Artificial Intelligence-Enhanced Decision Support for Informing Global Sustainable Development: A Human-Centric AI-Thinking Approach
Sustainable development is crucial to humanity. Utilization of primary socio-environmental data for analysis is essential for informing decision making by policy makers about sustainability in development. Artificial intelligence (AI)-based approaches are useful for analyzing data. However, it was n...
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-01-01
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| Series: | Information |
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| Online Access: | https://www.mdpi.com/2078-2489/11/1/39 |
| _version_ | 1818806527125880832 |
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| author | Meng-Leong How Sin-Mei Cheah Yong-Jiet Chan Aik Cheow Khor Eunice Mei Ping Say |
| author_facet | Meng-Leong How Sin-Mei Cheah Yong-Jiet Chan Aik Cheow Khor Eunice Mei Ping Say |
| author_sort | Meng-Leong How |
| collection | DOAJ |
| description | Sustainable development is crucial to humanity. Utilization of primary socio-environmental data for analysis is essential for informing decision making by policy makers about sustainability in development. Artificial intelligence (AI)-based approaches are useful for analyzing data. However, it was not easy for people who are not trained in computer science to use AI. The significance and novelty of this paper is that it shows how the use of AI can be democratized via a user-friendly human-centric probabilistic reasoning approach. Using this approach, analysts who are not computer scientists can also use AI to analyze sustainability-related EPI data. Further, this human-centric probabilistic reasoning approach can also be used as cognitive scaffolding to educe AI-Thinking in the analysts to ask more questions and provide decision making support to inform policy making in sustainable development. This paper uses the 2018 Environmental Performance Index (EPI) data from 180 countries which includes performance indicators covering environmental health and ecosystem vitality. AI-based predictive modeling techniques are applied on 2018 EPI data to reveal the hidden tensions between the two fundamental dimensions of sustainable development: (1) environmental health; which improves with economic growth and increasing affluence; and (2) ecosystem vitality, which worsens due to industrialization and urbanization. |
| first_indexed | 2024-12-18T19:11:11Z |
| format | Article |
| id | doaj.art-97c12871b15a450cbe5d00ccdd0aa291 |
| institution | Directory Open Access Journal |
| issn | 2078-2489 |
| language | English |
| last_indexed | 2024-12-18T19:11:11Z |
| publishDate | 2020-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Information |
| spelling | doaj.art-97c12871b15a450cbe5d00ccdd0aa2912022-12-21T20:56:15ZengMDPI AGInformation2078-24892020-01-011113910.3390/info11010039info11010039Artificial Intelligence-Enhanced Decision Support for Informing Global Sustainable Development: A Human-Centric AI-Thinking ApproachMeng-Leong How0Sin-Mei Cheah1Yong-Jiet Chan2Aik Cheow Khor3Eunice Mei Ping Say4National Institute of Education, Nanyang Technological University, Singapore 639798, SingaporeCenter for Management Practice, Singapore Management University, Singapore 188065, SingaporeFaculty of Education, Monash University, Victoria 3800, AustraliaFaculty of Education, Monash University, Victoria 3800, AustraliaNational Institute of Education, Nanyang Technological University, Singapore 639798, SingaporeSustainable development is crucial to humanity. Utilization of primary socio-environmental data for analysis is essential for informing decision making by policy makers about sustainability in development. Artificial intelligence (AI)-based approaches are useful for analyzing data. However, it was not easy for people who are not trained in computer science to use AI. The significance and novelty of this paper is that it shows how the use of AI can be democratized via a user-friendly human-centric probabilistic reasoning approach. Using this approach, analysts who are not computer scientists can also use AI to analyze sustainability-related EPI data. Further, this human-centric probabilistic reasoning approach can also be used as cognitive scaffolding to educe AI-Thinking in the analysts to ask more questions and provide decision making support to inform policy making in sustainable development. This paper uses the 2018 Environmental Performance Index (EPI) data from 180 countries which includes performance indicators covering environmental health and ecosystem vitality. AI-based predictive modeling techniques are applied on 2018 EPI data to reveal the hidden tensions between the two fundamental dimensions of sustainable development: (1) environmental health; which improves with economic growth and increasing affluence; and (2) ecosystem vitality, which worsens due to industrialization and urbanization.https://www.mdpi.com/2078-2489/11/1/39artificial intelligencedecision making supportsustainabilityenvironmental performance indexbayesianpredictive modelinghuman-centrichuman-in-the-loopai-thinkingexplainable-aiai for good |
| spellingShingle | Meng-Leong How Sin-Mei Cheah Yong-Jiet Chan Aik Cheow Khor Eunice Mei Ping Say Artificial Intelligence-Enhanced Decision Support for Informing Global Sustainable Development: A Human-Centric AI-Thinking Approach Information artificial intelligence decision making support sustainability environmental performance index bayesian predictive modeling human-centric human-in-the-loop ai-thinking explainable-ai ai for good |
| title | Artificial Intelligence-Enhanced Decision Support for Informing Global Sustainable Development: A Human-Centric AI-Thinking Approach |
| title_full | Artificial Intelligence-Enhanced Decision Support for Informing Global Sustainable Development: A Human-Centric AI-Thinking Approach |
| title_fullStr | Artificial Intelligence-Enhanced Decision Support for Informing Global Sustainable Development: A Human-Centric AI-Thinking Approach |
| title_full_unstemmed | Artificial Intelligence-Enhanced Decision Support for Informing Global Sustainable Development: A Human-Centric AI-Thinking Approach |
| title_short | Artificial Intelligence-Enhanced Decision Support for Informing Global Sustainable Development: A Human-Centric AI-Thinking Approach |
| title_sort | artificial intelligence enhanced decision support for informing global sustainable development a human centric ai thinking approach |
| topic | artificial intelligence decision making support sustainability environmental performance index bayesian predictive modeling human-centric human-in-the-loop ai-thinking explainable-ai ai for good |
| url | https://www.mdpi.com/2078-2489/11/1/39 |
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