Can Data and Machine Learning Change the Future of Basic Income Models? A Bayesian Belief Networks Approach
Appeals to governments for implementing basic income are contemporary. The theoretical backgrounds of the basic income notion only prescribe transferring equal amounts to individuals irrespective of their specific attributes. However, the most recent basic income initiatives all around the world are...
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-01-01
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| Series: | Data |
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| Online Access: | https://www.mdpi.com/2306-5729/9/2/18 |
| _version_ | 1797298467273441280 |
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| author | Hamed Khalili |
| author_facet | Hamed Khalili |
| author_sort | Hamed Khalili |
| collection | DOAJ |
| description | Appeals to governments for implementing basic income are contemporary. The theoretical backgrounds of the basic income notion only prescribe transferring equal amounts to individuals irrespective of their specific attributes. However, the most recent basic income initiatives all around the world are attached to certain rules with regard to the attributes of the households. This approach is facing significant challenges to appropriately recognize vulnerable groups. A possible alternative for setting rules with regard to the welfare attributes of the households is to employ artificial intelligence algorithms that can process unprecedented amounts of data. Can integrating machine learning change the future of basic income by predicting households vulnerable to future poverty? In this paper, we utilize multidimensional and longitudinal welfare data comprising one and a half million individuals’ data and a Bayesian beliefs network approach to examine the feasibility of predicting households’ vulnerability to future poverty based on the existing households’ welfare attributes. |
| first_indexed | 2024-03-07T22:36:19Z |
| format | Article |
| id | doaj.art-2903ca4ae0fd49e1b0f2e926edab375a |
| institution | Directory Open Access Journal |
| issn | 2306-5729 |
| language | English |
| last_indexed | 2024-03-07T22:36:19Z |
| publishDate | 2024-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Data |
| spelling | doaj.art-2903ca4ae0fd49e1b0f2e926edab375a2024-02-23T15:13:29ZengMDPI AGData2306-57292024-01-01921810.3390/data9020018Can Data and Machine Learning Change the Future of Basic Income Models? A Bayesian Belief Networks ApproachHamed Khalili0Research Group E-Government, Faculty of Computer Science, University of Koblenz, D-56070 Koblenz, GermanyAppeals to governments for implementing basic income are contemporary. The theoretical backgrounds of the basic income notion only prescribe transferring equal amounts to individuals irrespective of their specific attributes. However, the most recent basic income initiatives all around the world are attached to certain rules with regard to the attributes of the households. This approach is facing significant challenges to appropriately recognize vulnerable groups. A possible alternative for setting rules with regard to the welfare attributes of the households is to employ artificial intelligence algorithms that can process unprecedented amounts of data. Can integrating machine learning change the future of basic income by predicting households vulnerable to future poverty? In this paper, we utilize multidimensional and longitudinal welfare data comprising one and a half million individuals’ data and a Bayesian beliefs network approach to examine the feasibility of predicting households’ vulnerability to future poverty based on the existing households’ welfare attributes.https://www.mdpi.com/2306-5729/9/2/18basic incomepovertyvulnerabilitymachine learningBayesian networksartificial intelligence |
| spellingShingle | Hamed Khalili Can Data and Machine Learning Change the Future of Basic Income Models? A Bayesian Belief Networks Approach Data basic income poverty vulnerability machine learning Bayesian networks artificial intelligence |
| title | Can Data and Machine Learning Change the Future of Basic Income Models? A Bayesian Belief Networks Approach |
| title_full | Can Data and Machine Learning Change the Future of Basic Income Models? A Bayesian Belief Networks Approach |
| title_fullStr | Can Data and Machine Learning Change the Future of Basic Income Models? A Bayesian Belief Networks Approach |
| title_full_unstemmed | Can Data and Machine Learning Change the Future of Basic Income Models? A Bayesian Belief Networks Approach |
| title_short | Can Data and Machine Learning Change the Future of Basic Income Models? A Bayesian Belief Networks Approach |
| title_sort | can data and machine learning change the future of basic income models a bayesian belief networks approach |
| topic | basic income poverty vulnerability machine learning Bayesian networks artificial intelligence |
| url | https://www.mdpi.com/2306-5729/9/2/18 |
| work_keys_str_mv | AT hamedkhalili candataandmachinelearningchangethefutureofbasicincomemodelsabayesianbeliefnetworksapproach |