Pandemic Management Using Artificial Intelligence-Based Safety Measures

2021 ◽  
pp. 86-110
Author(s):  
Megha Nain ◽  
Shilpa Sharma ◽  
Sandeep Chaurasia
Keyword(s):  
Artificial Intelligence ◽  
Language Processing ◽  
Virus Disease ◽  
Health Conditions ◽  
Safety Measures ◽  
Research Areas ◽  
Worldwide Population ◽  
Safety And Health ◽  
The Impact

The pandemic corona virus disease (COVID-19) caused by the virus ‘SARS-CoV-2' continues affecting the health and affluence of the worldwide population. The role of artificial intelligence in improving safety and health conditions has been studied in the chapter. The various fields of artificial intelligence such as machine learning, computer vision, deep learning, and natural language processing are contributing to almost every field ranging from healthcare, agriculture, automotive, astronomy, and many others. For overcoming a global outbreak such as COVID-19, conventional approaches are not feasible enough, and therefore the requirement for the more robust and automated techniques for making predictions in advance is essential. The vision of this chapter is to assess and survey the impact of artificial intelligence-based approaches in the management of pandemics and recommend procedures for the enhancement of the currently used techniques along with the imminent research areas in artificial intelligence for controlling pandemics.

scholarly journals Rho AI – Leveraging artificial intelligence to address climate change: Financing, implementation and ethics

2021 ◽  
pp. 204388692096178
Author(s):  
Isabel Fischer ◽  
Claire Beswick ◽  
Sue Newell
Keyword(s):  
Climate Change ◽  
Artificial Intelligence ◽  
Language Processing ◽  
Data Science ◽  
Business Models ◽  
Climate Impact ◽  
Strategic Choices ◽  
Business In Society ◽  
The Impact

The case focusses on Rho AI, a data science firm, and its attempt to leverage artificial intelligence to encourage environmental, social and governance investments to limit the impact of climate change. Rho AI’s proposed open-source artificial intelligence tool integrates automated web scraping technology and machine learning with natural language processing. The aim of the tool is to enable investors to evaluate the climate impact of companies and to use this evaluation as a basis for making investments in companies. The case study allows for students to gain an insight into some of the strategic choices that need to be considered when developing an artificial intelligence–based tool. Students will be able to explore the role of ethics in decision-making related to artificial intelligence, while familiarising themselves with key technical terminology and possible business models. The case encourages students to see beyond the technical granularities and to consider the multi-faceted, wider corporate and societal issues and priorities. This case contributes to students recognising that business is not conducted in a vacuum and enhances students’ understanding of the role of business in society during new developments triggered by digital technology.

scholarly journals The Role of Artificial Intelligence in Fighting the COVID-19 Pandemic

2021 ◽  
Author(s):  
Francesco Piccialli ◽  
Vincenzo Schiano di Cola ◽  
Fabio Giampaolo ◽  
Salvatore Cuomo
Keyword(s):  
Artificial Intelligence ◽  
Clinical Trials ◽  
Digital Transformation ◽  
Daily Activities ◽  
Commercial Vehicles ◽  
Human Skills ◽  
To Come ◽  
Complex Scenario ◽  
The Impact

AbstractThe first few months of 2020 have profoundly changed the way we live our lives and carry out our daily activities. Although the widespread use of futuristic robotaxis and self-driving commercial vehicles has not yet become a reality, the COVID-19 pandemic has dramatically accelerated the adoption of Artificial Intelligence (AI) in different fields. We have witnessed the equivalent of two years of digital transformation compressed into just a few months. Whether it is in tracing epidemiological peaks or in transacting contactless payments, the impact of these developments has been almost immediate, and a window has opened up on what is to come. Here we analyze and discuss how AI can support us in facing the ongoing pandemic. Despite the numerous and undeniable contributions of AI, clinical trials and human skills are still required. Even if different strategies have been developed in different states worldwide, the fight against the pandemic seems to have found everywhere a valuable ally in AI, a global and open-source tool capable of providing assistance in this health emergency. A careful AI application would enable us to operate within this complex scenario involving healthcare, society and research.

Leveraging Twitter Using Artificial Intelligence to Explore Mental Health Insights in the UK During the COVID-19 Pandemic (Preprint)

2021 ◽  
Author(s):  
Christopher Marshall ◽  
Kate Lanyi ◽  
Rhiannon Green ◽  
Georgie Wilkins ◽  
Fiona Pearson ◽  
...  
Keyword(s):  
Mental Health ◽  
Artificial Intelligence ◽  
Language Processing ◽  
Mental Health Problems ◽  
Well Being ◽  
Research Activity ◽  
Health Crisis ◽  
Key Topics ◽  
The Uk ◽  
The Impact

BACKGROUND There is increasing need to explore the value of soft-intelligence, leveraged using the latest artificial intelligence (AI) and natural language processing (NLP) techniques, as a source of analysed evidence to support public health research activity and decision-making. OBJECTIVE The aim of this study was to further explore the value of soft-intelligence analysed using AI through a case study, which examined a large collection of UK tweets relating to mental health during the COVID-19 pandemic. METHODS A search strategy comprising a list of terms related to mental health, COVID-19, and lockdown restrictions was developed to prospectively collate relevant tweets via Twitter’s advanced search application programming interface over a 24-week period. We deployed a specialist NLP platform to explore tweet frequency and sentiment across the UK and identify key topics of discussion. A series of keyword filters were used to clean the initial data retrieved and also set up to track specific mental health problems. Qualitative document analysis was carried out to further explore and expand upon the results generated by the NLP platform. All collated tweets were anonymised RESULTS We identified and analysed 286,902 tweets posted from UK user accounts from 23 July 2020 to 6 January 2021. The average sentiment score was 50%, suggesting overall neutral sentiment across all tweets over the study period. Major fluctuations in volume and sentiment appeared to coincide with key changes to any local and/or national social-distancing measures. Tweets around mental health were polarising, discussed with both positive and negative sentiment. Key topics of consistent discussion over the study period included the impact of the pandemic on people’s mental health (both positively and negatively), fear and anxiety over lockdowns, and anger and mistrust toward the government. CONCLUSIONS Through the primary use of an AI-based NLP platform, we were able to rapidly mine and analyse emerging health-related insights from UK tweets into how the pandemic may be impacting people’s mental health and well-being. This type of real-time analysed evidence could act as a useful intelligence source that agencies, local leaders, and health care decision makers can potentially draw from, particularly during a health crisis.

scholarly journals An analytical survey on the role of machine learning algorithms in case of intrusion detection

2020 ◽  
Vol 5 (19) ◽  
pp. 32-35
Author(s):  
Anand Vijay ◽  
Kailash Patidar ◽  
Manoj Yadav ◽  
Rishi Kushwah
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Intrusion Detection ◽  
Intrusion Detection System ◽  
Detection System ◽  
Learning Algorithms ◽  
Machine Learning Algorithms ◽  
Handling Mechanism ◽  
The Impact

In this paper an analytical survey on the role of machine learning algorithms in case of intrusion detection has been presented and discussed. This paper shows the analytical aspects in the development of efficient intrusion detection system (IDS). The related study for the development of this system has been presented in terms of computational methods. The discussed methods are data mining, artificial intelligence and machine learning. It has been discussed along with the attack parameters and attack types. This paper also elaborates the impact of different attack and handling mechanism based on the previous papers.

scholarly journals Devices for Continuous Recording of "Integral ECG" for Determining Vital Physiological Indicators of a Person's State and Their use in Bio Cybernetic Complexes

2020 ◽  
Author(s):  
Bogatyrev Evgeniy ◽  
Kodkin Vladimir
Keyword(s):  
Artificial Intelligence ◽  
Information Systems ◽  
Physical Nature ◽  
Continuous Recording ◽  
Accurate Information ◽  
Physiological Indicators ◽  
Research Areas ◽  
The Creation

One of the rapidly developing research areas is the creation of systems. which are commonly referred to as cyberphysical complexes. In such systems, devices and complexes interact with a completely different physical nature. The role of a person in such systems usually consists in the formation of final tasks for “artificial intelligence” and executive mechanisms. The functioning of actuators is controlled by accurate information systems.

scholarly journals Human Gaze Assisted Artificial Intelligence: A Review

2020 ◽  
Author(s):  
Ruohan Zhang ◽  
Akanksha Saran ◽  
Bo Liu ◽  
Yifeng Zhu ◽  
Sihang Guo ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Language Processing ◽  
Cognitive State ◽  
Data Sets ◽  
Common Goal ◽  
Research Areas ◽  
Future Challenges ◽  
Potential Applications ◽  
High Level ◽  
And Robotics

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.

The Impact of Artificial Intelligence and Virtual Personal Assistants on Marketing

2018 ◽  
pp. 5748-5756 ◽  
Author(s):  
Christina L. McDowell Marinchak ◽  
Edward Forrest ◽  
Bogdan Hoanca
Keyword(s):  
Artificial Intelligence ◽  
Customer Satisfaction ◽  
Security Requirements ◽  
Marketing Effort ◽  
Ethical Implications ◽  
Personal Assistants ◽  
Customer Trust ◽  
The Impact

This entry will review the state of the art in AI, with a particular focus on applications in marketing. Based on the current capabilities of AI in marketing, the author's explore the new rules of engagement. Rather than simply targeting consumers, the marketing effort will also be directed at the algorithms controlling the consumers' virtual personal assistants (VPAs). Rather than exploiting human desires and weakness, marketing will need to focus on meeting the user's actual needs. The level of customer satisfaction will be even more critical as marketing will need to focus on establishing and maintaining a reputation in competition with those of similar offerings in the marketplace. This entry concludes with thoughts on the long-term implications, exploring the role of customer trust in the adoption of AI agents, the security requirements for agents and the ethical implications of access to such agents.

Data Security for Connected Governments and Organisations

2021 ◽  
pp. 229-251
Author(s):  
Heru Susanto ◽  
Leu Fang Yie ◽  
Didi Rosiyadi ◽  
Akbari Indra Basuki ◽  
Desi Setiana
Keyword(s):  
Artificial Intelligence ◽  
Early Warning ◽  
Data Security ◽  
Data Privacy ◽  
Government Agencies ◽  
Security Measures ◽  
Security Issues ◽  
The Impact ◽  
Distributed Technologies

Digital ecosystems have grown rapidly over the years, and governments are investing in digital provision for their processes and services. Despite the advantages of distributed technologies, there are many security issues as well that result in breaches of data privacy with serious impact including legal and reputational implications. To deal with such threats, government agencies need to thoughtfully improve their security defences to protect data and systems by using automation and artificial intelligence (AI), as well as easing the data security measures including early warning of threats and detection. This study provides a comprehensive view of AI and automaton to highlight challenges and issues concerning data security and suggests steps to combat the issues. The authors demonstrate the role of AI-driven security tools and automation to mitigate the impact of data breaches to also propose recommendations for government agencies to enhance their data security protection.

scholarly journals COVID-19: US federal accountability for entry, spread, and inequities—lessons for the future

2020 ◽  
Vol 35 (11) ◽  
pp. 995-1006 ◽  
Author(s):  
William P. Hanage ◽  
Christian Testa ◽  
Jarvis T. Chen ◽  
Letitia Davis ◽  
Elise Pechter ◽  
...  
Keyword(s):  
Occupational Safety ◽  
The United States ◽  
Health Administration ◽  
Worldwide Population ◽  
Safety And Health ◽  
The Us ◽  
Working Age ◽  
Community Transmission ◽  
Race Ethnicity ◽  
The Impact

AbstractThe United States (US) has been among those nations most severely affected by the first—and subsequent—phases of the pandemic of COVID-19, the disease caused by SARS-CoV-2. With only 4% of the worldwide population, the US has seen about 22% of COVID-19 deaths. Despite formidable advantages in resources and expertise, presently the per capita mortality rate is over 585/million, respectively 2.4 and 5 times higher compared to Canada and Germany. As we enter Fall 2020, the US is enduring ongoing outbreaks across large regions of the country. Moreover, within the US, an early and persistent feature of the pandemic has been the disproportionate impact on populations already made vulnerable by racism and dangerous jobs, inadequate wages, and unaffordable housing, and this is true for both the headline public health threat and the additional disastrous economic impacts. In this article we assess the impact of missteps by the Federal Government in three specific areas: the introduction of the virus to the US and the establishment of community transmission; the lack of national COVID-19 workplace standards and enforcement, and lack of personal protective equipment (PPE) for workplaces as represented by complaints to the Occupational Safety and Health Administration (OSHA) which we find are correlated with deaths 16 days later (ρ = 0.83); and the total excess deaths in 2020 to date already total more than 230,000, while COVID-19 mortality rates exhibit severe—and rising—inequities in race/ethnicity, including among working age adults.

Computational Methods in Legal Analysis

2020 ◽  
Vol 16 (1) ◽  
pp. 39-57 ◽  
Author(s):  
Jens Frankenreiter ◽  
Michael A. Livermore
Keyword(s):  
Computational Methods ◽  
Language Processing ◽  
Quantitative Estimation ◽  
Legal Analysis ◽  
Legal Scholarship ◽  
Research Areas ◽  
Legal Texts ◽  
Potential Applications ◽  
New Research ◽  
The Impact

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.

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