TANTANGAN ETIKA DALAM IMPLEMENTASI KECERDASAN BUATAN DAN PEMBELAJARAN MESIN: SYSTEMATIC LITERATURE REVIEW
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| Format: | Recurso digital |
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Zenodo
2025
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| _version_ | 1866901415586168832 |
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| author | Yaulie Deo Y Rindengan Febrian Rezki Hemeto Ryan Christian Fabian Rattu |
| author_facet | Yaulie Deo Y Rindengan Febrian Rezki Hemeto Ryan Christian Fabian Rattu |
| contents | <p>ABSTRACT<br>The development of artificial intelligence and machine learning<br>technologies has advanced rapidly over the past decade, yet<br>their implementation presents a range of complex ethical<br>challenges. This study aims to identify and analyze the main<br>ethical challenges in the implementation of artificial intelligence<br>and machine learning through a systematic literature review<br>approach. The research methodology uses the PRISMA protocol<br>with literature searches conducted in the IEEE Xplore, ACM<br>Digital Library, ScienceDirect, Springer Link, and Google Scholar<br>databases for the period 2018–2024. From 287 articles identified,<br>42 high-quality articles were selected for in-depth analysis.<br>The findings indicate that the primary ethical challenges include<br>algorithmic bias and discrimination, data privacy and security,<br>system transparency and explainability, and accountability in<br>automated decision-making. Significant social impacts include<br>job displacement, the digital divide, and information<br>manipulation through deepfakes. The study also identifies<br>various emerging ethical frameworks and risk-mitigation<br>solutions that can be applied.<br>The conclusion highlights that responsible implementation of<br>artificial intelligence requires a holistic approach that<br>incorporates technical, legal, and social aspects, supported by<br>collaboration among developers, regulators, and society.</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_17865565 |
| institution | Zenodo |
| language | |
| publishDate | 2025 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | TANTANGAN ETIKA DALAM IMPLEMENTASI KECERDASAN BUATAN DAN PEMBELAJARAN MESIN: SYSTEMATIC LITERATURE REVIEW Yaulie Deo Y Rindengan Febrian Rezki Hemeto Ryan Christian Fabian Rattu <p>ABSTRACT<br>The development of artificial intelligence and machine learning<br>technologies has advanced rapidly over the past decade, yet<br>their implementation presents a range of complex ethical<br>challenges. This study aims to identify and analyze the main<br>ethical challenges in the implementation of artificial intelligence<br>and machine learning through a systematic literature review<br>approach. The research methodology uses the PRISMA protocol<br>with literature searches conducted in the IEEE Xplore, ACM<br>Digital Library, ScienceDirect, Springer Link, and Google Scholar<br>databases for the period 2018–2024. From 287 articles identified,<br>42 high-quality articles were selected for in-depth analysis.<br>The findings indicate that the primary ethical challenges include<br>algorithmic bias and discrimination, data privacy and security,<br>system transparency and explainability, and accountability in<br>automated decision-making. Significant social impacts include<br>job displacement, the digital divide, and information<br>manipulation through deepfakes. The study also identifies<br>various emerging ethical frameworks and risk-mitigation<br>solutions that can be applied.<br>The conclusion highlights that responsible implementation of<br>artificial intelligence requires a holistic approach that<br>incorporates technical, legal, and social aspects, supported by<br>collaboration among developers, regulators, and society.</p> |
| title | TANTANGAN ETIKA DALAM IMPLEMENTASI KECERDASAN BUATAN DAN PEMBELAJARAN MESIN: SYSTEMATIC LITERATURE REVIEW |
| url | https://doi.org/10.5281/zenodo.17865565 |