Papers
. (2009). Under diagnosis and referral bias of autism in ethnic minorities. Journal Of Autism And Developmental Disorders, 39(1), 142 - 148. https://doi.org/10.1007/s10803-008-0611-5
. (2018). Understanding Chatbot-mediated Task Management (). In the 2018 CHI ConferenceProceedings of the 2018 CHI Conference on Human Factors in Computing Systems - CHI '18 (1 - 6). https://doi.org/10.1145/317357410.1145/3173574.3173632
. (2017). Understanding human-machine networks. Acm Computing Surveys, 50(1), 1 - 35. https://doi.org/10.1145/3039868
. (2018). Understanding tasks, automation, and the national health service (Vol. 10766, pp. 544 - 549; ). In (Vol. 10766, pp. 544 - 549). https://doi.org/10.1007/978-3-319-78105-1_60
. (2020). Understanding the Impact of Artificial Intelligence on Services. In International Conference on Exploring Services Science (1, 202–213). https://doi.org/10.1007/978-3-030-38724-2
. (2010). Understanding the role of occupational and organizational context. Journal Of Organizational Behavior, 31(2-3), 351 - 360. https://doi.org/10.1002/job.642
. (2019). Unsupervised by any other name: Hidden layers of knowledge production in artificial intelligence on social media. Big Data & Society, 6(1), 205395171881956. https://doi.org/10.1177/2053951718819569
. (2019). Use of Artificial Intelligence to Improve Resilience and Preparedness Against Adverse Flood Events. Water, 11(5), 973. https://doi.org/10.3390/w11050973
. (2015). Users’ reactions to actions of automated programs in Wikipedia. Computers In Human Behavior, 50, 66 - 75. https://doi.org/10.1016/j.chb.2015.03.078
. (2019). Using artificial intelligence in health-system pharmacy practice: Finding new patterns that matter. American Journal Of Health-System Pharmacy, 76(9), 622 - 627. https://doi.org/10.1093/ajhp/zxz018
. (2010). Using machine learning for network intrusion detection. Presented at the. Retrieved de http://www.icsi.berkeley.edu/pubs/networking/outsidethe10.pdf
. (2018). The value of work: Addressing the future of work through the lens of solidarity. Bioethics, 32(9), 585 - 592. https://doi.org/ 10.1111/bioe.12507
. (2020). A vulnerability analysis : Theorising the impact of artificial intelligence decision-making processes on individuals , society and human diversity from a social justice perspective. Computer Law & Security Review: The International Journal Of Technology Law And Practice, 38, 105429. https://doi.org/10.1016/j.clsr.2020.105429
. (2019). What happens when the jobs disappear?. Retrieved de https://super.journalxr.com/journal/index.php/TSJ
. (2017). What to expect from artificial intelligence. Mit Sloan Management Review , 58. Retrieved de http://ilp.mit.edu/media/news_articles/smr/2017/58311.pdf
. (2020). When machines think for us: The consequences for work and place. Cambridge Journal Of Regions, Economy And Society, 13, 3–23. https://doi.org/10.1093/cjres/rsaa004
. (2017). Where is technology taking the economy. Mckinsey & Company, (McKinsey Analytics). Retrieved de mckinsey.com/business-functions/mckinsey-analytics/our-insights/where-is-technology-taking-the-economy
. (2020). White Paper on Artificial Intelligence - A European approach to excellence and trust. In COM(2020) 65 final. Retrieved de https://www.cambridge.org/core/product/identifier/CBO9781107415324A009/type/book_part
. (2015). Who owns the robots rules the world. Iza World Of Labor. https://doi.org/10.15185/izawol.5
. (2015). Why Are There Still So Many Jobs? The History and Future of Workplace Automation. Journal Of Economic Perspectives, 29(3), 3-30. https://doi.org/10.1257/jep.29.3.3
. (2019). Why artificial intelligence will not outsmart complex knowledge work. Work, Employment And Society, 33(6), 1058 - 1067. https://doi.org/10.1177/0950017018817489
. (2019). Why small data holds the key to the future of artificial intelligence. In 8th International Conference on Data Science, Technology and ApplicationsProceedings of the 8th International Conference on Data Science, Technology and Applications (340 - 347). https://doi.org/10.5220/0007956203400347
. (2019). Why we are failing to understand the societal impact of artificial intelligence. Social Research: An International Quarterly, 86, pp. 477-498. Retrieved de https://muse.jhu.edu/article/732186