Navigating the Ethical Terrain of AI-Generated Text Tools: A Review
This review examines the ethical, social, and technical challenges posed by AI-generated text tools, focusing on their rapid advancement and widespread adoption. An exhaustive literature search across many databases, strict inclusion/exclusion criteria, and a rigorous analysis procedure are all part...
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| Format: | Article |
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IEEE
2024-01-01
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| Online Access: | https://ieeexplore.ieee.org/document/10813359/ |
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| author | Yasir Abdelgadir Mohamed Abdul Hakim H. M. Mohamed Akbar Khanan Mohamed Bashir Mousab A. E. Adiel Muawia A. Elsadig |
| author_facet | Yasir Abdelgadir Mohamed Abdul Hakim H. M. Mohamed Akbar Khanan Mohamed Bashir Mousab A. E. Adiel Muawia A. Elsadig |
| author_sort | Yasir Abdelgadir Mohamed |
| collection | DOAJ |
| description | This review examines the ethical, social, and technical challenges posed by AI-generated text tools, focusing on their rapid advancement and widespread adoption. An exhaustive literature search across many databases, strict inclusion/exclusion criteria, and a rigorous analysis procedure are all parts of our systematic review technique. This guarantees an impartial and complete study of the current status of AI-generated text tools. The study analyzes prominent language models, including GPT-3, GPT-4, LaMDA, PaLM, Claude, Jasper, and Llama 2, evaluating their capabilities in natural language processing and generation. The analysis reveals significant advancements, with GPT-3 demonstrating a 92% accuracy rate on standard natural language understanding benchmarks, outperforming LaMDA (88%) and PaLM (85%). To illustrate real-world implications, the review presents a case study of ChatGPT’s application in healthcare, where it achieved 80% consistency with expert opinions in assessing acute ulcerative colitis. This case highlights both the potential benefits and ethical concerns of AI in critical domains. Quantitative bias analysis shows that GPT-3 generated biased content in 15% of test cases involving sensitive topics, a higher rate than LaMDA (12%) and PaLM (10%). We provide an in-depth analysis of fairness and bias issues, particularly in image generation tasks depicting professional roles. Our research synthesizes insights from technical advancements, ethical considerations, and real-world applications across healthcare, education, and creative sectors. We address critical privacy concerns and data protection challenges, noting struggles in AI-generated text detection and investigating AI’s potential in enabling cyberattacks. We underscore the need for comprehensive governance systems and multidisciplinary cooperation. To provide a cohesive analysis of the ethical considerations surrounding AI-generated text tools, we employ a multifaceted ethical framework drawing on established theories. Utilitarianism, which seeks to maximize happiness for everyone; deontology, which places an emphasis on right and wrong; and Virtue Ethics, which analyzes the moral nature of deeds and actors, are all included in this framework. In this article, we use this approach to investigate AI ethics from a variety of angles, including privacy, prejudice, and social implications, as well as concerns of justice and fairness. Moreover, the study critically examines existing and proposed legal frameworks addressing AI ethics, identifying regulatory gaps and proposing adaptive policy recommendations to address the unique challenges posed by AI-generated text tools. Our review contributes a critical analysis of AI-generated text tools, their impacts, and the need for responsible innovation. The study provides precise guidelines for the ethical development and implementation of AI, highlighting the need to strike a balance between technical progress and ethical concerns to guarantee that AI technologies have a beneficial effect on society while protecting human values. The emergence of generative artificial intelligence (AI) signifies a substantial revolution in our methods of interacting with language and information. |
| format | Article |
| id | doaj-art-00b6e1ca9b8e4e8eba9e5f3f23ceaa11 |
| institution | DOAJ |
| issn | 2169-3536 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | IEEE |
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| series | IEEE Access |
| spelling | doaj-art-00b6e1ca9b8e4e8eba9e5f3f23ceaa112025-08-20T02:58:18ZengIEEEIEEE Access2169-35362024-01-011219706119712010.1109/ACCESS.2024.352194510813359Navigating the Ethical Terrain of AI-Generated Text Tools: A ReviewYasir Abdelgadir Mohamed0https://orcid.org/0000-0002-9337-7688Abdul Hakim H. M. Mohamed1https://orcid.org/0000-0001-5879-5385Akbar Khanan2https://orcid.org/0000-0002-2226-0001Mohamed Bashir3Mousab A. E. Adiel4https://orcid.org/0000-0002-9207-0035Muawia A. Elsadig5https://orcid.org/0000-0002-2622-6724College of Business administration, A’Sharqiyah University, Ibra, OmanCollege of Business administration, A’Sharqiyah University, Ibra, OmanCollege of Business administration, A’Sharqiyah University, Ibra, OmanCollege of Business administration, A’Sharqiyah University, Ibra, OmanCollege of Computer Science and Information Technology, Imam Abudlrahman Bin Faisal University, Dammam, Saudi ArabiaCollege of Computer Science and Information Technology, Imam Abudlrahman Bin Faisal University, Dammam, Saudi ArabiaThis review examines the ethical, social, and technical challenges posed by AI-generated text tools, focusing on their rapid advancement and widespread adoption. An exhaustive literature search across many databases, strict inclusion/exclusion criteria, and a rigorous analysis procedure are all parts of our systematic review technique. This guarantees an impartial and complete study of the current status of AI-generated text tools. The study analyzes prominent language models, including GPT-3, GPT-4, LaMDA, PaLM, Claude, Jasper, and Llama 2, evaluating their capabilities in natural language processing and generation. The analysis reveals significant advancements, with GPT-3 demonstrating a 92% accuracy rate on standard natural language understanding benchmarks, outperforming LaMDA (88%) and PaLM (85%). To illustrate real-world implications, the review presents a case study of ChatGPT’s application in healthcare, where it achieved 80% consistency with expert opinions in assessing acute ulcerative colitis. This case highlights both the potential benefits and ethical concerns of AI in critical domains. Quantitative bias analysis shows that GPT-3 generated biased content in 15% of test cases involving sensitive topics, a higher rate than LaMDA (12%) and PaLM (10%). We provide an in-depth analysis of fairness and bias issues, particularly in image generation tasks depicting professional roles. Our research synthesizes insights from technical advancements, ethical considerations, and real-world applications across healthcare, education, and creative sectors. We address critical privacy concerns and data protection challenges, noting struggles in AI-generated text detection and investigating AI’s potential in enabling cyberattacks. We underscore the need for comprehensive governance systems and multidisciplinary cooperation. To provide a cohesive analysis of the ethical considerations surrounding AI-generated text tools, we employ a multifaceted ethical framework drawing on established theories. Utilitarianism, which seeks to maximize happiness for everyone; deontology, which places an emphasis on right and wrong; and Virtue Ethics, which analyzes the moral nature of deeds and actors, are all included in this framework. In this article, we use this approach to investigate AI ethics from a variety of angles, including privacy, prejudice, and social implications, as well as concerns of justice and fairness. Moreover, the study critically examines existing and proposed legal frameworks addressing AI ethics, identifying regulatory gaps and proposing adaptive policy recommendations to address the unique challenges posed by AI-generated text tools. Our review contributes a critical analysis of AI-generated text tools, their impacts, and the need for responsible innovation. The study provides precise guidelines for the ethical development and implementation of AI, highlighting the need to strike a balance between technical progress and ethical concerns to guarantee that AI technologies have a beneficial effect on society while protecting human values. The emergence of generative artificial intelligence (AI) signifies a substantial revolution in our methods of interacting with language and information.https://ieeexplore.ieee.org/document/10813359/Generative AItext generationethics |
| spellingShingle | Yasir Abdelgadir Mohamed Abdul Hakim H. M. Mohamed Akbar Khanan Mohamed Bashir Mousab A. E. Adiel Muawia A. Elsadig Navigating the Ethical Terrain of AI-Generated Text Tools: A Review IEEE Access Generative AI text generation ethics |
| title | Navigating the Ethical Terrain of AI-Generated Text Tools: A Review |
| title_full | Navigating the Ethical Terrain of AI-Generated Text Tools: A Review |
| title_fullStr | Navigating the Ethical Terrain of AI-Generated Text Tools: A Review |
| title_full_unstemmed | Navigating the Ethical Terrain of AI-Generated Text Tools: A Review |
| title_short | Navigating the Ethical Terrain of AI-Generated Text Tools: A Review |
| title_sort | navigating the ethical terrain of ai generated text tools a review |
| topic | Generative AI text generation ethics |
| url | https://ieeexplore.ieee.org/document/10813359/ |
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