top of page

References:                

1. Open Mind. (2017, enero 20). El comienzo de la era de la Inteligencia Artificial. Extraído de https://www.bbvaopenmind.com/tecnologia/inteligencia-artificial/el-comienzo-de-la-era-de-la-inteligencia-artificial/  

 

2. Future of Life Institute, (n.d.) Asilomar AI Principles. Extraído de https://futureoflife.org/ai-principles/

 

3. Consejo de Estado República Popular de China (2017, Julio 8). China’s next Generation Artificial Intelligence Development Plan. Extraído de http://www.gov.cn/zhengce/content/2017-07/20/content_5211996.htm

 

4. Ovanesso_A. y Plastino E. (2016). Cómo la inteligencia artificial puede generar crecimiento en Sudamérica. Extraído de https://www.accenture.com/_acnmedia/pdf-49/accenture-como-la-ia-puede-generar-crecimiento-en-sudamerica.pdf

 

5. Reisinger, R. (2019, enero 19). A.I. Expert Says Automation Could Replace 40% of Jobs in 15 Years. Extraído de https://fortune.com/2019/01/10/automation-replace-jobs/

 

6. IEE Computational Intelligence Society (n.d.) IEEE Transactions on Neural Networks and Learning Systems. Extraído de https://cis.ieee.org  

 

7. Science Daily (n.d.) Artificial Intelligence Terms. Extraído de https://www.sciencedaily.com/terms/artificial_intelligence.htm 

 

8. Burkov A. (2019). The Hundred-Page Machine Learning Book. Extraído de https://leanpub.com/theMLbook

 

9. Techopedia (n.d.). The Ultimate Guide to Applying AI in Business / AI Terms. Extraído de https://www.techopedia.com/what-most-people-dont-understand-about-ai-and-the-ultimate-guide-to-applying-it-in-business/2/34057

 

10. Woirol, G.R. (1996). The Technological Unemployment and Structural Unemployment Debates. Extraído de https://books.google.com.do/books/about/The_Technological_Unemployment_and_Struc.html?id=KorYAAAAIAAJ&redir_esc=y

 

11. Harari, Y.N. (2019). 21 Lessons for the 21st Century. NYC, NY:Spiegel & Grau

12. IEE Explore Digital Library (n.d.). Safety Benefits of Forward Collision Warning, Brake Assist, and Autonomous Braking Systems in Rear-End Collisions. Extraído de https://ieeexplore.ieee.org/document/6180219 

 

13. McKinsey Global Institute. (2017, diciembre). Jobs Lost, Jobs Gained: Workforce Transitions In A Time Of Automation. Extraído de https://www.mckinsey.com/~/media/mckinsey/featured%20insights/future%20of%20organizations/what%20the%20future%20of%20work%20will%20mean%20for%20jobs%20skills%20and%20wages/mgi%20jobs%20lost-jobs%20gained_report_december%202017.ashx

 

14. Baxter, M. (2018, noviembre 28). AI won’t destroy jobs it will transform them. Extraído de https://www.information-age.com/ai-wont-destroy-jobs-123476901/

 

15. World Economic Forum. (2018, septiembre 17). Machines Will Do More Tasks Than Humans by 2025 but Robot Revolution Will Still Create 58 Million Net New Jobs in Next Five Years. Extraído de https://www.weforum.org/press/2018/09/machines-will-do-more-tasks-than-humans-by-2025-but-robot-revolution-will-still-create-58-million-net-new-jobs-in-next-five-years/

 

16. Diéz Díaz, F. (n.d.). CTIC Inteligencia Artificial y Big Data. Exraído de https://www.fundacionctic.org/es/tecnologias/inteligencia-artificial-y-big-data

 

17. Infobae. (2019, septiembre 7). Inteligencia artificial y Big Data: ¿Estamos preparados para la revolución digital?. Extraído de https://www.infobae.com/def/desarrollo/2019/09/07/inteligencia-artificial-y-big-data-estamos-preparados-para-la-revolucion-digital/

 

18. Rouse, M. (n.d.) Search Data Center: Internet de las cosas (IoT). Exrtaído de https://searchdatacenter.techtarget.com/es/definicion/Internet-de-las-cosas-IoT

 

19.  Open Mind. (2017, julio 18). Por qué Internet de las cosas necesita inteligencia artificial. Extraído de https://www.bbvaopenmind.com/tecnologia/mundo-digital/por-que-internet-de-las-cosas-necesita-inteligencia-artificial/

 

20. Khosla, V. (2014, noviembnre 6). The Next Technology Revolution Will Drive Abundance And Income Disparity. Extraído de https://www.forbes.com/sites/valleyvoices/2014/11/06/the-next-technology-revolution-will-drive-abundance-and-income-disparity/#12ac52cf1882

 

21. Eric A. Posner & E. Glen Weyl. (n.d.). Data as Labor. Extraído de http://radicalmarkets.com/chapters/data-as-labor/

 

22. Mazzucato, M. (2018, junio 27). Let’s make private data into a public good. Ectraído de https://www.technologyreview.com/s/611489/lets-make-private-data-into-a-public-good/amp/

 

23. Khan, F. (2018, noviembre 19). Data As Labor: Rethinking Jobs In The Information Age. Extraído de https://blog.singularitynet.io/data-as-labour-cfed2e2dc0d4

 

24. Andreu Perez, J., Deligianni, F., Ravi, D. y Yang, G. (n.d) Artificial Intelligence and Robotics. Extraído de https://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=10&ved=2ahUKEwjXmfGMh4vlAhUxVt8KHdyBAwIQFjAJegQIARAC&url=https%3A%2F%2Farxiv.org%2Fpdf%2F1803.10813&usg=AOvVaw3yP4Drn9YadDnDEVPCEowF  

 

25. Raghavan, M., Barocas, S., Kleinberg, J.M., Levy, K. (2019). Mitigating Bias in Algorithmic Employment Screening: Evaluating Claims and Practices. Extraído de https://www.semanticscholar.org/paper/Mitigating-Bias-in-Algorithmic-Employment-Claims-Raghavan-Barocas/aca38d20800f70e10d2e233511e83ee2aa994685

 

26. McCorduck, P. (2004). Machines Who Think: A Personal Inquiry into the History and Prospects of Artificial Intelligence. Extraído de https://monoskop.org/images/1/1e/McCorduck_Pamela_Machines_Who_Think_2nd_ed.pdf

 

27. Organización de los Estados Americanos Comisión Interamericana de Derechos Humanos. (2005, abril 15).  Caso 12.189 Dilcia Vean y Violeta Bosico República Dominicana. ALEGATOS FINALES ESCRITOS DE LA CIDH. Extraído de https://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=1&ved=2ahUKEwi_iqrd9PHkAhVLbKwKHS6zC0AQFjAAegQIABAC&url=http%3A%2F%2Fwww.corteidh.or.cr%2Fdocs%2Fcasos%2Fyeanbosi%2Fal_cidh.pdf&usg=AOvVaw2It4xHbSeqzUHX-LoLg_rA

 

28. International Telecommunication Union (2019). United Nations Activities on Artificial Intelligence (AI). Extraído de https://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=1&ved=2ahUKEwj3qJHk38TlAhUSVa0KHSmmDUoQFjAAegQIARAC&url=https%3A%2F%2Fwww.itu.int%2Fdms_pub%2Fitu-s%2Fopb%2Fgen%2FS-GEN-UNACT-2019-1-PDF-E.pdf&usg=AOvVaw0vy3YGUGMkYwgOvlslujJM

29. Selfridge, P., Ferose, VR y Kumar, A. (2018, octubre 24). From Digital Government To Intelligent Government Extraído de https://www.digitalistmag.com/digital-economy/2018/10/24/from-digital-government-to-intelligent-government-06191223

 

30. Ng, A. (2018, diciembre 13). AI Transformation Playbook: How to lead your company into the AI era. Extraído de https://landing.ai/ai-transformation-playbook/

Otros recursos:

Compilación de Estrategias Nacionales de Inteligencia Artificial

Buolamwini, J. y Gebru T. (2018). Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification. Extraído de http://proceedings.mlr.press/v81/buolamwini18a.html 

Cave S. y S Óh Éigeartaigh, S. (2018). An AI Race for Strategic Advantage: Rhetoric and Risks. Extraído de https://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=3&ved=2ahUKEwi2282a64zlAhVQT6wKHUaaBLUQFjACegQIBBAC&url=http%3A%2F%2Fwww.aies-conference.com%2F2018%2Fcontents%2Fpapers%2Fmain%2FAIES_2018_paper_163.pdf&usg=AOvVaw2s2VOGyu6tA9OnGrQ-9nKZ 

 

Chouldechova, A., Benavides-Prado, D., et.al. (2018). A case study of algorithm-assisted decision making in child maltreatment hotline screening decisions. Extraído de http://proceedings.mlr.press/v81/chouldechova18a.html 

 

Domingos, P. (13 de febrero de 2018). The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World Instrumentation & Measurement Society

 

Gebru, T., Morgenstern,J., et.al. (2019, abril 14). Datasheets for Datasets. Extraído de https://arxiv.org/abs/1803.09010 

 

Hao, K. (n.d.). Mit Technology Review. https://www.technologyreview.com/profile/karen-hao/ 

Hutchinson, B. y Mitchell, M. 50 Years of Test (Un)fairness: Lessons for Machine Learning. Extraído de  https://arxiv.org/abs/1811.10104 

Instrumentation & Mnagement Society - IEEEE. (2017, octubre 19). Society Conferences Management Guidelines. Extraído de (https://ieeexplore.ieee.org/abstract/document/8662743)

 

Iyer, R., Yuezhang, L., et.al. (2018, septiembre 17) Transparency and Explanation in Deep Reinforcement Learning Neural Networks. Extraído de https://arxiv.org/abs/1809.06061 

 ​ 

Liu, L.T., Dean, S., Rolf, E., Simchowitz, M. y Hardt, M. Delayed (2018, abril 8) Impact of Fair Machine Learning. Extraído de https://arxiv.org/abs/1803.04383 

Mannino, A., Althaus, D., Erhardt, J., Gloor, L., Hutter, A. and Metzinger, T. (2015, diciembre 12). Artificial Intelligence: Opportunities and Risks. Extraído de (p.3https://pdfs.semanticscholar.org/382d/37d735826af173e9e9eebcaf7c1aff1fb9e6.pdf)>

MIT Media Lab. (n.d.) Artificial Intelligence Inclusion. Extraído de https://aiandinclusion.org/

 

Mitchell, M., Wu, s., et.al. (2019, enero 14). Model Cards for Model Reporting. Extraído de https://arxiv.org/abs/1810.03993 

Selbst, A.D., Boyd, D., Friedler, S., Venkatasubramanian, S., y Vertesi J. (2018, diciembre 5). Fairness and Abstraction in Sociotechnical Systems. Extraído de https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3265913 


Valera, I., Singla, A., Gomez Rodriguez, M. (2018, mayo 25). Enhancing the Accuracy and Fairness of Human Decision Making Extraído de https://arxiv.org/abs/1805.10318

 

Websites:

 

University of San Francisco Applied Data Ethics: https://www.usfca.edu/data-institute/initiatives/center-applied-data-ethics

 

AI Readiness: https://www.oxfordinsights.com/ai-readiness2019

 

Asilomar AI Principles: https://futureoflife.org/ai-principles/  

Global Catastrophic Risks editado por Nick Bostrom y Milan Cirković: https://www.researchgate.net/publication/23784677_Global_Catastrophic_Risks_edited_by_Nick_Bostrom_Milan_Cirkovic 

 

Osonde Ope Osoba: https://twimlai.com/twiml-talk-192-ai-ethics-strategic-decisioning-and-game-theory-with-osonde-osoba/ 

Podcasts:

 

Lex Friedman

https://lexfridman.com/ai/

 

NVIDIA The AI Podcast

https://blogs.nvidia.com/ai-podcast/

Download

PDF

AI Regional Strategy

bottom of page