Abstract
Every fiscal quarter automated writing algorithms churn out thousands of corporate earnings articles for the AP (Associated Press) based on little more than structured data. Companies such as Automated Insights, which produces the articles for AP, and Narrative Science can now write straight news articles in almost any domain that has clean and well-structured data: finance, sure, but also sports, weather, and education, among others. The articles aren’t cardboard either; they have variability, tone, and style, and in some cases readers even have difficulty distinguishing the machine-produced articles from human-written ones.
- ACM. 2015. Software Engineering Code of Ethics and Professional Practice; https://www.acm.org/about/se-code#fullGoogle Scholar
- ACM Code of Ethics and Professional Conduct. 1992; https://www.acm.org/about/code-of-ethics.Google Scholar
- Citron, D., Pasquale, F. 2014. The scored society: due process for automated predictions. Washington Law Review 89.Google Scholar
- Clerwall, C. 2014. Enter the robot journalist. Journalism Practice 8(5): 519-531.Google ScholarCross Ref
- Diakopoulos, N. 2015. Algorithmic accountability: journalistic investigation of computational power structures. Digital Journalism 3(3): 398-415.Google ScholarCross Ref
- Diakopoulos, N. 2014. Algorithmic defamation: the case of the shameless autocomplete. Tow Center for Digital Journalism.Google Scholar
- Diakopoulos, N., et al. 2014. Data-driven rankings: the design and development of the IEEE Top Programming Languages news app. Proceedings of the Symposium on Computation + Journalism.Google Scholar
- Diakopoulos, N. 2015. How Uber surge pricing really works. Washington Post Wonkblog (April 17).Google Scholar
- Don Ray Drive-A-Way Co. v. Skinner, 785 F. Supp. 198 (D.D.C. 1992). 1992; http://law.justia.com/cases/federal/district-courts/FSupp/785/198/2144490/.Google Scholar
- Epstein, R., Robertson, R.E. 2015. The search engine manipulation effect (SEME) and its possible impact on the outcomes of elections. Proceedings of the National Academy of Sciences (PNAS) 112(33).Google ScholarCross Ref
- Eslami, M., et al. 2015. "I always assumed that I wasn't really that close to {her}": reasoning about invisible algorithms in the news feed. Proceedings of the 33rd Annual ACM SIGCHI Conference on Human Factors in Computing Systems. Google ScholarDigital Library
- Feldman, M., et al. 2015. Certifying and removing disparate impact. Proceedings of the 21st ACM International Conference on Knowledge Discovery and Data Mining: 259-268. Google ScholarDigital Library
- Herlocker, J. L., et al. 2000. Explaining collaborative filtering recommendations. Proceedings of the ACM Conference on Computer Supported Cooperative Work: 241-250. Google ScholarDigital Library
- Kalhan, A. 2013. Immigration policing and federalism through the lens of technology, surveillance, and privacy. Ohio State Law Journal 74.Google Scholar
- Kashin, K., et al. 2015. Systematic bias and nontransparency in US Social Security Administration forecasts. Journal of Economic Perspectives 29(2).Google ScholarCross Ref
- Kraemer, F., et al. 2010. Is there an ethics of algorithms? Ethics and Information Technology 13(3): 251-260. Google ScholarDigital Library
- Letham, B., et al. 2015. Building interpretable classifiers with rules using Bayesian analysis. Annals of Applied Statistics.Google ScholarCross Ref
- Mitchell, A., et al. 2015. Millennials and Political News. Pew Research Center, Journalism and Media (June 1); http://www.journalism.org/2015/06/01/millennials-political-news/.Google Scholar
- Muckrock. 2011. Source code of HEAT SAFETY TOOL; https://www.muckrock.com/foi/united-states-of-america-10/source-code-of-heat-safety-tool-766/.Google Scholar
- Mühlbacher, T., et al. 2014. Opening the black box: strategies for increased user involvement in existing algorithm implementations. IEEE Transactions on Visualization and Computer Graphics 20(12): 1643-1652.Google ScholarCross Ref
- Nissenbaum, H. 1996. Accountability in a computerized society. Science and Engineering Ethics 2(1): 25-42.Google ScholarCross Ref
- Schaffer, J., et al. 2015. Getting the message?: a study of explanation interfaces for microblog data analysis. Proceedings of the 20th International Conference on Intelligent User Interfaces (IUI): 345-356. Google ScholarDigital Library
- Sen, S., et al. 2015. Turkers, Scholars, "Arafat" and "Peace": cultural communities and algorithmic gold standards. Proceedings of the 18th ACM Conference on Computer Supported Cooperative Work and Social Computing: 826- 838. Google ScholarDigital Library
- Sifry, M. 2014. Facebook wants you to vote on Tuesday. Here's how it messed with your feed in 2012. Mother Jones (Oct. 31); http://www.motherjones.com/politics/2014/10/can-voting-facebook-button-improve-voter-turnout.Google Scholar
- Tintarev, N., Masthoff, J. 2007. A survey of explanations in recommender systems. Proceedings of the International Conference on Data Engineering: 801-810. Google ScholarDigital Library
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