scholarly journals Human Gaze Assisted Artificial Intelligence: A Review

Author(s):  
Ruohan Zhang ◽  
Akanksha Saran ◽  
Bo Liu ◽  
Yifeng Zhu ◽  
Sihang Guo ◽  
...  

Human gaze reveals a wealth of information about internal cognitive state. Thus, gaze-related research has significantly increased in computer vision, natural language processing, decision learning, and robotics in recent years. We provide a high-level overview of the research efforts in these fields, including collecting human gaze data sets, modeling gaze behaviors, and utilizing gaze information in various applications, with the goal of enhancing communication between these research areas. We discuss future challenges and potential applications that work towards a common goal of human-centered artificial intelligence.

2021 ◽  
Author(s):  
SANGHAMITRA CHOUDHURY ◽  
Shailendra Kumar

<p>The relationship between women, technology manifestation, and likely prospects in the developing world is discussed in this manuscript. Using India as a case study, the paper goes on to discuss how ontology and epistemology views utilised in AI (Artificial Intelligence) and robotics will affect women's prospects in developing countries. Women in developing countries, notably in South Asia, are perceived as doing domestic work and are underrepresented in high-level professions. They are disproportionately underemployed and face prejudice in the workplace. The purpose of this study is to determine if the introduction of AI would exacerbate the already precarious situation of women in the developing world or if it would serve as a liberating force. While studies on the impact of AI on women have been undertaken in developed countries, there has been less research in developing countries. This manuscript attempts to fill that need.</p>


Author(s):  
Fernando Enrique Lopez Martinez ◽  
Edward Rolando Núñez-Valdez

IoT, big data, and artificial intelligence are currently three of the most relevant and trending pieces for innovation and predictive analysis in healthcare. Many healthcare organizations are already working on developing their own home-centric data collection networks and intelligent big data analytics systems based on machine-learning principles. The benefit of using IoT, big data, and artificial intelligence for community and population health is better health outcomes for the population and communities. The new generation of machine-learning algorithms can use large standardized data sets generated in healthcare to improve the effectiveness of public health interventions. A lot of these data come from sensors, devices, electronic health records (EHR), data generated by public health nurses, mobile data, social media, and the internet. This chapter shows a high-level implementation of a complete solution of IoT, big data, and machine learning implemented in the city of Cartagena, Colombia for hypertensive patients by using an eHealth sensor and Amazon Web Services components.


2020 ◽  
Vol 16 (1) ◽  
pp. 39-57 ◽  
Author(s):  
Jens Frankenreiter ◽  
Michael A. Livermore

The digitization of legal texts and advances in artificial intelligence, natural language processing, text mining, network analysis, and machine learning have led to new forms of legal analysis by lawyers and law scholars. This article provides an overview of how computational methods are affecting research across the varied landscape of legal scholarship, from the interpretation of legal texts to the quantitative estimation of causal factors that shape the law. As computational tools continue to penetrate legal scholarship, they allow scholars to gain traction on traditional research questions and may engender entirely new research programs. Already, computational methods have facilitated important contributions in a diverse array of law-related research areas. As these tools continue to advance, and law scholars become more familiar with their potential applications, the impact of computational methods is likely to continue to grow.


Author(s):  
Oloruntoba Samson Abiodun ◽  
Akinode John Lekan

In recent years, there has been massive progress in Artificial Intelligence (AI) with the development of machine learning, deep neural networks, natural language processing, computer vision and robotics. These techniques are now actively being applied in the judiciary with many of the legal service activities currently being delivered by lawyers predicted to be taken over by AI in the coming years. This paper explores the potentials and efficiency of Artificial intelligence (AI) in justice delivery. The paper has two objectives: first to highlight the main applications of AI in justice administrations through some examples of AI tools recently developed; second, to assess the ethical challenges of AI in the judiciary. Artificial Intelligence algorithms are starting to support lawyers, for instance, through artificial intelligence search tools, or to support justice administrations with predictive technologies and business analytics based on the computation of Big Data. Using the concept of Artificial Intelligence (AI), Legal knowledgebased tools may accelerate the service delivery of legal professionals from typical searching of related case journals to extraction of precise information in a customized manner.


2020 ◽  
Vol 10 (18) ◽  
pp. 6428
Author(s):  
Ronan Thenault ◽  
Kevin Kaulanjan ◽  
Thomas Darde ◽  
Nathalie Rioux-Leclercq ◽  
Karim Bensalah ◽  
...  

Artificial Intelligence (AI) is progressively remodeling our daily life. A large amount of information from “big data” now enables machines to perform predictions and improve our healthcare system. AI has the potential to reshape prostate cancer (PCa) management thanks to growing applications in the field. The purpose of this review is to provide a global overview of AI in PCa for urologists, pathologists, radiotherapists, and oncologists to consider future changes in their daily practice. A systematic review was performed, based on PubMed MEDLINE, Google Scholar, and DBLP databases for original studies published in English from January 2009 to January 2019 relevant to PCa, AI, Machine Learning, Artificial Neural Networks, Convolutional Neural Networks, and Natural-Language Processing. Only articles with full text accessible were considered. A total of 1008 articles were reviewed, and 48 articles were included. AI has potential applications in all fields of PCa management: analysis of genetic predispositions, diagnosis in imaging, and pathology to detect PCa or to differentiate between significant and non-significant PCa. AI also applies to PCa treatment, whether surgical intervention or radiotherapy, skills training, or assessment, to improve treatment modalities and outcome prediction. AI in PCa management has the potential to provide a useful role by predicting PCa more accurately, using a multiomic approach and risk-stratifying patients to provide personalized medicine.


Author(s):  
Prakhar Mehrotra

The objective of this chapter is to discuss the integration of advancements made in the field of artificial intelligence into the existing business intelligence tools. Specifically, it discusses how the business intelligence tool can integrate time series analysis, supervised and unsupervised machine learning techniques and natural language processing in it and unlock deeper insights, make predictions, and execute strategic business action from within the tool itself. This chapter also provides a high-level overview of current state of the art AI techniques and provides examples in the realm of business intelligence. The eventual goal of this chapter is to leave readers thinking about what the future of business intelligence would look like and how enterprise can benefit by integrating AI in it.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Loveleen Gaur ◽  
Anam Afaq ◽  
Gurmeet Singh ◽  
Yogesh Kumar Dwivedi

Purpose The hospitality industry experienced an unanticipated challenge from the COVID-19 pandemic. However, research in this area is scarce. Accordingly, this study aims to unfold a three-angled research agenda to intensify the knowledge advancement in the hospitality sector. It proposes a theoretical framework by extending the protection motivation theory (PMT) to explain the guest’s intent to adopt artificial intelligence (AI) and robotics as a protective measure in reaction to COVID-19. Design/methodology/approach The research is centered on outlining the pertinent literature on hospitality management practices and the guest’s transformed behavior during the current crisis. This study intends to identify a research agenda based on investigating hospitality service trends in today’s changing times. Findings The study sets out a research agenda that includes three dimensions as follows: AI and robotics, cleanliness and sanitation and health care and wellness. This study’s findings suggest that AI and robotics may bring out definite research directions at the connection of health crisis and hospitality management, taking into account the COVID-19 crisis. Practical implications The suggested research areas are anticipated to propel the knowledge base and help the hospitality industry retrieve the COVID-19 crisis through digital transformation. AI and robotics are at the cusp of invaluable advancement that can revive the hotels while re-establish guests’ confidence in safe hotel practices. The proposed research areas are likely to impart pragmatic lessons to the hospitality industry to fight against disruptive situations. Originality/value This study stands out to be pioneer research that incorporated AI and robotics to expand the PMT and highlights how behavioral choices during emergencies can bring technological revolution.


2021 ◽  
Author(s):  
Dewey Murdick ◽  
Daniel Chou ◽  
Ryan Fedasiuk ◽  
Emily Weinstein

New analytic tools are used in this data brief to explore the public artificial intelligence (AI) research portfolio of China’s security forces. The methods contextualize Chinese-language scholarly papers that claim a direct working affiliation with components of the Ministry of Public Security, People's Armed Police Force, and People’s Liberation Army. The authors review potential uses of computer vision, robotics, natural language processing and general AI research.


2021 ◽  
Vol 22 (5) ◽  
pp. 223-231
Author(s):  
Jeong Yeop Ryu ◽  
Ho Yun Chung ◽  
Kang Young Choi

The field of artificial intelligence (AI) is rapidly advancing, and AI models are increasingly applied in the medical field, especially in medical imaging, pathology, natural language processing, and biosignal analysis. On the basis of these advances, telemedicine, which allows people to receive medical services outside of hospitals or clinics, is also developing in many countries. The mechanisms of deep learning used in medical AI include convolutional neural networks, residual neural networks, and generative adversarial networks. Herein, we investigate the possibility of using these AI methods in the field of craniofacial surgery, with potential applications including craniofacial trauma, congenital anomalies, and cosmetic surgery.


2021 ◽  
Author(s):  
SANGHAMITRA CHOUDHURY ◽  
Shailendra Kumar

<p>The relationship between women, technology manifestation, and likely prospects in the developing world is discussed in this manuscript. Using India as a case study, the paper goes on to discuss how ontology and epistemology views utilised in AI (Artificial Intelligence) and robotics will affect women's prospects in developing countries. Women in developing countries, notably in South Asia, are perceived as doing domestic work and are underrepresented in high-level professions. They are disproportionately underemployed and face prejudice in the workplace. The purpose of this study is to determine if the introduction of AI would exacerbate the already precarious situation of women in the developing world or if it would serve as a liberating force. While studies on the impact of AI on women have been undertaken in developed countries, there has been less research in developing countries. This manuscript attempts to fill that need.</p>


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