Papers

Export 11 results:
Filters: First Letter Of Last Name is P  [Clear All Filters]
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z 
A
Pennisi, E. (2017). AI in Action: Combing the genome for the roots of autism. Science, 357(6346), 25 - 25. https://doi.org/10.1126/science.357.6346.25
Garvey, C. (2018). AI risk mitigation through democratic governance (J. Furman, Marchant, G., Price, H., & Rossi, F., Trans.). In the 2018 AAAI/ACM ConferenceProceedings of the 2018 AAAI/ACM Conference on AI, Ethics, and Society - AIES '18 (366 - 367). https://doi.org/10.1145/3278721.3278801
Petridis, S., Diakopoulos, N., Crowston, K., Hansen, M., Henderson, K., Jastrzebski, S., et al.. (2023). AngleKindling: Supporting Journalistic Angle Ideation with Large Language Models. In Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems. https://doi.org/10.1145/3544548.3580907
Iliadis, L., Maglogiannis, I., & Plagianakos, V.. (2018). Artificial Intelligence Applications and Innovations. In 14th IFIP WG 12.5 International Conference, AIAI 2018. Presented at the 14th IFIP WG 12.5 International Conference, AIAI 2018. Retrieved de https://www.springer.com/gp/book/9783319920153
Kelley, K. H., Fontanetta, L. M., Heintzman, M., & Pereira, N.. (2018). Artificial intelligence: Implications for social inflation and insurance. Risk Management And Insurance Review, 21(3), 373 - 387. https://doi.org/10.1111/rmir.12111
Musib, M., Wang, F., Tarselli, M. A., Yoho, R., Yu, K. - H., Andrés, R. Medina, et al.. (2017). Artificial intelligence in research. Science, 357(6346), 28 - 30. https://doi.org/10.1126/science.357.6346.28
Panch, T., Szolovits, P., & Atun, R.. (2018). Artificial intelligence, machine learning and health systems. Journal Of Global Health, 8(2). https://doi.org/10.7189/jogh.08.020303
B
Parker, S. K. (2014). Beyond motivation: Job and work design for development, health, ambidexterity, and more. Annual Review Of Psychology, 65(1), 661 - 691. https://doi.org/10.1146/annurev-psych-010213-115208
Bednarek, A. T., Wyborn, C., Cvitanovic, C., Meyer, R., Colvin, R. M., Addison, P. F. E., et al.. (2018). Boundary spanning at the science–policy interface: the practitioners’ perspectives. Sustainability Science, 13(4), 1175 - 1183. https://doi.org/10.1007/s11625-018-0550-9
Bednarek, A. T., Wyborn, C., Cvitanovic, C., Meyer, R., Colvin, R. M., Addison, P. F. E., et al.. (2018). Boundary spanning at the science–policy interface: the practitioners’ perspectives. Sustainability Science, 13(4), 1175 - 1183. https://doi.org/10.1007/s11625-018-0550-9
C
Pratt, G. A. (2015). Is a Cambrian Explosion Coming for Robotics?. Journal Of Economic Perspectives, 29(3), 51 - 60. https://doi.org/10.1257/jep.29.3.51
Pepito, J. Andrew, & Locsin, R.. (2019). Can nurses remain relevant in a technologically advanced future?. International Journal Of Nursing Sciences, 6(1), 106 - 110. https://doi.org/10.1016/j.ijnss.2018.09.013
Woods, D. D., Patterson, E. S., & Roth, E. M.. (2002). Can we ever escape from data overload? A cognitive systems diagnosis. Cognition, Technology & Work, 4(1), 22 - 36. https://doi.org/10.1007/s101110200002
Aragon, C. R., Poon, S., & Silva, C. T.. (2009). The changing face of digital science (D. R. Olsen, Arthur, R. B., Hinckley, K., Morris, M. Ringel, Hudson, S., & Greenberg, S., Trans.). In the 27th international conference extended abstractsProceedings of the 27th international conference extended abstracts on Human factors in computing systems - CHI EA '09 (4819). https://doi.org/10.1145/1520340.1520749

Pages