March 01, 2020
Digital Repression in Autocracies
Repression is a hallmark feature of authoritarian rule. It raises the costs of disloyalty and makes it more difficult for groups to mobilize against the regime (Wintrobe, 1998). Though dictatorships vary markedly in the extent to which they rely on repression, all regimes use it to some degree (Frantz and Kendall-Taylor, 2014). This reality of authoritarian politics has not changed over time. What has changed, however, are the tools available to autocratic governments to carry out such repression (Xu, 2019).
With the advent of new technologies, dictatorships can censor and filter the Internet to prohibit the spread of unfavorable information, as exemplified by the Chinese regime’s “Great Firewall.”1 They can also use bot-driven information-distortion campaigns on social media to cloud information channels with noise and confuse citizens, a tactic at which the Russian government is particularly adept.2 And they can use artificial intelligence (AI) to surveil their citizens, making it easy to identify, monitor, and target those who oppose them. Saudi Arabia, for example, reportedly hacks into the online accounts of its dissidents using commercially available surveillance technology.3 In other words, opportunities for leveraging new technologies to carry out repression in new ways – what we refer to as digital repression – are vast.
Read the full paper from the Varieties of Democracy (V-Dem) Institute.
- See “The Great Firewall of China,”’ Bloomberg News, 05 November 2018, https://www.bloomberg.com/quicktake/great-firewall-of-china (accessed 24 February 2020). ↩
- “How Russia and Other Foreign Actors Sow Disinformation in Elections,” National Public Radio, 21 February 2020, https://www.npr.org/2020/02/21/808275155/how-russia-and-other-foreign-actors-sow-disinformation-in-elections (accessed 24 February 2020). ↩
- “Saudi Arabia: Change Comes with Punishing Cost”, Human Rights Watch, 04 November 2019, https://www.hrw.org/news/2019/11/04/saudi-arabia-change-comes-punishing-cost (accessed 24 February 2020). ↩
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