analyzed by 8 researchers specialized in dentistry, AI, and ethics. The team used Covidence for data extraction and Dedoose for the identification of ethics-related information. PRISMA guidelines were followed. Among the included studies, 130 (73.0%) studies were published after 2016, and 93 (52.2%) were published in journals specialized in computer sciences. The technologies used were neural learning techniques for 75 (42.1%), traditional learning techniques for 76 (42.7%), or a combination of several technologies for 20 (11.2%). Overall, 7 countries contributed to 109 (61.2%) studies. A total of 53 different applications of AI in dentistry were identified, involving most dental specialties. The use of initial data sets for internal validation was reported in 152 (85.4%) studies. Forty-five ethical issues (related to the use AI in dentistry) were reported in 22 (12.4%) studies around 6 principles: prudence (10 times), equity (8), privacy (8), responsibility (6), democratic participation (4), and solidarity (4). The ratio of studies mentioning AI-related ethical issues has remained similar in the past years, showing that there is no increasing interest in the field of dentistry on this topic. This study confirms the growing presence of AI in dentistry and highlights a current lack of information on the ethical challenges surrounding its use. In addition, the scarcity of studies sharing their code could prevent future replications. The authors formulate recommendations to contribute to a more responsible use of AI technologies in dentistry.

scholarly journals Ethics as a Service: A Pragmatic Operationalisation of AI Ethics

2021 ◽  
Author(s):  
Jessica Morley ◽  
Anat Elhalal ◽  
Francesca Garcia ◽  
Libby Kinsey ◽  
Jakob Mökander ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Ethical Issues ◽  
Ethics Codes ◽  
Practical Design ◽  
Ethical Design ◽  
Ai Ethics ◽  
Algorithmic Design ◽  
Almost All ◽  
Technical Guidance ◽  
Tools And Methods

AbstractAs the range of potential uses for Artificial Intelligence (AI), in particular machine learning (ML), has increased, so has awareness of the associated ethical issues. This increased awareness has led to the realisation that existing legislation and regulation provides insufficient protection to individuals, groups, society, and the environment from AI harms. In response to this realisation, there has been a proliferation of principle-based ethics codes, guidelines and frameworks. However, it has become increasingly clear that a significant gap exists between the theory of AI ethics principles and the practical design of AI systems. In previous work, we analysed whether it is possible to close this gap between the ‘what’ and the ‘how’ of AI ethics through the use of tools and methods designed to help AI developers, engineers, and designers translate principles into practice. We concluded that this method of closure is currently ineffective as almost all existing translational tools and methods are either too flexible (and thus vulnerable to ethics washing) or too strict (unresponsive to context). This raised the question: if, even with technical guidance, AI ethics is challenging to embed in the process of algorithmic design, is the entire pro-ethical design endeavour rendered futile? And, if no, then how can AI ethics be made useful for AI practitioners? This is the question we seek to address here by exploring why principles and technical translational tools are still needed even if they are limited, and how these limitations can be potentially overcome by providing theoretical grounding of a concept that has been termed ‘Ethics as a Service.’

scholarly journals Ethics of Corporeal, Co-present Robots as Agents of Influence: a Review

2021 ◽  
Author(s):  
AJung Moon ◽  
Shalaleh Rismani ◽  
H. F. Machiel Van der Loos
Keyword(s):  
Artificial Intelligence ◽  
Physical Environment ◽  
Ethical Issues ◽  
Human Robot Interaction ◽  
Physical Interaction ◽  
Ethical Challenges ◽  
Natural Tendency ◽  
Ai Ethics ◽  
Recent Trends ◽  
The Impact

Abstract Purpose of Review To summarize the set of roboethics issues that uniquely arise due to the corporeality and physical interaction modalities afforded by robots, irrespective of the degree of artificial intelligence present in the system. Recent Findings One of the recent trends in the discussion of ethics of emerging technologies has been the treatment of roboethics issues as those of “embodied AI,” a subset of AI ethics. In contrast to AI, however, robots leverage human’s natural tendency to be influenced by our physical environment. Recent work in human-robot interaction highlights the impact a robot’s presence, capacity to touch, and move in our physical environment has on people, and helping to articulate the ethical issues particular to the design of interactive robotic systems. Summary The corporeality of interactive robots poses unique sets of ethical challenges. These issues should be considered in the design irrespective of and in addition to the ethics of artificial intelligence implemented in them.

scholarly journals The Role of Artificial Intelligence in the Diagnosis and Prognosis of Renal Cell Tumors

Diagnostics ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 206
Author(s):  
Matteo Giulietti ◽  
Monia Cecati ◽  
Berina Sabanovic ◽  
Andrea Scirè ◽  
Alessia Cimadamore ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Renal Cancer ◽  
Renal Cell ◽  
Treatment Plan ◽  
Molecular Data ◽  
Receiver Operating Curve ◽  
Diagnosis And Prognosis ◽  
Study Results ◽  
Gene Panels ◽  
Next Generation Sequencing Ngs

The increasing availability of molecular data provided by next-generation sequencing (NGS) techniques is allowing improvement in the possibilities of diagnosis and prognosis in renal cancer. Reliable and accurate predictors based on selected gene panels are urgently needed for better stratification of renal cell carcinoma (RCC) patients in order to define a personalized treatment plan. Artificial intelligence (AI) algorithms are currently in development for this purpose. Here, we reviewed studies that developed predictors based on AI algorithms for diagnosis and prognosis in renal cancer and we compared them with non-AI-based predictors. Comparing study results, it emerges that the AI prediction performance is good and slightly better than non-AI-based ones. However, there have been only minor improvements in AI predictors in terms of accuracy and the area under the receiver operating curve (AUC) over the last decade and the number of genes used had little influence on these indices. Furthermore, we highlight that different studies having the same goal obtain similar performance despite the fact they use different discriminating genes. This is surprising because genes related to the diagnosis or prognosis are expected to be tumor-specific and independent of selection methods and algorithms. The performance of these predictors will be better with the improvement in the learning methods, as the number of cases increases and by using different types of input data (e.g., non-coding RNAs, proteomic and metabolic). This will allow for more precise identification, classification and staging of cancerous lesions which will be less affected by interpathologist variability.

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