Inteligencia artificial sostenible y evaluación ética constructiva

Antonio Luis  Terrones Rodríguez

doi:10.3989/isegoria.2022.67.10

Autores/as

Antonio Luis Terrones Rodríguez Universitat de Valencia / Instituto de Filosofía-CSIC https://orcid.org/0000-0002-4015-8537

DOI:

https://doi.org/10.3989/isegoria.2022.67.10

Palabras clave:

Inteligencia artificial, ética, sostenibilidad, evaluación tecnológica, democracia

Resumen

El aumento considerable de la capacidad de la inteligencia artificial (IA) implica un alto consumo de recursos energéticos. La situación ambiental actual, caracterizada por la acuciante degradación de ecosistemas y la ruptura del equilibrio, exige tomar medidas en diversos ámbitos. La IA no puede quedar al margen, y aunque es empleada para objetivos de sostenibilidad, debe plantearse como sostenible en términos integrales. La propuesta de una inteligencia artificial sostenible se argumenta a partir de una evaluación ética constructiva, donde la inclusión y la participación de los grupos de interés representan dos elementos fundamentales.

Descargas

Los datos de descargas todavía no están disponibles.

Citas

Abels, G. y Bora, A., "Ethics and Public Participation in Technology Assessment", [Inédito], 2016. https://pub.uni-bielefeld.de/record/2905695

Ammanath, B., Jarvis, D. y Hupfer, S., "Thriving in the era of pervasive AI", Deloitte, 2020. https://www2.deloitte.com/xe/en/insights/focus/cognitive-technologies/state-of-ai-and-intelligent-automation-in-business-survey0.html

Andrae, A. S. G., "Hypotheses for Primary Energy Use, Electricity Use and CΟ2 Emissions of Global Computing and Its Shares of the Total Between 2020 and 2030", WSEAS Transactions on Power Systems, 15, 2020 (pp. 50-59). https://doi.org/10.37394/232016.2020.15.6

Andrae, A. S. G., "New perspectives on Internet electricity use in 2030", Engineering and Applied Science Letters, 3(2), 2020 (pp. 19-31).

Allen, C., Smith, I. y Wallach, W., "Artificial morality: Top-down, bottom-up, and hybrid approaches", Ethics and Information Technology, 7, 2005 (pp. 149-155). https://doi.org/10.1007/s10676-006-0004-4

Almeida, D., Shmarko, K. y Lomas, E., "The ethics of facial recognition technologies, surveillance, and accountability in an age of artificial intelligence: a comparative analysis of US, EU, and UK regulatory frameworks", AI and Ethics, 2(3), 2021 (pp. 377-387). https://doi.org/10.1007/s43681-021-00077-w PMid:34790955 PMCid:PMC8320316

Ben-Eli, M, Sustainability: Definition and five core principles. A New Framework, New York: The Sustainability Laboratory, 2015. http://www.sustainabilitylabs.org/assets/img/SL5CorePrinciples.pdf

Belkhir, L. y Elmeligi, A., "Assessing ICT global emissions footprint: Trends to 2040 & recommendations", Journal of Cleaner Production, 177, 2018 (pp. 448-463). https://doi.org/10.1016/j.jclepro.2017.12.239

Berberich, N., Nishida, T. y Suzuki, S., "Harmonizing Artificial Intelligence for Social Good", Philosophy & Technology, 33, 2020 (pp. 613-638). https://doi.org/10.1007/s13347-020-00421-8

Bijker, W., Hughes, T. y Pinch T., The Social Construction of Technological Systems. New Directions in the Sociology and History of Technolocial Systems, Cambridge, MA, MIT Press, 1987.

Bimber, B. A., The politics of expertise in congress: The rise and fall of the office of technology assessment, Albany: State University of New York Press, 1996.

Bostrom, N y Yudkowsky, E., "The Ethics of Artificial Intelligence", en Ramsey W. y Frankish, Cambridge Hankbook of Artificial Intelligence, Cambridge, England, Cambridge University Press, 2011 (pp. 316-334). https://doi.org/10.1017/CBO9781139046855.020

Coeckelbergh, M., "AI for climate: freedom, justice, and other ethical and political challenges", AI and Ethics, 1, 2021 (pp. 67-72). https://doi.org/10.1007/s43681-020-00007-2

Comisión Europea, Horizon 2020. El Programa Marco de Investigación e Innovación de la Unión Europea, Luxemburgo, Oficina de Publicaciones de la Unión Europea, 2014. https://ec.europa.eu/programmes/horizon2020/sites/horizon2020/files/H2020_ES_KI0213413ESN.pdf

Comisión Europea, White Paper on Citizen Science in Europe, 2015. https://ec.europa.eu/futurium/en/system/files/ged/socientize_white_paper_on_citizen_science.pdf

Comisión Europea, Un Pacto Verde Europeo, 2019. https://eur-lex.europa.eu/legal-content/ESTXT/?qid=1576150542719&uri=COM%3A2019%3A640%3AFIN

Crawford, K. y Joler, V., Anatomy of an AI System. The Amazon Echo as an anatomical map of human labor, data and planetary resources, 2018. https://anatomyof.ai/index.html

Crutzen, P. J., "The 'Anthropocen'", en Ehlers, E. y Krafft, T., Earth System science in the anthropocene, Berlin, Springer, 2006 (pp. 13-18). https://doi.org/10.1007/3-540-26590-2_3

Floridi, L., Cowls, J., Beltrametti, M., Chatila, R., Chazerand, P., Dignum, V., Luetge, C., Madelin, R., Pagallo, U., Rossi, F., Schafer, B., Valcke, P. y Vayena, E., "AI4People -An Ethical Framework for a Good AI Society: Opportunities, Risks, Principles, and Recommendations", Minds and Machines, 28, 2018 (pp. 689-707). https://doi.org/10.1007/s11023-018-9482-5 PMid:30930541 PMCid:PMC6404626

González Esteban, E. y Calvo, P., "Ethically governing artificial intelligence in the field of scientific research and innovation", Heliyon, 8(2), 2022 (pp. 1-9). https://doi.org/10.1016/j.heliyon.2022.e08946 PMid:35243068 PMCid:PMC8860912

Greenpeace, Clicking Clean: Who is Winning the Race to Build a Green Internet, 2017. http://www.clickclean.org/

Grunwald, A., "Technology Assessment for Responsible Innovation", en van den Hoven, J., Doorn, N., Swierstra, T., Koops, B.-J. y Jomijn, H., Responsible Innovation 1: Innovate Solutions for Global Issues, New York, United States: Springer, 2014 (pp. 15-31).

Grunwald, A., "The inherently democratic nature of technology assessment", Science and Public Policy, 46(5), 2019 (pp. 702-709). https://doi.org/10.1093/scipol/scz023

Gunkel, D. J. y Bryson, J. "Introduction to the Special Issue on Machine Morality: The Machine as Moral Agent and Patient", Philosophy & Technology, 27, 2014 (pp. 5-8). https://doi.org/10.1007/s13347-014-0151-1

Hennen, L., "Why do we still need participatory technology assessment?", Poiesis Prax, 9, 2012 (pp. 27-41). https://doi.org/10.1007/s10202-012-0122-5 PMid:23204994 PMCid:PMC3510387

ITU-International Telecommunication Union, Frontier technologies to protect the environment and tackle climate change, 2020. https://www.itu.int/en/action/environment-and-climate-change/Documents/frontier-technologies-to-protect-the-environment-and-tackle-climate-change.pdf.

Jonas, H. El principio de responsabilidad: ensayo de una ética para la civilización tecnológica. Barcelona, Herder Editorial, 2004.

Kazim, E. y Koshiyama, A., "The interrelation between data and AI ethics in the context of impact assessments", AI and Ethics, 1, 2021 (pp. 219-225). https://doi.org/10.1007/s43681-020-00029-w

Kartha, S.; Siebert, C.K; Mathur, R.; Nakicenovic, N.; Ramanathan, V.; Rockström, J.; Schellnhuber, H.J; Srivastava, L.; Watt, R., A Copenhagen Prognosis: Towards a safe climate future. Report by the Potsdam Institute for Climate Impact Research, Sto-ckholm Environment Institute, and The Energy and Resources Institute, 2009. https://mediamanager.sei.org/documents/Publications/Climate-mitigation-adaptation/a20copenhagen20prognosis.pdf

Konrad, K., Rip, A. y Schulze Greiving, V"Constructive Technology Assessment-STS for and with Technology Actors", EASST Review, 36(3), 2017. https://easst.net/article/constructive-technology-assessment-sts-for-and-with-technology-actors/

Lacoste, A., Luccione, A., Schmidt, V. y Dandres, T., Quantifying the Carbon Emisions of Machine Learning, 2019. https://arxiv.org/abs/1910.09700v2

Microsoft, AI for Earth, 2018. https://www.microsoft.com/en-us/ai/ai-for-earth

Monasterio Astobiza, A., "Inteligencia Artificial para el bien común (AI4SG): IA y los Objetivos de Desarrollo Sostenible", Arbor, 197(802), 2021 (pp. 1-19). https://doi.org/10.3989/arbor.2021.802007

Monasterio Astobiza, A., Toboso, M., Aparicio, M. y López, D., "AI Ethics for Sustainable Development Goals", IEEE Technology and Society Magazine, 40(2), 2021 (pp. 66-71). https://doi.org/10.1109/MTS.2021.3056294

Mosco, V., To the Cloud: Big Data in a Turbulent World, Boulder, Paradigm, 2014.

Nilsson J. N., Inteligencia artificial: una nueva síntesis. Madrid: McGraw-Hill, 2001.

Organización de Naciones Unidas, Objetivos de Desarrollo Sostenible, 2015. https://www.undp.org/content/undp/es/home/sustainable-development-goals.html

Parikka, J., A Geology of Media, Minneapolis, University Of Minnesota Press, 2015. https://doi.org/10.5749/minnesota/9780816695515.001.0001

Patterson, D., Gonzalez, J., Le, Q., Liang, C., Munguia, L.-M., Rothchild, D., So, D., Texier, M. y Dean, J., Carbon Emissions and Large Neural Network Training, 2021. https://arxiv.org/abs/2104.10350

Rip, A., van del Belt, H. y Schwarz, M., "Theoretische Analyses", en Daey Ouwens, C., van Hoogstraten, P., Jelsma, J., Prakke, F. and Rip, A., Constructief Technologisch Aspectenonderzoek, Een Verkenning, Den Haag, Staatsuitgeverij, 1987 (pp. 14-29)

Rip. A., Misa, T. y Schot, J., Managing Technology in Society. The Approach of Constructive Technology Assessment, London: Thomson Learning, 1995.

Rip, A. y Robinson, D. R. R., "Constructive Technology Assessment and the Methodology of Insertion", en Neelke, D., Daan, S., Ibo, P. y Michael E. G., Early engagement and new technologies: Opening up the laboratory, Springer, 2013 (pp. 37-53). https://doi.org/10.1007/978-94-007-7844-3_3

Robbins, S., "A Misdirected Principle with a Catch: Explicability for AI", Minds and Machines, 29, 2019 (pp. 495-514). https://doi.org/10.1007/s11023-019-09509-3

Rolnick, D., Donti, P. L., Haack, L. H., Kochanski, K., Lacoste, A., Sankaran, K., Slavin Ross, A., Milojevic-Dupont, N., Jaques, N., Waldman-Brown, Luccioni, A., Maharaj, T., Sherwin, E. D., Mukkavilli, K., Kording, K. P., Gomes, C., Ng, A. Y., Hassabis, D., Platt, J. C., Creutzig, F., Chayes, J. y Bengio, Y., Tackling Climate Change with Machine Learning, 2019. https://arxiv.org/abs/1906.05433

Sartori, L. y Theodorou, A., "A sociotechnical perspective for the future of AI: narratives, inequalities, and human control", Ethics and Information Technology, 24(4), 2022 (pp. 1-11). https://doi.org/10.1007/s10676-022-09624-3

Schot, J. y Rip, A., "The Past and Future of Constructive Technology Assessment", Technological Forecasting and Social Change, 54, 1997 (pp. 251-268). https://doi.org/10.1016/S0040-1625(96)00180-1

Schwab, K., La cuarta revolución industrial. Barcelona: Debate, 2016.

Schwartz, R., Dodge, J., Smith, N. A. y Etzioni, O., Green AI, 2019. https://arxiv.org/abs/1907.10597

Skeem, J. L. y Lowenkamp Ch., "Risk, Race, and Recidivism. Predictive Bias and Disparate Impact", Criminology, 54(4), 2016 (pp. 680-712). https://doi.org/10.1111/1745-9125.12123

Solomon, S., D. Quin, M. Manning, Z. Chen, M. Marquis, K.B. Averyt, M. Tignor y H.L. Miller, Climate Change 2007 - The Physical Science Basis, Cambridge, United Kingdom and New York, NY, USA, Cambridge University Press, 2007.

Steffen, W., Richardson, K., Rockström, J., Cornell, S. E., Fetzer, I., Bennett, E. M., Biggs, R., Carpenter, S. T., de Vries, W., de Wit, C. A., Foke, C., Gerten, D., Heinke, J., Mace, G. M., Persson, L. M., Ramanathan, V., Reyers, B. y Sörlin, S., "Planetary boundaries: Guiding human development on a changing planet", Science, 349(6254), 2015 (pp. 1286-1287). https://doi.org/10.1126/science.1259855 PMid:25592418

Stoddart, H., Schneeberger, K., Dodds, F., Shaw, A., Bottero, M., Cornforth, J. y White, R., "A pocket guide to sustainable development governance", Stakeholder Forum 2011, 2011.

Strubell, E., Ganesh, A. y McCallum A., "Energy and Policy Considerations for Deep Learning in NLP", in 57th Annual Meeting of the Association for Computational Linguistics (ACL). Florence, Italy. July 2019. https://arxiv.org/abs/1906.02243v1 https://doi.org/10.18653/v1/P19-1355

Terrones Rodríguez, A. L., "Inteligencia artificial, responsabilidad y compromiso cívico y democrático", Revista Iberoamericana de Ciencia, Tecnología y Sociedad, 44(15), 2020 (pp. 253-276).

Van Wynsberghe, A., "Sustainable AI: AI for sustainability and the sustainability of AI", AI and Ethics, 1, 2021 (pp. 213-218). https://doi.org/10.1007/s43681-021-00043-6

Wolff Anthony, L. F., Kanding, B. y Selvan, R., "Carbontracker: Tracking and Predicting the Carbon Footprint of Training Deep Learning Models", Challenges in Deploying and monitoring Machine Learning Systems, 2020. https://arxiv.org/abs/2007.03051

World Meteorological Organization, WHO Statement on the State of the Global Climate in 2019, 2020. https://library.wmo.int/index.php?lvl=notice_display&id=21704#.YQe0Po4zZPY