PUBLICATION TRENDS IN GASTROENTEROLOGY AND HEPATOLOGY OVER THE PAST 40 YEARS: AN ARTIFICIAL INTELLIGENCE ANALYSIS

The world of work has been impacted by technology. Work is different than it was in the past due to digital innovation. Labor market opportunities are becoming polarized between high-end and low-end skilled jobs. Migration and its effects on employment have become a sensitive political issue. From Buffalo to Beijing public debates are raging about the future of work. Developments like artificial intelligence and machine intelligence are contributing to productivity, efficiency, safety, and convenience but are also having an impact on jobs, skills, wages, and the nature of work. The “undiscovered country” of the workplace today is the combination of the changing landscape of work itself and the availability of ill-fitting tools, platforms, and knowledge to train for the requirements, skills, and structure of this new age.

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Artificial Intelligence and Human Rights: Four Realms of Discussion: Summary of Remarks

Proceedings of the ASIL Annual Meeting ◽

10.1017/amp.2021.47 ◽

2020 ◽

Vol 114 ◽

pp. 242-245

Author(s):

Jootaek Lee

Keyword(s):

Artificial Intelligence ◽

Machine Learning ◽

Decision Making ◽

Deep Learning ◽

Language Processing ◽

Human Reasoning ◽

The Past ◽

Making Choices ◽

Data Capturing ◽

Intensive Procedures

The term, Artificial Intelligence (AI), has changed since it was first coined by John MacCarthy in 1956. AI, believed to have been created with Kurt Gödel's unprovable computational statements in 1931, is now called deep learning or machine learning. AI is defined as a computer machine with the ability to make predictions about the future and solve complex tasks, using algorithms. The AI algorithms are enhanced and become effective with big data capturing the present and the past while still necessarily reflecting human biases into models and equations. AI is also capable of making choices like humans, mirroring human reasoning. AI can help robots to efficiently repeat the same labor intensive procedures in factories and can analyze historic and present data efficiently through deep learning, natural language processing, and anomaly detection. Thus, AI covers a spectrum of augmented intelligence relating to prediction, autonomous intelligence relating to decision making, automated intelligence for labor robots, and assisted intelligence for data analysis.

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Boundaries Between Research Ethics and Ethical Research Use in Artificial Intelligence Health Research

Journal of Empirical Research on Human Research Ethics ◽

10.1177/15562646211002744 ◽

2021 ◽

pp. 155626462110027

Author(s):

Gabrielle Samuel ◽

Jenn Chubb ◽

Gemma Derrick

Keyword(s):

Artificial Intelligence ◽

Health Research ◽

Decision Makers ◽

Societal Impact ◽

The Past ◽

Research And Innovation ◽

The United Kingdom ◽

Responsible Research ◽

Past Half

The governance of ethically acceptable research in higher education institutions has been under scrutiny over the past half a century. Concomitantly, recently, decision makers have required researchers to acknowledge the societal impact of their research, as well as anticipate and respond to ethical dimensions of this societal impact through responsible research and innovation principles. Using artificial intelligence population health research in the United Kingdom and Canada as a case study, we combine a mapping study of journal publications with 18 interviews with researchers to explore how the ethical dimensions associated with this societal impact are incorporated into research agendas. Researchers separated the ethical responsibility of their research with its societal impact. We discuss the implications for both researchers and actors across the Ethics Ecosystem.

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The Future of the Planetary Trust in a Kaleidoscopic World

Environmental Policy and Law ◽

10.3233/epl-209001 ◽

2021 ◽

pp. 1-8

Author(s):

Edith Brown Weiss

Keyword(s):

Artificial Intelligence ◽

Natural Resource ◽

Human Activities ◽

New Technologies ◽

Future Generations ◽

Nuclear War ◽

Human Environment ◽

The Past ◽

Resource Degradation ◽

Shared Goal

Today, it is evident that we are part of a planetary trust. Conserving our planet represents a public good, global as well as local. The threats to future generations resulting from human activities make applying the normative framework of a planetary trust even more urgent than in the past decades. Initially, the planetary trust focused primarily on threats to the natural system of our human environment such as pollution and natural resource degradation, and on threats to cultural heritage. Now, we face a higher threat of nuclear war, cyber wars, and threats from gene drivers that can cause inheritable changes to genes, potential threats from other new technologies such as artificial intelligence, and possible pandemics. In this context, it is proposed that in the kaleidoscopic world, we must engage all the actors to cooperate with the shared goal of caring for and maintaining planet Earth in trust for present and future generations.

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Global publication trends and hotspots of molecular biomarkers in DILI from 1991 to 2020: A 30-year bibliometric analysis

Science Progress ◽

10.1177/00368504211000535 ◽

2021 ◽

Vol 104 (1) ◽

pp. 003685042110005

Author(s):

Mingnan Cao ◽

Li Wang ◽

Lin Zhang ◽

Jingli Duan

Keyword(s):

Bibliometric Analysis ◽

Research Collaboration ◽

Citation Networks ◽

Publication Trends ◽

Drug Induced ◽

Topic Area ◽

The Past ◽

Black Box Warnings ◽

The Usa ◽

Post Marketing

Drug-induced liver injury (DILI) is one of the common adverse drug reactions and the leading cause of drug development attritions, black box warnings, and post-marketing withdrawals. Current biomarkers are suboptimal in detecting DILI and predicting its outcome. This study aimed to quantitatively and qualitatively investigate the research trends on DILI biomarkers using bibliometric analysis. All relevant publications were extracted from the Web of Science database. An online analysis platform of literature metrology, bibliographic item co-occurrence matrix builder, and CiteSpace software were used to analyze the publication trends. CitNetExplorer was used to construct direct citation networks and VOSviewer was used to analyze the keywords and research hotspots. We found a total of 485 publications related to DILI biomarkers published from 1991 to 2020. Toxicological Sciences had been the most popular journal in this field over the past 30 years. The USA maintained a top position worldwide and provided a pivotal influence, followed by China. Among all the institutions, the University of Liverpool was regarded as a leader for research collaboration. Moreover, Professors Paul B. Watkins and Tsuyoshi Yokoi made great achievements in topic area. We analyzed the citation networks and keywords, therefore identified five and six research hotspot clusters, respectively. We considered the publication information regarding different countries/regions, organizations, authors, journals, et al. by summarizing the literature on DILI biomarkers over the past 30 years. Notably, the subject of DILI biomarkers is an active area of research. In addition, the investigation and discovery of novel promising biomarkers such as microRNAs, keratin18, and bile acids will be future developing hotspots.

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Application of Artificial Intelligence in Food Industry—a Guideline

Food Engineering Reviews ◽

10.1007/s12393-021-09290-z ◽

2021 ◽

Author(s):

Nidhi Rajesh Mavani ◽

Jarinah Mohd Ali ◽

Suhaili Othman ◽

M. A. Hussain ◽

Haslaniza Hashim ◽

...

Keyword(s):

Artificial Intelligence ◽

Intelligent Systems ◽

Food Industry ◽

Near Infrared ◽

Vision System ◽

Electronic Tongue ◽

World Population ◽

Computer Vision System ◽

The Past

AbstractArtificial intelligence (AI) has embodied the recent technology in the food industry over the past few decades due to the rising of food demands in line with the increasing of the world population. The capability of the said intelligent systems in various tasks such as food quality determination, control tools, classification of food, and prediction purposes has intensified their demand in the food industry. Therefore, this paper reviews those diverse applications in comparing their advantages, limitations, and formulations as a guideline for selecting the most appropriate methods in enhancing future AI- and food industry–related developments. Furthermore, the integration of this system with other devices such as electronic nose, electronic tongue, computer vision system, and near infrared spectroscopy (NIR) is also emphasized, all of which will benefit both the industry players and consumers.

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Artificial Intelligence in Education (AIEd): a high-level academic and industry note 2021

AI and Ethics ◽

10.1007/s43681-021-00074-z ◽

2021 ◽

Author(s):

Muhammad Ali Chaudhry ◽

Emre Kazim

Keyword(s):

Artificial Intelligence ◽

Intelligent Tutoring Systems ◽

Policy Makers ◽

Tutoring Systems ◽

Research And Practice ◽

The Past ◽

Artificial Intelligence In Education ◽

Potential Impact ◽

High Level ◽

Contextualized Learning

AbstractIn the past few decades, technology has completely transformed the world around us. Indeed, experts believe that the next big digital transformation in how we live, communicate, work, trade and learn will be driven by Artificial Intelligence (AI) [83]. This paper presents a high-level industrial and academic overview of AI in Education (AIEd). It presents the focus of latest research in AIEd on reducing teachers’ workload, contextualized learning for students, revolutionizing assessments and developments in intelligent tutoring systems. It also discusses the ethical dimension of AIEd and the potential impact of the Covid-19 pandemic on the future of AIEd’s research and practice. The intended readership of this article is policy makers and institutional leaders who are looking for an introductory state of play in AIEd.

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