Sustainability

Editorial

3 pages, 180 KiB

Open AccessEditorial

Artificial Intelligence (AI) and Sustainable Development Goals (SDGs): Exploring the Impact of AI on Politics and Society

by Anna Visvizi

Sustainability 2022, 14(3), 1730; https://doi.org/10.3390/su14031730 - 2 Feb 2022

Cited by 14 | Viewed by 4347

Abstract

In popular discourse, artificial intelligence (AI) has turned into one of the most inexplicable issues It has turned into an artifact that people do not dare to question [...] Full article

(This article belongs to the Special Issue Artificial Intelligence (AI) and Sustainable Development Goals (SDGs): Exploring the Impact of AI on Politics and Society)

Research

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17 pages, 2203 KiB

Open AccessArticle

Turning Crisis into Opportunities: How a Firm Can Enrich Its Business Operations Using Artificial Intelligence and Big Data during COVID-19

by Yasheng Chen and Mohammad Islam Biswas

Sustainability 2021, 13(22), 12656; https://doi.org/10.3390/su132212656 - 16 Nov 2021

Cited by 18 | Viewed by 8828

Abstract

The COVID-19 pandemic has severe impacts on global health and social and economic safety. The present study discusses strategies for turning the COVID-19 crisis into opportunities to use artificial intelligence (AI) and big data in business operations. Based on the shared experience and [...] Read more.

The COVID-19 pandemic has severe impacts on global health and social and economic safety. The present study discusses strategies for turning the COVID-19 crisis into opportunities to use artificial intelligence (AI) and big data in business operations. Based on the shared experience and theoretical ground, researchers identified five major business challenges during the COVID-19 pandemic: production and supply-chain disruption, appropriate business model selection, inventory management, budget planning, and workforce management. These five challenges were outlined with eight business cases as examples of companies that had already utilized AI and big data for their business operations during the COVID-19 pandemic. The outcomes of this study provide valuable insights into contemporary social science research and business management with AI and big data applications as a business response to any crisis in the future. Full article

(This article belongs to the Special Issue Artificial Intelligence (AI) and Sustainable Development Goals (SDGs): Exploring the Impact of AI on Politics and Society)

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19 pages, 1250 KiB

Open AccessArticle

AI in Context and the Sustainable Development Goals: Factoring in the Unsustainability of the Sociotechnical System

by Henrik Skaug Sætra

Sustainability 2021, 13(4), 1738; https://doi.org/10.3390/su13041738 - 5 Feb 2021

Cited by 52 | Viewed by 12175

Abstract

Artificial intelligence (AI) is associated with both positive and negative impacts on both people and planet, and much attention is currently devoted to analyzing and evaluating these impacts. In 2015, the UN set 17 Sustainable Development Goals (SDGs), consisting of environmental, social, and [...] Read more.

Artificial intelligence (AI) is associated with both positive and negative impacts on both people and planet, and much attention is currently devoted to analyzing and evaluating these impacts. In 2015, the UN set 17 Sustainable Development Goals (SDGs), consisting of environmental, social, and economic goals. This article shows how the SDGs provide a novel and useful framework for analyzing and categorizing the benefits and harms of AI. AI is here considered in context as part of a sociotechnical system consisting of larger structures and economic and political systems, rather than as a simple tool that can be analyzed in isolation. This article distinguishes between direct and indirect effects of AI and divides the SDGs into five groups based on the kinds of impact AI has on them. While AI has great positive potential, it is also intimately linked to nonuniversal access to increasingly large data sets and the computing infrastructure required to make use of them. As a handful of nations and companies control the development and application of AI, this raises important questions regarding the potential negative implications of AI on the SDGs. The conceptual framework here presented helps structure the analysis of which of the SDGs AI might be useful in attaining and which goals are threatened by the increased use of AI. Full article

(This article belongs to the Special Issue Artificial Intelligence (AI) and Sustainable Development Goals (SDGs): Exploring the Impact of AI on Politics and Society)

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16 pages, 548 KiB

Open AccessArticle

Poverty Classification Using Machine Learning: The Case of Jordan

by Adham Alsharkawi, Mohammad Al-Fetyani, Maha Dawas, Heba Saadeh and Musa Alyaman

Sustainability 2021, 13(3), 1412; https://doi.org/10.3390/su13031412 - 29 Jan 2021

Cited by 30 | Viewed by 6002

Abstract

The scope of this paper is focused on the multidimensional poverty problem in Jordan. Household expenditure and income surveys provide data that are used for identifying and measuring the poverty status of Jordanian households. However, carrying out such surveys is hard, time consuming, [...] Read more.

The scope of this paper is focused on the multidimensional poverty problem in Jordan. Household expenditure and income surveys provide data that are used for identifying and measuring the poverty status of Jordanian households. However, carrying out such surveys is hard, time consuming, and expensive. Machine learning could revolutionize this process. The contribution of this work is the proposal of an original machine learning approach to assess and monitor the poverty status of Jordanian households. This approach takes into account all the household expenditure and income surveys that took place since the early beginning of the new millennium. This approach is accurate, inexpensive, and makes poverty identification cheaper and much closer to real-time. Data preprocessing and handling imbalanced data are major parts of this work. Various machine learning classification models are applied. The LightGBM algorithm has achieved the best performance with 81% F1-Score. The final machine learning classification model could transform efforts to track and target poverty across the country. This work demonstrates how powerful and versatile machine learning can be, and hence, it promotes for adoption across many domains in both the private sector and government. Full article

(This article belongs to the Special Issue Artificial Intelligence (AI) and Sustainable Development Goals (SDGs): Exploring the Impact of AI on Politics and Society)

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16 pages, 5279 KiB

Open AccessArticle

Cultural Identity Distance Computation through Artificial Intelligence as an Analysis Tool of the Amazon Indigenous People. A Case Study in the Waorani Community

by Aldrin Marcel Espín-León, Antonio Jimeno-Morenilla, María Luisa Pertegal-Felices and Jorge Azorín-López

Sustainability 2020, 12(22), 9513; https://doi.org/10.3390/su12229513 - 15 Nov 2020

Cited by 4 | Viewed by 3478

Abstract

Cultural identity is a complex concept that includes subjective factors such as ideology, family knowledge, customs, language, and acquired skills, among others. Measuring culture involves a significant level of difficulty, since its study and scope differ from the point of view, the time [...] Read more.

Cultural identity is a complex concept that includes subjective factors such as ideology, family knowledge, customs, language, and acquired skills, among others. Measuring culture involves a significant level of difficulty, since its study and scope differ from the point of view, the time and the place where the studies are carried out. In the Amazon, indigenous communities are in an accelerated process of acculturation that results in a loss of cultural identity that is not easy to quantify. This paper presents a method to measure the cultural distance between individuals or between groups of people using Artificial Intelligence techniques. The distance between individuals is calculated as the distance of the minimum path in the self-organizing map using Dijkstra’s algorithm. The experiments have been carried out to measure the cultural identity of indigenous people in the Waorani Amazon community and compares them with people living in cities who have a modern identity. The results showed that the communities are still distant in terms of identity from the westernised cities around them, although there are already factors where the distances are minimal concerning these cities. In any case, the method makes it possible to quantify the state of acculturation. This quantification can help the authorities to monitor these communities and take political decisions that will enable them to preserve their cultural identity. Full article

(This article belongs to the Special Issue Artificial Intelligence (AI) and Sustainable Development Goals (SDGs): Exploring the Impact of AI on Politics and Society)

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16 pages, 2071 KiB

Open AccessArticle

Design Pattern Elicitation Framework for Proof of Integrity in Blockchain Applications

by Kawther Saeedi, Monirah Dakilallah Almalki, Dania Aljeaid, Anna Visvizi and Muhammad Ahtisham Aslam

Sustainability 2020, 12(20), 8404; https://doi.org/10.3390/su12208404 - 13 Oct 2020

Cited by 5 | Viewed by 2252

Abstract

An emerging technology with a secure and a decentralized nature, blockchain has the potential to transform conventional practices in an efficient and dynamic manner. However, migrating to blockchain can be challenging due to the complexity of its infrastructure and processes. The complexity of [...] Read more.

An emerging technology with a secure and a decentralized nature, blockchain has the potential to transform conventional practices in an efficient and dynamic manner. However, migrating to blockchain can be challenging due to the complexity of its infrastructure and processes. The complexity of building applications on blockchain has been highlighted by many studies, thus stressing the need to investigate practical solutions further. A commonly known software engineering concept, software design pattern contributes to the acceleration of software development. It offers a holistic reusable solution for commonly occurring problems in a given context. It helps to identify problems that occur repetitively and describes best practices to address them. The present study is one of the first investigations to inquire into design patterns for blockchain application. Seeking to reduce the complexity in understanding and building applications on blockchain, this paper identifies a design pattern elicitation framework from similar blockchain applications. Next, it provides a demonstration of the Proof of Integrity (PoI) pattern elicited from two different applications on the blockchain. The applicability of the pattern is evaluated by building a blockchain application to verify the integrity of the academic certificates and by explaining how this integrity has been achieved empirically. Full article

(This article belongs to the Special Issue Artificial Intelligence (AI) and Sustainable Development Goals (SDGs): Exploring the Impact of AI on Politics and Society)

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27 pages, 1437 KiB

Open AccessArticle

Impact of Artificial Intelligence Research on Politics of the European Union Member States: The Case Study of Portugal

by João Reis, Paula Santo and Nuno Melão

Sustainability 2020, 12(17), 6708; https://doi.org/10.3390/su12176708 - 19 Aug 2020

Cited by 16 | Viewed by 5776

Abstract

Currently, artificial intelligence (AI) is at the center of academic and public debate. However, its implications on politics remain little understood. To understand the impact of the AI phenomenon on politics of the European Union (EU), we have carried out qualitative multimethod research [...] Read more.

Currently, artificial intelligence (AI) is at the center of academic and public debate. However, its implications on politics remain little understood. To understand the impact of the AI phenomenon on politics of the European Union (EU), we have carried out qualitative multimethod research by performing a systematic literature review and a case study. The first method was performed according to the preferred reporting items for systematic reviews and meta-analyses (PRISMA), in order to report the state-of-the-art in the existing literature and explore the most relevant research areas. The second method contained contributions from experts in data science and AI of the Portuguese scientific community. The results showed that solutions such as intelligent decision support systems are improving the political decision-making process and impacting the Portuguese society at local, regional, and national levels. We also found that practitioners and scientists are currently shifting their interests from environmental and biological sciences to healthcare services, which is bringing new challenges in terms of protecting patient/citizen data and growing concerns about handling of critical information. Future research may focus on comparative studies with other EU States to obtain a comprehensive and holistic understanding of the AI phenomenon. Full article

(This article belongs to the Special Issue Artificial Intelligence (AI) and Sustainable Development Goals (SDGs): Exploring the Impact of AI on Politics and Society)

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19 pages, 4889 KiB

Open AccessArticle

Beware Thy Bias: Scaling Mobile Phone Data to Measure Traffic Intensities

by Johan Meppelink, Jens Van Langen, Arno Siebes and Marco Spruit

Sustainability 2020, 12(9), 3631; https://doi.org/10.3390/su12093631 - 1 May 2020

Cited by 4 | Viewed by 2777

Abstract

Mobile phone data are a novel data source to generate mobility information from Call Detail Records (CDRs). Although mobile phone data can provide us with valuable insights in human mobility, they often show a biased picture of the traveling population. This research, therefore, [...] Read more.

Mobile phone data are a novel data source to generate mobility information from Call Detail Records (CDRs). Although mobile phone data can provide us with valuable insights in human mobility, they often show a biased picture of the traveling population. This research, therefore, focuses on correcting for these biases and suggests a new method to scale mobile phone data to the true traveling population. Moreover, the scaled mobile phone data will be compared to roadside measurements at 100 different locations on Dutch highways. We infer vehicle trips from the mobile phone data and compare the scaled counts with roadside measurements. The results are evaluated for October 2015. The proposed scaling method shows very promising results with near identical vehicle counts from both data sources in terms of monthly, weekly, and hourly vehicle counts. This indicates the scaling method, in combination with mobile phone data, is able to correctly measure traffic intensities on highways, and thereby able to anticipate calibrated human mobility behaviour. Nevertheless, there are still some discrepancies—for one, during weekends—calling for more research. This paper serves researchers in the field of mobile phone data by providing a proven method to scale the sample to the population, a crucial step in creating unbiased mobility information. Full article

(This article belongs to the Special Issue Artificial Intelligence (AI) and Sustainable Development Goals (SDGs): Exploring the Impact of AI on Politics and Society)

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