Robotic Journalism: from Scientific Discourse to Journalism Education

For citation: Zamkov A.V., Krasheninnikova M.A., Lukina M.M., Tsynareva N.A. (2017) Robotizirovannaya zhurnalistika: ot nauchnogo diskursa k zhurnalistskomu obrazovaniyu [Robotic Journalism: from Scientific Discourse to Journalism Education]. Mediaskop 2. (in Russian). Available at: http://www.mediascope.ru/2295

© Andrey V. Zamkov
Researcher at the Problem Research Laboratory for Complex Studies of Modern Media Problems, Faculty of Journalism, Lomonosov Moscow State University (Moscow, Russia), zamkov.andrey@mail.ru

© Maria A. Krasheninnikova
Lecturer at the Chair of New Media and Theory of Communication, Faculty of Journalism, Lomonosov Moscow State University (Moscow, Russia), mashagarnova@gmail.com

© Maria M. Lukina
PhD, Associate Professor at the Chair of New Media and Communication Theory Faculty of Journalism, Lomonosov Moscow State University (Moscow, Russia), maria_lukina@list.ru

© Natalya A. Tsynareva
PhD, Senior Researcher at the Chair of Foreign Journalism and Literature, Faculty of Journalism, Lomonosov Moscow State University (Moscow, Russia), tsynareva.na@gmail.com

Abstract

New technological solutions that captured media industry force journalism teachers to search for new approaches to the educational process – update its content and create new modules and disciplines that should not only match current media practice but even outrun to some extent those processes, that nowadays appear to be progressive. For this reason technological forecasting has become an important element in determining new approaches, methods and teaching technologies, as well as hunting in the interdisciplinary and related fields, that are well known for their innovative achievements. Authors of this paper are attracted by professional discourse and findings in the field of artificial intelligence and robotics used in journalism, and propose these topics to be included in programs for journalism education for expert discussion. Authors explain the main principles of algorithms that help solve such intellectual tasks as information search, protection from plagiarism and offensive content as well as other achievements and limitations in semantic robotic solutions linked to natural language technologies. Several innovative implementations are forecasted for journalism education syllabi relying on "smart" professional components which will form the future journalism, and in particular newer interpretations of informatics basics, editing of robotic texts, as well as studying ethical challenges that arise in the context of robotic invasion to journalism routines.

Key words: Journalism education, artificial intelligence, robotic journalism.

Notes

Chumakov N. (2017) Kitayskiy robot-zhurnalist za sekundu napisal pervuyu stat'yu iz 300 simvolov [Chinese Robot Journalist Wrote the First Article of 300 Characters in 1 Second]. TJournal, January, 19. Available at: https://tjournal.ru/40042-kitaiskii-robot-zhurnalist-za-sekundu-napisal-pervuu-statu-iz-300-simvolov (aссessed: 12.02.2017).

Kornev M., Pulya (2016) Vs. 5 trendov novykh media v 2017 godu [5 Trends in New Media in 2017]. Mediatoolbox. Available at: http://mediatoolbox.ru/trends2017/ (aссessed: 12.02.2017).

Miroshnichenko A. (2015) Robotozhurnalistika: vkalyvayut roboty – schastliv chelovek? [Robot Journalism: Robots Work Hard - Is Human Happy?]. TexTerra, November, 26. Available at: https://texterra.ru/blog/roboto-zhurnalistika-vkalyvayut-roboty-schastliv-chelovek.html (aссessed: 12.02.2017).

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