Sosyal Fayda için Yapay Zeka
Yıl: 2024 Cilt: 5 Sayı: 1 Sayfa Aralığı: 85 - 101 Metin Dili: Türkçe DOI: 10.47613/reflektif.2024.146 İndeks Tarihi: 12-03-2024
Sosyal Fayda için Yapay Zeka
Öz:AI for Social Good
Öz: Belge Türü: Makale Makale Türü: Diğer Erişim Türü: Erişime Açık
- Arabi, H., ve Zaidi, H. (2020). Applications of artificial intelligence and deep learning in molecular imaging and radiotherapy. European Journal of Hybrid Imaging,4(1), 17. https://doi.org/10.1186/s41824-020- 00086-8
- Barba, P. (2020, Ekim 22). Challenges in Developing Multilingual Language Models in Natural Language Processing (NLP). Medium. https://towardsdatascience.com/challenges-in-developing-multilingual- language-models-in-natural-language-processing-nlp-f3b2bed64739
- Barry, B., Zhu, X., Behnken, E., Inselman, J., Schaepe, K., McCoy, R., Rushlow, D., Noseworthy, P., Richardson, J., ve Curtis, S. (2022). Provider Perspectives on Artificial Intelligence–Guided Screening for Low Ejection Fraction in Primary Care: Qualitative Study. JMIR AI, 1(1), e41940.
- Chi, N., Lurie, E., ve Mulligan, D. K. (2021). Reconfiguring diversity and inclusion for AI ethics. Proceedings of the 2021 AAAI/ACM Conference on AI, Ethics, and Society, 447–457. https://doi. org/10.1145/3461702.3462622
- Cox, A. M., ve Mazumdar, S. (2022). Defining artificial intelligence for librarians. Journal of Librarianship and Information Science, 096100062211420. https://doi.org/10.1177/09610006221142029
- Daneshjou, R., Smith, M. P., Sun, M. D., Rotemberg, V., ve Zou, J. (2021). Lack of transparency and potential bias in artificial intelligence data sets and algorithms: A scoping review. JAMA Dermatology, 157(11), 1362–1369.
- De Laat, M., Joksimovic, S., ve Ifenthaler, D. (2020). Artificial intelligence, real-time feedback and workplace learning analytics to support in situ complex problem-solving: A commentary. The International Journal of Information and Learning Technology, 37(5), 267–277. https://doi.org/10.1108/ IJILT-03-2020-0026
- Dergunova, Y., Aubakirova, R. Z., Yelmuratova, B. Z., Gulmira, T. M., Yuzikovna, P. N., ve Antikeyeva, S. (2022). Artificial Intelligence Awareness Levels of Students. International Journal of Emerging Technologies in Learning, 17(18). https://search.ebscohost.com/login.
- Fukumura, Y. E., Gray, J. M., Lucas, G. M., Becerik-Gerber, B., ve Roll, S. C. (2021). Worker perspectives on incorporating artificial intelligence into office workspaces: Implications for the future of office work. International Journal of Environmental Research and Public Health, 18(4), 1690.
- Fulton, R., Fulton, D., ve Kaplan, S. (2022). Artificial Intelligence: Framework of Driving Triggers to Past, Present and Future Applications snd Influencers of Industry Sector Adoption (arXiv:2204.01518). arXiv. http://arxiv.org/abs/2204.01518
- Gorbacheva, A. (2023, Ekim 6). No Language Left Behind: How to Bridge the Rapidly Evolving AI Language Gap | United Nations Development Programme. https://www.undp.org/kazakhstan/blog/no-language- left-behind-how-bridge-rapidly-evolving-ai-language-gap
- Gualdi, F., ve Cordella, A. (2021). Artificial Intelligence and Decision-making: The Question of Accountability. https://eprints.lse.ac.uk/110995/
- Huang, M.-H., ve Rust, R. T. (2018). Artificial Intelligence in Service. Journal of Service Research, 21(2), 155–172. https://doi.org/10.1177/1094670517752459
- Huang, M.-H., ve Rust, R. T. (2021). Engaged to a Robot? The Role of AI in Service. Journal of Service Research, 24(1), 30–41. https://doi.org/10.1177/1094670520902266
- Koleva, M. (2023, Ekim 23). Building a Better Tomorrow: How No-Code Apps Powered by AI Benefit NGOs. Planet Crust. https://www.planetcrust.com/building-a-better-tomorrow-how-no-code-apps-powered- by-ai-benefit-ngos/?utm_campaign=blog
- Kshirsagar, M., Robinson, C., Yang, S., Gholami, S., Klyuzhin, I., Mukherjee, S., Nasir, M., Ortiz, A., Oviedo, F., Tanner, D., Trivedi, A., Xu, Y., Zhong, M., Dilkina, B., Dodhia, R., ve Lavista Ferres, J. M. (2021). Becoming Good at AI for Good. Proceedings of the 2021 AAAI/ACM Conference on AI, Ethics, and Society, 664–673. https://doi.org/10.1145/3461702.3462599
- Li, H., ve Sun, Y. (2022). A Social-Driven Intelligent System to assist the classification of pet emotions using deep learning and big data analysis. CS & IT Conference Proceedings, 12(13). https://csitcp.net/ paper/12/1213csit12.pdf
- Mirbabaie, M., Brünker, F., Möllmann Frick, N. R. J., ve Stieglitz, S. (2022). The rise of artificial intelligence – understanding the AI identity threat at the workplace. Electronic Markets, 32(1), 73–99. https://doi. org/10.1007/s12525-021-00496-x
- Neuhofer, B., Magnus, B., ve Celuch, K. (2021). The impact of artificial intelligence on event experiences: A scenario technique approach. Electronic Markets, 31(3), 601–617. https://doi.org/10.1007/s12525- 020-00433-4
- Ping, H., ve Ying, G. Y. (2018). Comprehensive view on the effect of artificial intelligence on employment. Topics in Education, Culture and Social Development (TECSD), 1(1), 32–35.
- Pratama, A. M., ve Kharisma, D. B. (2022). Civil liability regime for artificial intelligence in indonesia: become a future legal subject? International Conference for Democracy and National Resilience 2022 (ICDNR 2022), 237–243. https://www.atlantis-press.com/proceedings/icdnr-22/125978726
- Rancy, A. (2023, Ekim 19). Setting Democratic Ground Rules for AI: Civil Society Strategies. NATIONAL ENDOWMENT FOR DEMOCRACY. https://www.ned.org/setting-democratic-ground-rules-for-ai- civil-society-strategies/
- Razumovskaia, E., Glavaš, G., Majewska, O., Ponti, E., ve Vulić, I. (2022). Natural language processing for multilingual task-oriented dialogue. Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics: Tutorial Abstracts, 44–50. https://aclanthology.org/2022.acl-tutorials.8/
- Reeve, O., Colom, A., ve Modhvadia, R. (2023, Ekim 26). What do the Public Think About AI? https://www. adalovelaceinstitute.org/evidence-review/what-do-the-public-think-about-ai/
- Rosnerova, Z., ve Hraskova, D. (2021). The Application and Importance of Marketing and its Tools in the Conditions of Non-profit Organizations on a Global Scale. SHS Web of Conferences, 92, 02055. https://www.shs-conferences.org/articles/shsconf/abs/2021/03/shsconf_glob20_02055/shsconf_ glob20_02055.html
- Russell, R. G., Lovett Novak, L., Patel, M., Garvey, K. V., Craig, K. J. T., Jackson, G. P., Moore, D., ve Miller, B. M. (2023). Competencies for the Use of Artificial Intelligence–Based Tools by Health Care Professionals. Academic Medicine, 98(3), 348–356.
- Salah, K., Rehman, M. H. U., Nizamuddin, N., ve Al-Fuqaha, A. (2019). Blockchain for AI: Review and open research challenges. IEEE Access, 7, 10127–10149.
- Selbst, A. D., Boyd, D., Friedler, S. A., Venkatasubramanian, S., ve Vertesi, J. (2019). Fairness and Abstraction in Sociotechnical Systems. Proceedings of the Conference on Fairness, Accountability, and Transparency, 59–68. https://doi.org/10.1145/3287560.3287598
- Shrestha, Y. R., Ben-Menahem, S. M., ve Von Krogh, G. (2019). Organizational Decision-Making Structures in the Age of Artificial Intelligence. California Management Review, 61(4), 66–83. https://doi. org/10.1177/0008125619862257
- Smith, S. (2023, Ekim 24). Deciphering the Language of Artificial Intelligence: Challenges in Training Multilingual AI Models. Day Translations Blog. https://www.daytranslations.com/blog/deciphering- the-language-of-artificial-intelligence-challenges-in-training-multilingual-ai-models/
- Spector, J. M., ve Ma, S. (2019). Inquiry and critical thinking skills for the next generation: From artificial intelligence back to human intelligence. Smart Learning Environments, 6(1), 8, s40561-019-0088-z. https://doi.org/10.1186/s40561-019-0088-z
- The Fundraising KIT Team. (2021, Ağustos 23). 5 Nonprofit Tasks That Can Be Automated using AI. Fundraising KIT. https://fundraisingkit.com/blog/automate-nonprofit-tasks-using-artificial-intelligence/
- Tschandl, P. (2021). Risk of bias and error from data sets used for dermatologic artificial intelligence. JAMA Dermatology, 157(11), 1271–1273.
- Vijayakumar, H. (2023). Business Value Impact of AI-Powered Service Operations (AIServiceOps). Available at SSRN 4396170. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4396170
- Wang, Z., ve Zhang, Y. (2022). A Study of Ethics on Intelligent Nonlinear Prediction Creative Design. Scientific Programming, 2022. https://www.hindawi.com/journals/sp/2022/8616308/
- Wilkens, U. (2020). Artificial intelligence in the workplace–A double-edged sword. The International Journal of Information and Learning Technology, 37(5), 253–265.
- Yan, Z., Song, X., Zhong, H., Yang, L., ve Wang, Y. (2022). Ship classification and anomaly detection based on spaceborne AIS data considering behavior characteristics. Sensors, 22(20), 7713.
- Yang, F., Qiao, Y., Wei, W., Wang, X., Wan, D., Damaševičius, R., ve Woźniak, M. (2020). DDTree: A hybrid deep learning model for real-time waterway depth prediction and smart navigation. Applied Sciences, 10(8), 2770.
- Yeo, S.-J., Choi, K., Cuc, B. T., Hong, N. N., Bao, D. T., Ngoc, N. M., Le, M. Q., Hang, N. L. K., Thach, N. C., ve Mallik, S. K. (2016). Smartphone-based fluorescent diagnostic system for highly pathogenic H5N1 viruses. Theranostics, 6(2), 231.
- Yu, H., Shen, Z., Miao, C., Leung, C., Lesser, V. R., ve Yang, Q. (2018). Building Ethics into Artificial Intelligence (arXiv:1812.02953). arXiv. http://arxiv.org/abs/1812.02953
- Zhang, D., Li, J., Wu, Q., Liu, X., Chu, X., ve He, W. (2017). Enhance the AIS data availability by screen- ing and interpolation. 2017 4th International Conference on Transportation Information and Safety (ICTIS), 981–986. https://ieeexplore.ieee.org/abstract/document/8047888/?casa_token=ny- f6kWJlNqoAAAAA:5v0KBPmXemFhdxvX2bLtmPK6IEQx2BSNF3UEB_K17owPrjAUKZyuLvMY- h9oUe525ppQoZaGeyg
- Zhao, B. (2023). Analysis on the negative impact of ai development on employment and its countermeasures. SHS Web of Conferences, 154, 03022. https://www.shs-conferences.org/articles/shsconf/abs/2023/03/ shsconf_pesd2023_03022/shsconf_pesd2023_03022.html
| APA | Saka E (2024). Sosyal Fayda için Yapay Zeka. , 85 - 101. 10.47613/reflektif.2024.146 |
| Chicago | Saka Erkan Sosyal Fayda için Yapay Zeka. (2024): 85 - 101. 10.47613/reflektif.2024.146 |
| MLA | Saka Erkan Sosyal Fayda için Yapay Zeka. , 2024, ss.85 - 101. 10.47613/reflektif.2024.146 |
| AMA | Saka E Sosyal Fayda için Yapay Zeka. . 2024; 85 - 101. 10.47613/reflektif.2024.146 |
| Vancouver | Saka E Sosyal Fayda için Yapay Zeka. . 2024; 85 - 101. 10.47613/reflektif.2024.146 |
| IEEE | Saka E "Sosyal Fayda için Yapay Zeka." , ss.85 - 101, 2024. 10.47613/reflektif.2024.146 |
| ISNAD | Saka, Erkan. "Sosyal Fayda için Yapay Zeka". (2024), 85-101. https://doi.org/10.47613/reflektif.2024.146 |
| APA | Saka E (2024). Sosyal Fayda için Yapay Zeka. Reflektif Sosyal Bilimler Dergisi, 5(1), 85 - 101. 10.47613/reflektif.2024.146 |
| Chicago | Saka Erkan Sosyal Fayda için Yapay Zeka. Reflektif Sosyal Bilimler Dergisi 5, no.1 (2024): 85 - 101. 10.47613/reflektif.2024.146 |
| MLA | Saka Erkan Sosyal Fayda için Yapay Zeka. Reflektif Sosyal Bilimler Dergisi, vol.5, no.1, 2024, ss.85 - 101. 10.47613/reflektif.2024.146 |
| AMA | Saka E Sosyal Fayda için Yapay Zeka. Reflektif Sosyal Bilimler Dergisi. 2024; 5(1): 85 - 101. 10.47613/reflektif.2024.146 |
| Vancouver | Saka E Sosyal Fayda için Yapay Zeka. Reflektif Sosyal Bilimler Dergisi. 2024; 5(1): 85 - 101. 10.47613/reflektif.2024.146 |
| IEEE | Saka E "Sosyal Fayda için Yapay Zeka." Reflektif Sosyal Bilimler Dergisi, 5, ss.85 - 101, 2024. 10.47613/reflektif.2024.146 |
| ISNAD | Saka, Erkan. "Sosyal Fayda için Yapay Zeka". Reflektif Sosyal Bilimler Dergisi 5/1 (2024), 85-101. https://doi.org/10.47613/reflektif.2024.146 |
