AI for Social Good-Explainability and Sustainability of Decision-Making Practices
A special issue of Sustainability (ISSN 2071-1050).
Deadline for manuscript submissions: 31 May 2025 | Viewed by 109
Special Issue Editors
Interests: explainable Artificial Intelligence; computational intelligence; intelligent modelling; expert system design; evolutionary optimisation
Special Issues, Collections and Topics in MDPI journals
Interests: AI for social good; AI fairness; AI explainability; smart agriculture; visual analytics; behavior analytics; human-computer interaction
Special Issues, Collections and Topics in MDPI journals
Interests: digital transformation; digital processing; visualization; E-commerce; business intelligence; m-Health
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
AI and technology are changing the world we live in. The United Nations (UN) has published an initiative that laid out 17 Sustainable Development Goals (SDGs) covering far-reaching challenges related to poverty, inequality, climate change, environmental degradation, peace, and justice. AI can be used as a tool to address the challenges related to SDGs. For example, AI can be applied to provide unbiased insights into the candidate pool for job applications. This would address the inequality challenge. Additionally, it is important to apply the AI algorithms ethically and responsibly for social good. Academia has the responsibility to pave the way towards discovering decision-making solutions that are fair, transparent, and explainable and making sure that AI solutions are sustainable. Explainable AI is one of the ways to bring transparency to the decision-making process to ensure the solutions provided through technological systems are sustainable.
This Special Issue focuses on providing solutions and algorithms to increase the explainability and transparency of the AI systems to ensure sustainability. Both theoretical and actual applications of AI algorithms and XAI that highlight the alignment with sustainability and applicability for social good are welcome. This includes local and global XAI methods, their application for problem solving, and solutions to enhance the performance of the decision-making algorithms. The solutions addressing problems utilizing different forms of data (images, numerical, etc.) that incorporate XAI algorithms and demonstrate the contribution to sustainability and social good, are welcome.
We are mainly interested in manuscripts that apply AI algorithms and decision-making processes to address challenges related to sustainable, socio-economic, scientific, and integrated approaches for sustainable development, including applying AI to SDG challenges and sustainability issues.
Dr. Niusha Shafiabady
Dr. Jianlong Zhou
Dr. Robert M.X. Wu
Guest Editors
Manuscript Submission Information
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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sustainability is an international peer-reviewed open access semimonthly journal published by MDPI.
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
- explainable AI
- AI for social good
- XAI applications
- XAI algorithms
- AI transparency
- sustainability
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