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The Impact of Artificial Intelligence on Social Problems and Solutions: An Analysis on The Context of Digital Divide and Exploitation

Year 2022, Issue: 13, 247 - 264, 29.12.2022
https://doi.org/10.55609/yenimedya.1146586

Abstract

Continued advances in artificial intelligence (AI) technology innovations include ever-wider aspects of modern society’s economic, cultural, religious, and political life via new media tools and communication techniques. Considering AI as part of technological tools, networks, and institutional systems, innovative technology can be essential in solving social problems. With such a mindset, this study done on literature knowledge and sectoral research reports aims to capture AI’s expanding role and impact on social relations by expanding its ethical understandings and conceptual scope. The study tries to answer, if recent innovations in AI herald unprecedented social transformations and new challenges. This article critically assesses the problem, challenging the unending innovative technological determinism of many debates and reframing related issues with a sociological and religious approach. The study focuses on the importance of theoretical discussing the relationship between specificity and ecological validity of algorithmic models and how AI modeling is an essential contribution to the methodological approaches of scientists interested in social phenomena.

References

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  • Adaş, E. & Erbay, B. (2022). Yapay Zekâ Sosyolojisi Üzerine Bir Değerlendirme . Gaziantep University Journal of Social Sciences , 21 (1) , 326-337 . DOI: 10.21547/jss.991383
  • Ali, SM (2016). A brief introduction to de-colonial computing. XRDS: Crossroads The ACM Magazine for Students , 22 (4), 16–21.
  • Angwin, J., Larson, J., Mattu, S., & Kirchner, L. (2016). Machine bias. There's software used across the country to predict future criminals and it's biased against blacks. ProPublica. https://www.propublica.org/article/machine-bias-risk-assessments-in-criminal-sentencing .
  • Asilomar Meeting. (2017). Asilomar AI principles. https://futureoflife.org/ai-principles/
  • Awori, K., Bidwell, NJ., Hussan, TS., Gill, S., & Lindtner, S. (2016). Decolonising technology design. In Proceedings of the first African conference on human-computer interaction, pp. 226–228 .
  • Beer, D. (2017). The social power of algorithms. Information, Communication & Society, 20(1), 1–13.
  • Benjamin, R. (2019). Race after technology: abolitionist tools for the new Jim Code . New York: John Wiley & Sons.
  • Boden, MA (2018). Artificial intelligence: a very short introduction . London: Oxford University Press.
  • Broussard, M. (2018). Artificial unintelligence: How computers misunderstand the world. Massachusetts: The MIT Press.
  • Buolamwini, J., & Gebru, T. (2018). Gender shades: intersectional accuracy disparities in commercial gender classification. In Conference on fairness, accountability and transparency, pp 77–91 .
  • Chitty N. and Dias S. (2017) Artificial Intelligence, Soft Power and Social Transformation Journal of Content, Community & Communication, ISSN: 2395-7514 Vol. 6 Year 3, December.
  • Costanza-Chock, S. (2018). Design justice, AI, and escape from the matrix of domination. Journal of Design and Science.
  • Couldry, N., & Mejias, UA (2019a). The costs of connection: how data is colonizing human life and appropriating it for capitalism . Stanford: Stanford University Press.
  • Couldry, N., & Mejias, UA (2019b). Data colonialism: rethinking big data's relation to the contemporary subject. Television & New Media , 20 (4), 336–349.
  • D'Ignazio, C., & Klein, LF (2020). data feminism . Cambridge: MIT Press. Dastin, J. (2018). Amazon scraps secret AI recruiting tool that showed bias against women. San Francisco, CA: Reuters Retrieved on October 9:2018.
  • Easton, D. (1965). A Framework for Political Analysis. Englewood Cliffs, NJ: PrenticeHall, Inc.
  • Eynon, R., & Young, E. (2021). Methodology, legend, and rhetoric: The constructions of AI by academia, industry, and policy groups for lifelong learning. Science, Technology, & Human Values, 46(1), 166–191.
  • Ferdowsian HR, Beck N (2011) Ethical and Scientific Considerations Regarding Animal Testing and Research. PLoS ONE 6(9): e24059. https://doi.org/10.1371/journal.pone.0024059
  • Finkelhor D. & Korbin J. (1988) Child abuse as an international issue, Child Abuse & Neglect, Volume 12, Issue 1, , Pages 3-23, ISSN 0145-2134, https://doi.org/10.1016/0145- 2134(88)90003-8 .
  • Ford, M. Robotların yükselişi: Yapay zekâ ve işsiz bir gelecek tehlikesi (C. Duran, Çev.). İstanbul: Kronik Kitap.
  • Gerrish, S. (2018). How smart machines think . Cambridge: MIT Press.
  • Griffin K. (1987) World Hunger and the World Economy. In: World Hunger and the World Economy. Palgrave Macmillan, London. https://doi.org/10.1007/978-1-349-18739-3_1
  • Hendler J. & Berners-Lee, T. (2010) From the Semantic Web to social machines: A research challenge for AI on the World Wide Web, Artificial Intelligence, Volume 174, Issue 2, Pages 156-161,ISSN 0004-3702, https ://doi.org/10.1016/j.artint.2009.11.010 .
  • Hogarth, I. (2018). AI nationalisms. https://www.ianhogarth.com/blog/2018/6/13/ai-nationalism .
  • IEEE Global Initiative. (2016). Ethically aligned design. IEEE Standards v1.
  • IHS (2017) Number of Connected IoT Devices Will Surge to 125 Billion by 2030, IHS Markit Says, October 24 news, https://news.ihsmarkit.com/prviewer/release_only/slug/number-connected-iot-devices-will -surge-125-billion-2030-ihs-markit-says
  • Irani, L., Vertesi, J., Dourish, P., Philip, K., & Grinter, RE (2010). Postcolonial computing: a lens on design and development. In Proceedings of the SIGCHI conference on human factors in computing systems (pp. 1311–1320). New York: ACM.
  • Isaac, WS (2017). Hope, hype, and fear: the promise and potential pitfalls of artificial intelligence in criminal justice. Ohio State Journal of Criminal Law , 15 , 543.
  • ITU. (2019). United nations activities on artificial intelligence (AI) . Geneva: International Telecommunication Union. https://www.itu.int/dms_pub/itu-s/opb/gen/S-GEN-UNACT-2019-1-PDF-E.pdf .
  • James, CLR (1993). Beyond a boundary . Durham: Duke University Press.
  • Jansen, J. (2019). Decolonisation in universities: the politics of knowledge. Wits University Press.
  • Jasanoff, S., & Hurlbut, JB (2018). A global observatory for gene editing. Nature , 555 (7697), 435–437.
  • Jobin, A., Ienca, M., & Vayena, E. (2019). The global landscape of AI ethics guidelines. Nature Machine Intelligence , 1 (9), 389–399.
  • Johnston, K. (2019). A comparison of two smart cities: Singapore and Atlanta. Journal of Comparative Urban Law and Policy , 3 , 191.
  • Joyce, K., Smith-Doerr, L., Alegria, S., Bell, S., Cruz, T., Hoffman, S. G., Noble, S. U., & Shestakofsky, B. (2021). Toward a sociology of artificial intelligence: A call for research on inequalities and structural change. Socius, 7. 1-11.
  • Jung, C., Kearns, M., Neel, S., Roth, A., Stapleton, L., & Wu, ZS (2019). Eliciting and informing subjective individual fairness. arXiv: 190510660 .
  • Kanth, DR (2019). India boycotts 'Osaka Track' at G20 summit. Live Mint. https://www.livemint.com/news/world/india-boycotts-osaka-track-at-g20-summit-1561897592466.html .
  • Katell, M., Young, M., Dailey, D., Herman, B., Guitler, V., Tam, A., Binz, C., Raz, D., & Krafft, P. (2020). Toward situated interventions for algorithmic equity: lessons from the field. In Proceedings of the 2020 conference on fairness, accountability, and transparency, pp 45–55 .
  • Katz, Y. (2020). Artificial whiteness: Politics and ideology in artificial intelligence. New York: Columbia University Press.
  • Keyes, O. (2018). The misgendering machines: trans/HCI implications of automatic gender recognition. Proceedings of the ACM on Human-Computer Interaction , 2 (CSCW), 88.
  • Kiros, T. (1992). Moral philosophy and development: the human condition in Africa, vol 61. Ohio Univ Ctr for International Studies.
  • Landman Todd , Silverman Bernard W. (2019) Globalization and Modern Slavery, Journal of Politics and Governance, https://doi.org/10.17645/pag.v7i4.2233
  • Law, J., & et al. (1987). Technology and heterogeneous engineering: the case of Portuguese expansion. The social construction of technological systems:, New directions in the sociology and history of technology , 1 , 1–134.
  • Liu, Z. (2021). Sociological perspectives on artificial intelligence: A typological reading. Sociology Compass, 15(1).
  • Lohr S., (2018) Facial Reconition is occurate Yeah you are a white guy, NYTIMES, https://www.nytimes.com/2018/02/09/technology/facial-recognition-race-artificial-intelligence.html
  • McIlroy-Young Reid, Sen Siddhartha, Kleinberg Jon, and Anderson Ashton. (2020) Aligning Superhuman AI with Human Behavior: Chess as a Model System. In Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD '20). Association for Computing Machinery, New York, NY, USA, 1677–1687. DOI: https://doi.org/10.1145/3394486.3403219
  • Mohamed, S., Png, MT. & Isaac, W. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philos. Technol. 33, 659–684 (2020). https://doi.org/10.1007/s13347-020-00405-8
  • Nagy, S. (2020). The Role of Artificial Intelligence in Social Innovations. Bulletin of the National Technical University "Kharkov Polytechnic Institute" (economic sciences), (4), 112-116. http://es.khpi.edu.ua/article/view/231982
  • Obermeyer, Z., Powers, B., Vogeli, C., & Mullainathan, S. (2019). Dissecting racial bias in an algorithm used to manage the health of populations. Science , 366 (6464), 447–453.
  • OECD. (2019). OECD principles on artificial intelligence. https://www.oecd.org/going-digital/ai/principles/ .
  • Özkan, K. D. (2020). Bilişim Teknolojilerinin Gelişimi ve Veri Madenciliği Işığında Bir Gelecek İnşası: Black Mirror Dizisi Örneği . Yeni Medya , 2020 (8) , 41-65 . Retrieved from https://dergipark.org.tr/tr/pub/yenimedya/issue/56548/748649
  • Pathways for Prosperity. (2019). Digital diplomacy: technology governance for developing countries. Pathways for Prosperity Commission on Technology and Inclusive Development . https://pathwayscommission.bsg.ox.ac.uk/sites/default/files/2019-10/Digital-Diplomacy.pdf .
  • Rhee, J. (2018). The robotic imaginary: The human and the price of dehumanized labor. Minneapolis: University of Minnesota Press.
  • Ricaurte, P. (2019). Data epistemologies, the coloniality of power, and resistance. Television & New Media , 20 (4), 350–365.
  • Richardson, R., Schultz, J., & Crawford, K. (2019). Dirty data, bad predictions: how civil rights violations impact police data, predictive policing systems and justice. New York University Law Review Online, Forthcoming.
  • Rogers, EM (2001). The Digital Divide. Convergence, 7(4), 96–111. https://doi.org/10.1177/135485650100700406
  • Sap, M., Card, D., Gabriel, S., Choi, Y., & Smith, NA (2019). The risk of racial bias in hate speech detection. In Proceedings of the 57th annual meeting of the association for computational linguistics, pp 1668–1678 .
  • Stark, L. (2019). Facial recognition is the plutonium of AI. XRDS: Crossroads. The ACM Magazine for Students , 25 (3), 50–55.
  • Taylor, E. (2016). Groups and Oppression. Hypatia , 31 (3), 520–536.
  • Tellan, T. (2020). Duyarlı Makine: Yapay Zekanın Olgunluk Çağı . Yeni Medya , 2020 (9), 142-146. https://dergipark.org.tr/tr/pub/yenimedya/issue/58796/831469
  • Thrush, C. (2008). American curiosity: cultures of natural history in the colonial British Atlantic world. Environmental History , 13 (3), 573.
  • Toesland Finbar (2018) Five tech solutions to global problems, Raconteur, https://www.raconteur.net/technology/tech-solutions-global-problems/
  • UK National Health Service. (2019). Code of conduct for data-driven health and care technology.
  • Van de Poel, I., & Kroes, P. (2014). Can technology embody values?. In The moral status of technical artefacts (pp. 103–124). Berlin: Springer.
  • van der Linden, H. (2015). Drone warfare and just war theory. M. Cohn (Ed.), Drones and targeted Killing: Legal, moral and geopolitical issues (216-260 ss.). Massachusetts: Olive Branch Press.
  • Varshney Kush R., Mojsilovic Aleksandra (2019) Open Platforms for Artificial Intelligence for Social Good: Common Patterns as a Pathway to True Impact, Computers and Society, https://arxiv.org/abs/1905.11519
  • von Bertalanffy, L. (1972). 'The History and Status of General Systems Theory'.Trends in General System Theory, Ed. Klir, George, Wiley-Interscience, New York.
  • Yolgormez C., (2018) Bir Sosyolog Yapay Zekadan Ne Anlar?, https://duzensiz.org/bir-sosyolog-yapay-zekadan-ne-anlar-2f8d0dfd144a
  • Young, M., Magassa, L., & Friedman, B. (2019). Toward inclusive tech policy design: a method for underrepresented voices to strengthen tech policy documents. Ethics and Information Technology , 21 (2), 89–103.
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Yapay zekanın toplumsal sorunlara ve çözümlere etkisi: sayısal bölünme ve sömürü bağlamında bir analiz

Year 2022, Issue: 13, 247 - 264, 29.12.2022
https://doi.org/10.55609/yenimedya.1146586

Abstract

Yapay zeka (AI) teknolojisi yeniliklerinde devam eden ilerlemeler, yeni medya araçları ve iletişim teknikleri aracılığıyla modern toplumun ekonomik, kültürel, dini ve politik yaşamının her zamankinden daha geniş yönlerini içerir. Yapay zekayı teknolojik araçların, ağların bir parçası olarak ele almak, ve kurumsal sistemler, BT sosyal sorunların çözümünde gerekli olabilir. Böyle bir zihniyetle literatür bilgisi ve sektörel araştırma raporları üzerine yapılan bu çalışma, yapay zekanın etik anlayışlarını ve kavramsal kapsamını genişleterek sosyal ilişkiler üzerindeki genişleyen rolünü ve etkisini yakalamayı amaçlamaktadır. Yapay zekadaki son yenilikler benzeri görülmemiş sosyal dönüşümlerin ve yeni zorlukların habercisi mi? Bu makale, birçok tartışmanın bitmeyen yenilikçi teknolojik determinizmine meydan okuyarak ve ilgili konuları sosyolojik ve dini bir yaklaşımla yeniden çerçeveleyerek sorunu eleştirel olarak değerlendirmektedir. Çalışma, algoritmik modellerin özgüllüğü ve ekolojik geçerliliği arasındaki ilişkiyi teorik olarak tartışmanın önemine ve AI modellemesinin sosyal fenomenlerle ilgilenen bilim insanlarının metodolojik yaklaşımlarına nasıl önemli bir katkı olduğuna odaklanmaktadır.

References

  • Açıkalın, E. (2018). Avrupa Birliği’ne Uyum Sürecinde Türkiye’de Küçüklerin Kitle İletişim Araçlarından Korunması. Yeni Medya, (3), 51-67. Retrieved from https://dergipark.org.tr/tr/pub/yenimedya/issue/55565/760565
  • Adaş, E. & Erbay, B. (2022). Yapay Zekâ Sosyolojisi Üzerine Bir Değerlendirme . Gaziantep University Journal of Social Sciences , 21 (1) , 326-337 . DOI: 10.21547/jss.991383
  • Ali, SM (2016). A brief introduction to de-colonial computing. XRDS: Crossroads The ACM Magazine for Students , 22 (4), 16–21.
  • Angwin, J., Larson, J., Mattu, S., & Kirchner, L. (2016). Machine bias. There's software used across the country to predict future criminals and it's biased against blacks. ProPublica. https://www.propublica.org/article/machine-bias-risk-assessments-in-criminal-sentencing .
  • Asilomar Meeting. (2017). Asilomar AI principles. https://futureoflife.org/ai-principles/
  • Awori, K., Bidwell, NJ., Hussan, TS., Gill, S., & Lindtner, S. (2016). Decolonising technology design. In Proceedings of the first African conference on human-computer interaction, pp. 226–228 .
  • Beer, D. (2017). The social power of algorithms. Information, Communication & Society, 20(1), 1–13.
  • Benjamin, R. (2019). Race after technology: abolitionist tools for the new Jim Code . New York: John Wiley & Sons.
  • Boden, MA (2018). Artificial intelligence: a very short introduction . London: Oxford University Press.
  • Broussard, M. (2018). Artificial unintelligence: How computers misunderstand the world. Massachusetts: The MIT Press.
  • Buolamwini, J., & Gebru, T. (2018). Gender shades: intersectional accuracy disparities in commercial gender classification. In Conference on fairness, accountability and transparency, pp 77–91 .
  • Chitty N. and Dias S. (2017) Artificial Intelligence, Soft Power and Social Transformation Journal of Content, Community & Communication, ISSN: 2395-7514 Vol. 6 Year 3, December.
  • Costanza-Chock, S. (2018). Design justice, AI, and escape from the matrix of domination. Journal of Design and Science.
  • Couldry, N., & Mejias, UA (2019a). The costs of connection: how data is colonizing human life and appropriating it for capitalism . Stanford: Stanford University Press.
  • Couldry, N., & Mejias, UA (2019b). Data colonialism: rethinking big data's relation to the contemporary subject. Television & New Media , 20 (4), 336–349.
  • D'Ignazio, C., & Klein, LF (2020). data feminism . Cambridge: MIT Press. Dastin, J. (2018). Amazon scraps secret AI recruiting tool that showed bias against women. San Francisco, CA: Reuters Retrieved on October 9:2018.
  • Easton, D. (1965). A Framework for Political Analysis. Englewood Cliffs, NJ: PrenticeHall, Inc.
  • Eynon, R., & Young, E. (2021). Methodology, legend, and rhetoric: The constructions of AI by academia, industry, and policy groups for lifelong learning. Science, Technology, & Human Values, 46(1), 166–191.
  • Ferdowsian HR, Beck N (2011) Ethical and Scientific Considerations Regarding Animal Testing and Research. PLoS ONE 6(9): e24059. https://doi.org/10.1371/journal.pone.0024059
  • Finkelhor D. & Korbin J. (1988) Child abuse as an international issue, Child Abuse & Neglect, Volume 12, Issue 1, , Pages 3-23, ISSN 0145-2134, https://doi.org/10.1016/0145- 2134(88)90003-8 .
  • Ford, M. Robotların yükselişi: Yapay zekâ ve işsiz bir gelecek tehlikesi (C. Duran, Çev.). İstanbul: Kronik Kitap.
  • Gerrish, S. (2018). How smart machines think . Cambridge: MIT Press.
  • Griffin K. (1987) World Hunger and the World Economy. In: World Hunger and the World Economy. Palgrave Macmillan, London. https://doi.org/10.1007/978-1-349-18739-3_1
  • Hendler J. & Berners-Lee, T. (2010) From the Semantic Web to social machines: A research challenge for AI on the World Wide Web, Artificial Intelligence, Volume 174, Issue 2, Pages 156-161,ISSN 0004-3702, https ://doi.org/10.1016/j.artint.2009.11.010 .
  • Hogarth, I. (2018). AI nationalisms. https://www.ianhogarth.com/blog/2018/6/13/ai-nationalism .
  • IEEE Global Initiative. (2016). Ethically aligned design. IEEE Standards v1.
  • IHS (2017) Number of Connected IoT Devices Will Surge to 125 Billion by 2030, IHS Markit Says, October 24 news, https://news.ihsmarkit.com/prviewer/release_only/slug/number-connected-iot-devices-will -surge-125-billion-2030-ihs-markit-says
  • Irani, L., Vertesi, J., Dourish, P., Philip, K., & Grinter, RE (2010). Postcolonial computing: a lens on design and development. In Proceedings of the SIGCHI conference on human factors in computing systems (pp. 1311–1320). New York: ACM.
  • Isaac, WS (2017). Hope, hype, and fear: the promise and potential pitfalls of artificial intelligence in criminal justice. Ohio State Journal of Criminal Law , 15 , 543.
  • ITU. (2019). United nations activities on artificial intelligence (AI) . Geneva: International Telecommunication Union. https://www.itu.int/dms_pub/itu-s/opb/gen/S-GEN-UNACT-2019-1-PDF-E.pdf .
  • James, CLR (1993). Beyond a boundary . Durham: Duke University Press.
  • Jansen, J. (2019). Decolonisation in universities: the politics of knowledge. Wits University Press.
  • Jasanoff, S., & Hurlbut, JB (2018). A global observatory for gene editing. Nature , 555 (7697), 435–437.
  • Jobin, A., Ienca, M., & Vayena, E. (2019). The global landscape of AI ethics guidelines. Nature Machine Intelligence , 1 (9), 389–399.
  • Johnston, K. (2019). A comparison of two smart cities: Singapore and Atlanta. Journal of Comparative Urban Law and Policy , 3 , 191.
  • Joyce, K., Smith-Doerr, L., Alegria, S., Bell, S., Cruz, T., Hoffman, S. G., Noble, S. U., & Shestakofsky, B. (2021). Toward a sociology of artificial intelligence: A call for research on inequalities and structural change. Socius, 7. 1-11.
  • Jung, C., Kearns, M., Neel, S., Roth, A., Stapleton, L., & Wu, ZS (2019). Eliciting and informing subjective individual fairness. arXiv: 190510660 .
  • Kanth, DR (2019). India boycotts 'Osaka Track' at G20 summit. Live Mint. https://www.livemint.com/news/world/india-boycotts-osaka-track-at-g20-summit-1561897592466.html .
  • Katell, M., Young, M., Dailey, D., Herman, B., Guitler, V., Tam, A., Binz, C., Raz, D., & Krafft, P. (2020). Toward situated interventions for algorithmic equity: lessons from the field. In Proceedings of the 2020 conference on fairness, accountability, and transparency, pp 45–55 .
  • Katz, Y. (2020). Artificial whiteness: Politics and ideology in artificial intelligence. New York: Columbia University Press.
  • Keyes, O. (2018). The misgendering machines: trans/HCI implications of automatic gender recognition. Proceedings of the ACM on Human-Computer Interaction , 2 (CSCW), 88.
  • Kiros, T. (1992). Moral philosophy and development: the human condition in Africa, vol 61. Ohio Univ Ctr for International Studies.
  • Landman Todd , Silverman Bernard W. (2019) Globalization and Modern Slavery, Journal of Politics and Governance, https://doi.org/10.17645/pag.v7i4.2233
  • Law, J., & et al. (1987). Technology and heterogeneous engineering: the case of Portuguese expansion. The social construction of technological systems:, New directions in the sociology and history of technology , 1 , 1–134.
  • Liu, Z. (2021). Sociological perspectives on artificial intelligence: A typological reading. Sociology Compass, 15(1).
  • Lohr S., (2018) Facial Reconition is occurate Yeah you are a white guy, NYTIMES, https://www.nytimes.com/2018/02/09/technology/facial-recognition-race-artificial-intelligence.html
  • McIlroy-Young Reid, Sen Siddhartha, Kleinberg Jon, and Anderson Ashton. (2020) Aligning Superhuman AI with Human Behavior: Chess as a Model System. In Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD '20). Association for Computing Machinery, New York, NY, USA, 1677–1687. DOI: https://doi.org/10.1145/3394486.3403219
  • Mohamed, S., Png, MT. & Isaac, W. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philos. Technol. 33, 659–684 (2020). https://doi.org/10.1007/s13347-020-00405-8
  • Nagy, S. (2020). The Role of Artificial Intelligence in Social Innovations. Bulletin of the National Technical University "Kharkov Polytechnic Institute" (economic sciences), (4), 112-116. http://es.khpi.edu.ua/article/view/231982
  • Obermeyer, Z., Powers, B., Vogeli, C., & Mullainathan, S. (2019). Dissecting racial bias in an algorithm used to manage the health of populations. Science , 366 (6464), 447–453.
  • OECD. (2019). OECD principles on artificial intelligence. https://www.oecd.org/going-digital/ai/principles/ .
  • Özkan, K. D. (2020). Bilişim Teknolojilerinin Gelişimi ve Veri Madenciliği Işığında Bir Gelecek İnşası: Black Mirror Dizisi Örneği . Yeni Medya , 2020 (8) , 41-65 . Retrieved from https://dergipark.org.tr/tr/pub/yenimedya/issue/56548/748649
  • Pathways for Prosperity. (2019). Digital diplomacy: technology governance for developing countries. Pathways for Prosperity Commission on Technology and Inclusive Development . https://pathwayscommission.bsg.ox.ac.uk/sites/default/files/2019-10/Digital-Diplomacy.pdf .
  • Rhee, J. (2018). The robotic imaginary: The human and the price of dehumanized labor. Minneapolis: University of Minnesota Press.
  • Ricaurte, P. (2019). Data epistemologies, the coloniality of power, and resistance. Television & New Media , 20 (4), 350–365.
  • Richardson, R., Schultz, J., & Crawford, K. (2019). Dirty data, bad predictions: how civil rights violations impact police data, predictive policing systems and justice. New York University Law Review Online, Forthcoming.
  • Rogers, EM (2001). The Digital Divide. Convergence, 7(4), 96–111. https://doi.org/10.1177/135485650100700406
  • Sap, M., Card, D., Gabriel, S., Choi, Y., & Smith, NA (2019). The risk of racial bias in hate speech detection. In Proceedings of the 57th annual meeting of the association for computational linguistics, pp 1668–1678 .
  • Stark, L. (2019). Facial recognition is the plutonium of AI. XRDS: Crossroads. The ACM Magazine for Students , 25 (3), 50–55.
  • Taylor, E. (2016). Groups and Oppression. Hypatia , 31 (3), 520–536.
  • Tellan, T. (2020). Duyarlı Makine: Yapay Zekanın Olgunluk Çağı . Yeni Medya , 2020 (9), 142-146. https://dergipark.org.tr/tr/pub/yenimedya/issue/58796/831469
  • Thrush, C. (2008). American curiosity: cultures of natural history in the colonial British Atlantic world. Environmental History , 13 (3), 573.
  • Toesland Finbar (2018) Five tech solutions to global problems, Raconteur, https://www.raconteur.net/technology/tech-solutions-global-problems/
  • UK National Health Service. (2019). Code of conduct for data-driven health and care technology.
  • Van de Poel, I., & Kroes, P. (2014). Can technology embody values?. In The moral status of technical artefacts (pp. 103–124). Berlin: Springer.
  • van der Linden, H. (2015). Drone warfare and just war theory. M. Cohn (Ed.), Drones and targeted Killing: Legal, moral and geopolitical issues (216-260 ss.). Massachusetts: Olive Branch Press.
  • Varshney Kush R., Mojsilovic Aleksandra (2019) Open Platforms for Artificial Intelligence for Social Good: Common Patterns as a Pathway to True Impact, Computers and Society, https://arxiv.org/abs/1905.11519
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Details

Primary Language English
Journal Section Review Article
Authors

Ahmet Efe 0000-0002-2691-7517

Publication Date December 29, 2022
Submission Date July 21, 2022
Published in Issue Year 2022 Issue: 13

Cite

APA Efe, A. (2022). The Impact of Artificial Intelligence on Social Problems and Solutions: An Analysis on The Context of Digital Divide and Exploitation. Yeni Medya, 2022(13), 247-264. https://doi.org/10.55609/yenimedya.1146586

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