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Special Issue "AI and Interaction Technologies for Social Sustainability"

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A special issue of Sustainability (ISSN 2071-1050).

Deadline for manuscript submissions: closed (15 June 2022) | Viewed by 24085

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Special Issue Editors

Dr. Marwa Mahmoud

E-Mail Website
Guest Editor

Department of Computer Science and Technology, University of Cambridge, Cambridge CB2 1TN, UK
Interests: computer vision; affective computing; social signal processing; pattern recognition; machine learning; multimodal representation learning; behavioural analytics; human behaviour understanding

Dr. Maria Perez-Ortiz

E-Mail Website
Guest Editor

Artificial Intelligence Center, University College London, London WC1E 6BT, UK
Interests: machine learning; image processing; recommender systems; AI in education; environmental sustainability; biomedicine

Special Issue Information

Dear Colleagues,

Over the past decade, technology and interactive systems are becoming an integral part of our society. Artificial intelligence (AI) is becoming intertwined in our daily life and progressively having a wider impact on many sectors. It is necessary to assess innovation’s effect on the achievement of the sustainable development goals.

Although sustainable goals are often not directly considered the main objective when developing and creating new AI models and computer interaction interfaces, many applications of these technologies, such as in healthcare, smart cities, education and welfare, will have a powerful and direct impact on people’s lives and could play a crucial role as catalysts in developing a sustainable society.

This Special Issue generally aims to i) synthesize how AI might change (and is already changing) our society, ii) serve as a display of the potential of intelligent and interactive technologies for ensuring a thriving and sustainable society, as well as iii) provide a synopsis of the developments needed in order to leverage this sustainable technological revolution on a global scale.

Dr. Marwa Mahmoud
Dr. Maria Perez-Ortiz
Guest Editors

Manuscript Submission Information

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

AI for social good
human–computer interaction for social sustainability
fair and responsible AI
social signal processing
AI in low resource settings and global challenges
transparent and accountable machine learning
affective computing
AI in biomedicine and healthcare
intelligent interactive systems in education
interactive and sustainable smart cities

Published Papers (6 papers)

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Research

25 pages, 1172 KiB

Open AccessArticle

Power to the Learner: Towards Human-Intuitive and Integrative Recommendations with Open Educational Resources

and

Sustainability 2022, 14(18), 11682; https://doi.org/10.3390/su141811682 - 17 Sep 2022

Cited by 5 | Viewed by 1874

Abstract

Educational recommenders have received much less attention in comparison with e-commerce- and entertainment-related recommenders, even though efficient intelligent tutors could have potential to improve learning gains and enable advances in education that are essential to achieving the world’s sustainability agenda. Through this work, we make foundational advances towards building a state-aware, integrative educational recommender. The proposed recommender accounts for the learners’ interests and knowledge at the same time as content novelty and popularity, with the end goal of improving predictions of learner engagement in a lifelong-learning educational video platform. Towards achieving this goal, we (i) formulate and evaluate multiple probabilistic graphical models to capture learner interest; (ii) identify and experiment with multiple probabilistic and ensemble approaches to combine interest, novelty, and knowledge representations together; and (iii) identify and experiment with different hybrid recommender approaches to fuse population-based engagement prediction to address the cold-start problem, i.e., the scarcity of data in the early stages of a user session, a common challenge in recommendation systems. Our experiments with an in-the-wild interaction dataset of more than 20,000 learners show clear performance advantages by integrating content popularity, learner interest, novelty, and knowledge aspects in an informational recommender system, while preserving scalability. Our recommendation system integrates a human-intuitive representation at its core, and we argue that this transparency will prove important in efforts to give agency to the learner in interacting, collaborating, and governing their own educational algorithms. Full article

(This article belongs to the Special Issue AI and Interaction Technologies for Social Sustainability)

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11 pages, 934 KiB

Open AccessArticle

A Patch-Based CNN Built on the VGG-16 Architecture for Real-Time Facial Liveness Detection

Dewan Ahmed Muhtasim

Monirul Islam Pavel

and

Siok Yee Tan

Sustainability 2022, 14(16), 10024; https://doi.org/10.3390/su141610024 - 12 Aug 2022

Cited by 3 | Viewed by 2174

Abstract

Facial recognition is a prevalent method for biometric authentication that is utilized in a variety of software applications. This technique is susceptible to spoofing attacks, in which an imposter gains access to a system by presenting the image of a legitimate user to the sensor, hence increasing the risks to social security. Consequently, facial liveness detection has become an essential step in the authentication process prior to granting access to users. In this study, we developed a patch-based convolutional neural network (CNN) with a deep component for facial liveness detection for security enhancement, which was based on the VGG-16 architecture. The approach was tested using two datasets: REPLAY-ATTACK and CASIA-FASD. According to the results, our approach produced the best results for the CASIA-FASD dataset, with reduced HTER and EER scores of 0.71% and 0.67%, respectively. The proposed approach also produced consistent results for the REPLAY-ATTACK dataset while maintaining balanced and low HTER and EER values of 1.52% and 0.30%, respectively. By adopting the suggested enhanced liveness detection, architecture that is based on artificial intelligence could make current biometric-based security systems more secure and sustainable while also reducing the risks to social security. Full article

(This article belongs to the Special Issue AI and Interaction Technologies for Social Sustainability)

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22 pages, 3130 KiB

Open AccessArticle

Human-Centered Artificial Intelligence: The Superlative Approach to Achieve Sustainable Development Goals in the Fourth Industrial Revolution

David Mhlanga

Sustainability 2022, 14(13), 7804; https://doi.org/10.3390/su14137804 - 27 Jun 2022

Cited by 14 | Viewed by 5704

Abstract

Artificial intelligence (AI) is currently being developed by large corporations, and governments all over the world are yearning for it. AI isn’t a futuristic concept; it is already here, and it is being implemented in a range of industries. Finance, national security, health care, criminal justice, transportation, and smart cities are all examples of this. There are countless examples of AI having a substantial impact on the world and complementing human abilities. However, due to the immense societal ramifications of these technologies, AI is on the verge of disrupting a host of industries, so the technique by which AI systems are created must be better understood. The goal of the study was to look at what it meant to be human-centred, how to create human-centred AI, and what considerations should be made for human-centred AI to achieve sustainability and the SDGs. Using a systematic literature review technique, the study discovered that a human-centred AI strategy strives to create and implement AI systems in ways that benefit mankind and serve their interests. The study also found that a human-in-the-loop concept should be used to develop procedures for creating human-centred AI, as well as other initiatives, such as the promotion of AI accountability, encouraging businesses to use autonomy wisely, to motivate businesses to be aware of human and algorithmic biases, to ensure that businesses prioritize customers, and form multicultural teams to tackle AI research. The study concluded with policy recommendations for human-centred AI to help accomplish the SDGs, including expanding government AI investments, addressing data and algorithm biases, and resolving data access issues, among other things. Full article

(This article belongs to the Special Issue AI and Interaction Technologies for Social Sustainability)

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17 pages, 497 KiB

Open AccessArticle

Use of Artificial Intelligence in Smart Cities for Smart Decision-Making: A Social Innovation Perspective

Syed Asad A. Bokhari

and

Seunghwan Myeong

Sustainability 2022, 14(2), 620; https://doi.org/10.3390/su14020620 - 06 Jan 2022

Cited by 33 | Viewed by 6260

Abstract

The goal of this study is to investigate the direct and indirect relationships that exist between artificial intelligence (AI), social innovation (SI), and smart decision-making (SDM). This study used a survey design and collected cross-sectional data from South Korea and Pakistan using survey questionnaires. Four hundred sixty respondents from the public and private sectors were obtained and empirically analyzed using SPSS multiple regression. The study discovered a strong and positive mediating effect of SI between the relationship of AI and SDM, as predicted. Previous researchers have investigated some of the factors that influence the decision-making process. This study adds to the social science literature by examining the impact of a mediating factor on decision-making. The findings of this study will contribute to the local government in building smart cities such that the factor of social innovations should be involved in the decision-making process because smart decision-making would share such collected data with entrepreneurs, businesses, and industries and would benefit society and all relevant stakeholders, including such social innovators. Full article

(This article belongs to the Special Issue AI and Interaction Technologies for Social Sustainability)

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19 pages, 456 KiB

Open AccessArticle

Towards Social Identity in Socio-Cognitive Agents

Diogo Rato

and

Rui Prada

Sustainability 2021, 13(20), 11390; https://doi.org/10.3390/su132011390 - 15 Oct 2021

Cited by 7 | Viewed by 1453

Abstract

Current architectures for social agents are designed around some specific units of social behavior that address particular challenges, such as modeling beliefs and motivations, establishing social relationships, or understanding group memberships. Although their performance might be adequate for controlled environments, deploying these agents in the wild is difficult. Moreover, the increasing demand for autonomous agents capable of living alongside humans calls for the design of more robust social agents that can cope with diverse social situations. We believe that to design such agents, their sociality and cognition should be conceived as one. This includes creating mechanisms for constructing social reality as an interpretation of the physical world with social meanings and selective deployment of cognitive resources adequate to the situation. We identify several design principles that should be considered while designing agent architectures for socio-cognitive systems. Taking these remarks into account, we propose a socio-cognitive agent model based on the concept of cognitive social frames that allow the adaptation of an agent’s cognition based on its interpretation of its surroundings, its social context. Our approach supports an agent’s reasoning about other social actors and its relationship with them. Cognitive social frames can be built around social groups, and form the basis for social group dynamics mechanisms and construct of social identity. Full article

(This article belongs to the Special Issue AI and Interaction Technologies for Social Sustainability)

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25 pages, 1954 KiB

Open AccessArticle

Ethics of Smart Cities: Towards Value-Sensitive Design and Co-Evolving City Life

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Sustainability 2021, 13(20), 11162; https://doi.org/10.3390/su132011162 - 09 Oct 2021

Cited by 20 | Viewed by 4721

Abstract

The digital revolution has brought about many societal changes such as the creation of “smart cities”. The smart city concept has changed the urban ecosystem by embedding digital technologies in the city fabric to enhance the quality of life of its inhabitants. However, it has also led to some pressing issues and challenges related to data, privacy, ethics inclusion, and fairness. While the initial concept of smart cities was largely technology- and data-driven, focused on the automation of traffic, logistics and processes, this concept is currently being replaced by technology-enabled, human-centred solutions. However, this is not the end of the development, as there is now a big trend towards “design for values”. In this paper, we point out how a value-sensitive design approach could promote a more sustainable pathway of cities that better serves people and nature. Such “value-sensitive design” will have to take ethics, law and culture on board. We discuss how organising the digital world in a participatory way, as well as leveraging the concepts of self-organisation, self-regulation, and self-control, would foster synergy effects and thereby help to leverage a sustainable technological revolution on a global scale. Furthermore, a “democracy by design” approach could also promote resilience. Full article

(This article belongs to the Special Issue AI and Interaction Technologies for Social Sustainability)

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