Incidencia de los principios éticos en el uso de la inteligencia artificial a nivel global.

El artículo destaca la importancia de incorporar principios éticos en el desarrollo y uso de la inteligencia artificial (IA), considerando su creciente influencia en sectores clave como la salud, transporte y negocios. Aunque la IA aún no tiene conciencia humana, sus capacidades de automatización y...

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Autores:
Sanclemente Capacho, Andres Camilo
Tipo de recurso:
Trabajo de grado de pregrado
Fecha de publicación:
2025
Institución:
Universidad Libre
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RIU - Repositorio Institucional UniLibre
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OAI Identifier:
oai:repository.unilibre.edu.co:10901/30483
Acceso en línea:
https://hdl.handle.net/10901/30483
Palabra clave:
Inteligencia Artificial (IA)
Principios éticos
Derechos humanos
Estándares éticos
Responsabilidad
Transparencia
Regulación
educación
Artificial Intelligence (AI)
Ethical principles
Human rights
Ethical standards
Responsibility
Transparency
Regulation
Education
Inteligencia artificial
Rights
openAccess
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http://creativecommons.org/licenses/by-nc-nd/2.5/co/
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dc.title.spa.fl_str_mv Incidencia de los principios éticos en el uso de la inteligencia artificial a nivel global.
dc.title.alternative.spa.fl_str_mv Impact of ethical principles in the use of artificial intelligence at a global level
title Incidencia de los principios éticos en el uso de la inteligencia artificial a nivel global.
spellingShingle Incidencia de los principios éticos en el uso de la inteligencia artificial a nivel global.
Inteligencia Artificial (IA)
Principios éticos
Derechos humanos
Estándares éticos
Responsabilidad
Transparencia
Regulación
educación
Artificial Intelligence (AI)
Ethical principles
Human rights
Ethical standards
Responsibility
Transparency
Regulation
Education
Inteligencia artificial
title_short Incidencia de los principios éticos en el uso de la inteligencia artificial a nivel global.
title_full Incidencia de los principios éticos en el uso de la inteligencia artificial a nivel global.
title_fullStr Incidencia de los principios éticos en el uso de la inteligencia artificial a nivel global.
title_full_unstemmed Incidencia de los principios éticos en el uso de la inteligencia artificial a nivel global.
title_sort Incidencia de los principios éticos en el uso de la inteligencia artificial a nivel global.
dc.creator.fl_str_mv Sanclemente Capacho, Andres Camilo
dc.contributor.advisor.none.fl_str_mv Villamizar Estrada, Avilio
dc.contributor.author.none.fl_str_mv Sanclemente Capacho, Andres Camilo
dc.subject.spa.fl_str_mv Inteligencia Artificial (IA)
Principios éticos
Derechos humanos
Estándares éticos
Responsabilidad
Transparencia
Regulación
educación
topic Inteligencia Artificial (IA)
Principios éticos
Derechos humanos
Estándares éticos
Responsabilidad
Transparencia
Regulación
educación
Artificial Intelligence (AI)
Ethical principles
Human rights
Ethical standards
Responsibility
Transparency
Regulation
Education
Inteligencia artificial
dc.subject.subjectenglish.spa.fl_str_mv Artificial Intelligence (AI)
Ethical principles
Human rights
Ethical standards
Responsibility
Transparency
Regulation
Education
dc.subject.lemb.spa.fl_str_mv Inteligencia artificial
description El artículo destaca la importancia de incorporar principios éticos en el desarrollo y uso de la inteligencia artificial (IA), considerando su creciente influencia en sectores clave como la salud, transporte y negocios. Aunque la IA aún no tiene conciencia humana, sus capacidades de automatización y procesamiento masivo de datos plantean desafíos éticos significativos, especialmente en temas de empleo, privacidad y justicia social. Estos desafíos requieren atención para evitar impactos negativos que afecten el bienestar de la sociedad y promuevan un uso equitativo de la tecnología. Para mitigar estos riesgos, la ética en IA se enfoca en principios como transparencia, seguridad de datos, autonomía, intencionalidad y responsabilidad, que buscan orientar la creación de sistemas imparciales y explicables. Sin embargo, problemas como la "caja negra" de algunos algoritmos y la presencia de sesgos en los datos de entrenamiento dificultan la confianza en estas tecnologías, ya que pueden perpetuar prejuicios sociales. Esto subraya la necesidad de mejorar los estándares éticos y asegurar que la IA actúe en beneficio de todos, eliminando sesgos y promoviendo decisiones justas. Gobiernos y grandes corporaciones también han comenzado a implementar marcos regulatorios, como los principios FEAT (justicia, ética, responsabilidad y transparencia), para supervisar el uso ético de la IA. Estudios de caso, como la identificación biométrica en India, resaltan tanto los beneficios como los riesgos de la IA, sugiriendo que para una IA ética se requiere regulación, educación y cooperación internacional, a fin de reducir la desigualdad y proteger los derechos humanos en un marco de gobernanza transparente.
publishDate 2025
dc.date.accessioned.none.fl_str_mv 2025-01-23T22:11:54Z
dc.date.available.none.fl_str_mv 2025-01-23T22:11:54Z
dc.date.created.none.fl_str_mv 2025-01-22
dc.type.local.spa.fl_str_mv Tesis de Pregrado
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dc.identifier.uri.none.fl_str_mv https://hdl.handle.net/10901/30483
url https://hdl.handle.net/10901/30483
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Barclay, I., Preece, A., Taylor, I., & Verma, D. (2021). Towards traceability in data ecosystems using a bill of materials model. CEUR Workshop Proceedings, 2975.
Bender, E. M., Gebru, T., McMillan-Major, A., & Shmitchell, S. (2021). On the dangers of stochastic parrots: Can language models be too big? FAccT 2021 - Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency, 610–623. https://doi.org/10.1145/3442188.3445922
Binns, R., Van Kleek, M., Veale, M., Lyngs, U., Zhao, J., & Shadbolt, N. (2018). “It’s reducing a human being to a percentage”; perceptions of justice in algorithmic decisions. Conference on Human Factors in Computing Systems - Proceedings, 2018-April. https://doi.org/10.1145/3173574.3173951
Bostrom, N., & Yudkowsky, E. (2014). The ethics of artificial intelligence. In The Cambridge handbook of artificial intelligence (pp. 316-334). Cambridge Press. doi:10.1017/CBO9781139046855.020
Bossmann, J. (2016). Top 9 ethical issues in artificial intelligence. World Economic Forum. Retrieved from https://www.weforum.org/ethical-issues-in-AI
Bradley, T. (2017). Facebook AI Creates Its Own Language In Creepy Preview of Our
Brundage, M., Avin, S., Clark, J., Toner, H., Eckersley, P., Garfinkel, B., Dafoe, A., Scharre, P., Zeitzoff, T., Filar, B., Anderson, H., Roff, H., Allen, G. C., Steinhardt, J., Flynn, C., hÉigeartaigh, S. Ó., Beard, S., Belfield, H., Farquhar, S., … Amodei, D. (2018). The Malicious Use of Artificial Intelligence: Forecasting, Prevention, and Mitigation. http://arxiv.org/abs/1802.07228
Bryson, J., & Winfield, A. (2017). Standardizing Ethical Design for Artificial Intelligence and Autonomous Systems. Computer, 50(5), 116–119. https://doi.org/10.1109/MC.2017.154
Choudhuri, R., Liu, D., Steinmacher, I., Gerosa, M., & Sarma, A. (2024). How Far Are We? The Triumphs and Trials of Generative AI in Learning Software Engineering. Proceedings of the IEEE/ACM 46th International Conference on Software Engineering, 1–13. https://doi.org/10.1145/3597503.3639201
Cramer, H., Reddy, S., Bouyer, R. T., Garcia-Gathright, J., & Springer, A. (2019). Translation, tracks & Data: An algorithmic bias effort in practice. Conference on Human Factors in Computing Systems - Proceedings. https://doi.org/10.1145/3290607.3299057
Davidson, T., Bhattacharya, D., & Weber, I. (2019). Racial Bias in Hate Speech and Abusive Language Detection Datasets. 25–35. https://doi.org/10.18653/v1/w19-3504
Diakopoulos, N. (2016). Accountability in algorithmic decision making. Communications of the ACM, 59(2), 56–62. https://doi.org/10.1145/2844110
Díaz, M., Johnson, I., Lazar, A., Piper, A. M., & Gergle, D. (2018). Addressing age-related bias in sentiment analysis. Conference on Human Factors in Computing Systems - Proceedings, 2018-April. https://doi.org/10.1145/3173574.3173986
Dawson, D., Schleiger, E., Horton, J., McLaughlin, J., Robinson, C., Quezada, G., . . . Hajkowicz, S. (2019). Artificial Intelligence: Australia’s Ethics Framework. Data61 CSIRO, Australia.
European Commission. (2019). Ethics guidelines for trustworthy AI. Retrieved from https://ec.europa.eu/digital- single-market/en/news/ethics-guidelines-trustworthy-ai
Floridi, L., Cowls, J., Beltrametti, M., Chatila, R., Chazerand, P., Dignum, V., & Vayena, E. et al. (2018). AI4People—an ethical framework for a good AI society: Opportunities, risks, principles, and recommendations. Minds and Machines, 28(4), 689–707. doi:10.1007/s11023-018-9482-5 PMID:30930541
Future of Life Institute. (2017). Asilomar AI Principles. Retrieved from https://futureoflife.org/ai-principles/?cn-reloaded=1
Hagerty, A., & Rubinov, I. (2019). Global AI Ethics: A Review of the Social Impacts and Ethical Implications of Artificial Intelligence. http://arxiv.org/abs/1907.07892
Hanna, M. (2019). We don’t need more guidelines or frameworks on ethical AI use. It’s time for regulatory action. Brink the Edge of Risk. Retrieved from https://www.brinknews.com/we-dont-need-more-guidelines-or-frameworks-on-ethical-ai-use-its-time-for-regulatory-action/Haga clic o pulse aquí para escribir texto.
Hamidi, F., Scheuerman, M. K., & Branham, S. M. (2018). Gender Recognition or Gender reductionism? The socialimplications of Automatic Gender Recognition systems. Conference on Human Factors in Computing Systems - Proceedings, 2018-April. https://doi.org/10.1145/3173574.3173582
Holstein, K., Vaughan, J. W., Daumé, H., Dudík, M., & Wallach, H. (2019). Improving fairness in machine learning systems: What do industry practitioners need? Conference on Human Factors in Computing Systems - Proceedings, 16. https://doi.org/10.1145/3290605.3300830
IAPP. (2018). White Paper -- Building Ethics into Privacy Frameworks for Big Data and AI. Retrieved from https://iapp.org/resources/article/building-ethics-into-privacy-frameworks-for-big-data-and-ai/
IEEE. (2019). Ethically aligned Design. Retrieved from https://ethicsinaction.ieee.org/
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Siau, K., & Wang, W. (2020). Artificial Intelligence (AI) Ethics: Ethics of AI and Ethical AI. https://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/JDM.2020040105, 31(2), 74–87. https://doi.org/10.4018/JDM.2020040105
Siau, K., Xi, Y., & Zou, C. (2019). Industry 4.0: Challenges and Opportunities in Different Countries. Cutter Business Technology Journal., 32(6), 6–14.
Schwartz, R., Dodge, J., Smith, N. A., & Etzioni, O. (2020). Green AI. Communications of the ACM, 63(12), 54–63. https://doi.org/10.1145/3381831
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Wang, W., & Siau, K. (2019b). Industry 4.0: Ethical and moral Predicaments. Cutter Business Technology Journal., 32(6), 36–45.
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spelling Villamizar Estrada, AvilioSanclemente Capacho, Andres CamiloCúcuta2025-01-23T22:11:54Z2025-01-23T22:11:54Z2025-01-22https://hdl.handle.net/10901/30483El artículo destaca la importancia de incorporar principios éticos en el desarrollo y uso de la inteligencia artificial (IA), considerando su creciente influencia en sectores clave como la salud, transporte y negocios. Aunque la IA aún no tiene conciencia humana, sus capacidades de automatización y procesamiento masivo de datos plantean desafíos éticos significativos, especialmente en temas de empleo, privacidad y justicia social. Estos desafíos requieren atención para evitar impactos negativos que afecten el bienestar de la sociedad y promuevan un uso equitativo de la tecnología. Para mitigar estos riesgos, la ética en IA se enfoca en principios como transparencia, seguridad de datos, autonomía, intencionalidad y responsabilidad, que buscan orientar la creación de sistemas imparciales y explicables. Sin embargo, problemas como la "caja negra" de algunos algoritmos y la presencia de sesgos en los datos de entrenamiento dificultan la confianza en estas tecnologías, ya que pueden perpetuar prejuicios sociales. Esto subraya la necesidad de mejorar los estándares éticos y asegurar que la IA actúe en beneficio de todos, eliminando sesgos y promoviendo decisiones justas. Gobiernos y grandes corporaciones también han comenzado a implementar marcos regulatorios, como los principios FEAT (justicia, ética, responsabilidad y transparencia), para supervisar el uso ético de la IA. Estudios de caso, como la identificación biométrica en India, resaltan tanto los beneficios como los riesgos de la IA, sugiriendo que para una IA ética se requiere regulación, educación y cooperación internacional, a fin de reducir la desigualdad y proteger los derechos humanos en un marco de gobernanza transparente.Universidad Libre -Ingenierías- Ingeniería en tecnologías de la investigación y las comunicacionesThe article highlights the importance of incorporating ethical principles in the development and use of artificial intelligence (AI), considering its growing influence in key sectors such as health, transportation, and business. Although AI does not yet have human consciousness, its capabilities in automation and massive data processing pose significant ethical challenges, especially in areas like employment, privacy, and social justice. These challenges require attention to prevent negative impacts that could affect society's well-being and promote an equitable use of technology. To mitigate these risks, AI ethics focuses on principles such as transparency, data security, autonomy, intentionality, and responsibility, aiming to guide the creation of impartial and explainable systems. However, issues like the "black box" of certain algorithms and the presence of biases in training data make it difficult to trust these technologies, as they may perpetuate social prejudices. This underscores the need to improve ethical standards and ensure that AI acts for the benefit of all, eliminating biases and promoting fair decisions. Governments and large corporations have also begun implementing regulatory frameworks, such as the FEAT principles (fairness, ethics, accountability, and transparency), to oversee the ethical use of AI. Case studies, such as biometric identification in India, highlight both the benefits and risks of AI, suggesting that an ethical AI requires regulation, education, and international cooperation to reduce inequality and protect human rights within a transparent governance framework.PDFhttp://creativecommons.org/licenses/by-nc-nd/2.5/co/Atribución-NoComercial-SinDerivadas 2.5 Colombiainfo:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Inteligencia Artificial (IA)Principios éticosDerechos humanosEstándares éticosResponsabilidadTransparenciaRegulacióneducaciónArtificial Intelligence (AI)Ethical principlesHuman rightsEthical standardsResponsibilityTransparencyRegulationEducationInteligencia artificialIncidencia de los principios éticos en el uso de la inteligencia artificial a nivel global.Impact of ethical principles in the use of artificial intelligence at a global levelTesis de Pregradohttp://purl.org/coar/resource_type/c_7a1finfo:eu-repo/semantics/bachelorThesisAnderson, M., & Anderson, S. L. (2007). Machine ethics: Creating an ethical intelligent agent. AI Magazine, 28(4), 15–26.Barclay, I., Preece, A., Taylor, I., & Verma, D. (2021). Towards traceability in data ecosystems using a bill of materials model. CEUR Workshop Proceedings, 2975.Bender, E. M., Gebru, T., McMillan-Major, A., & Shmitchell, S. (2021). On the dangers of stochastic parrots: Can language models be too big? FAccT 2021 - Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency, 610–623. https://doi.org/10.1145/3442188.3445922Binns, R., Van Kleek, M., Veale, M., Lyngs, U., Zhao, J., & Shadbolt, N. (2018). “It’s reducing a human being to a percentage”; perceptions of justice in algorithmic decisions. Conference on Human Factors in Computing Systems - Proceedings, 2018-April. https://doi.org/10.1145/3173574.3173951Bostrom, N., & Yudkowsky, E. (2014). The ethics of artificial intelligence. In The Cambridge handbook of artificial intelligence (pp. 316-334). Cambridge Press. doi:10.1017/CBO9781139046855.020Bossmann, J. (2016). Top 9 ethical issues in artificial intelligence. World Economic Forum. Retrieved from https://www.weforum.org/ethical-issues-in-AIBradley, T. (2017). Facebook AI Creates Its Own Language In Creepy Preview of OurBrundage, M., Avin, S., Clark, J., Toner, H., Eckersley, P., Garfinkel, B., Dafoe, A., Scharre, P., Zeitzoff, T., Filar, B., Anderson, H., Roff, H., Allen, G. C., Steinhardt, J., Flynn, C., hÉigeartaigh, S. Ó., Beard, S., Belfield, H., Farquhar, S., … Amodei, D. (2018). The Malicious Use of Artificial Intelligence: Forecasting, Prevention, and Mitigation. http://arxiv.org/abs/1802.07228Bryson, J., & Winfield, A. (2017). Standardizing Ethical Design for Artificial Intelligence and Autonomous Systems. Computer, 50(5), 116–119. https://doi.org/10.1109/MC.2017.154Choudhuri, R., Liu, D., Steinmacher, I., Gerosa, M., & Sarma, A. (2024). How Far Are We? The Triumphs and Trials of Generative AI in Learning Software Engineering. Proceedings of the IEEE/ACM 46th International Conference on Software Engineering, 1–13. https://doi.org/10.1145/3597503.3639201Cramer, H., Reddy, S., Bouyer, R. T., Garcia-Gathright, J., & Springer, A. (2019). Translation, tracks & Data: An algorithmic bias effort in practice. Conference on Human Factors in Computing Systems - Proceedings. https://doi.org/10.1145/3290607.3299057Davidson, T., Bhattacharya, D., & Weber, I. (2019). Racial Bias in Hate Speech and Abusive Language Detection Datasets. 25–35. https://doi.org/10.18653/v1/w19-3504Diakopoulos, N. (2016). Accountability in algorithmic decision making. Communications of the ACM, 59(2), 56–62. https://doi.org/10.1145/2844110Díaz, M., Johnson, I., Lazar, A., Piper, A. M., & Gergle, D. (2018). Addressing age-related bias in sentiment analysis. Conference on Human Factors in Computing Systems - Proceedings, 2018-April. https://doi.org/10.1145/3173574.3173986Dawson, D., Schleiger, E., Horton, J., McLaughlin, J., Robinson, C., Quezada, G., . . . Hajkowicz, S. (2019). Artificial Intelligence: Australia’s Ethics Framework. Data61 CSIRO, Australia.European Commission. (2019). Ethics guidelines for trustworthy AI. Retrieved from https://ec.europa.eu/digital- single-market/en/news/ethics-guidelines-trustworthy-aiFloridi, L., Cowls, J., Beltrametti, M., Chatila, R., Chazerand, P., Dignum, V., & Vayena, E. et al. (2018). AI4People—an ethical framework for a good AI society: Opportunities, risks, principles, and recommendations. Minds and Machines, 28(4), 689–707. doi:10.1007/s11023-018-9482-5 PMID:30930541Future of Life Institute. (2017). Asilomar AI Principles. Retrieved from https://futureoflife.org/ai-principles/?cn-reloaded=1Hagerty, A., & Rubinov, I. (2019). Global AI Ethics: A Review of the Social Impacts and Ethical Implications of Artificial Intelligence. http://arxiv.org/abs/1907.07892Hanna, M. (2019). We don’t need more guidelines or frameworks on ethical AI use. It’s time for regulatory action. Brink the Edge of Risk. Retrieved from https://www.brinknews.com/we-dont-need-more-guidelines-or-frameworks-on-ethical-ai-use-its-time-for-regulatory-action/Haga clic o pulse aquí para escribir texto.Hamidi, F., Scheuerman, M. K., & Branham, S. M. (2018). Gender Recognition or Gender reductionism? The socialimplications of Automatic Gender Recognition systems. Conference on Human Factors in Computing Systems - Proceedings, 2018-April. https://doi.org/10.1145/3173574.3173582Holstein, K., Vaughan, J. W., Daumé, H., Dudík, M., & Wallach, H. (2019). Improving fairness in machine learning systems: What do industry practitioners need? Conference on Human Factors in Computing Systems - Proceedings, 16. https://doi.org/10.1145/3290605.3300830IAPP. 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