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Brittan Heller. 6/12/2020. “Reimagining Reality: Human Rights and Immersive Technology.” Carr Center Discussion Paper Series, 2020-008. See full text.Abstract

This paper explores the human rights implications of emergent technology, and focuses on virtual reality (VR), augmented reality (AR), and immersive technologies. Because of the psychological and physiological aspects of immersive technologies, and the potential for a new invasive class of privacy-related harms, she argues that content creators, hardware producers, and lawmakers should take increased caution to protect users. This will help protect the nascent industry in a changing legal landscape and help ensure that the beneficial uses of this powerful technology outweigh the potential misuses.

In the paper, Heller first reviews the technology and terminology around immersive technologies to explain how they work, how a user’s body and mind are impacted by the hardware, and what social role these technologies can play for communities. Next she describes some of the unique challenges for immersive media, from user safety to misalignment with current biometrics laws. She introduces a new concept, biometric psychography, to explain how the potential for privacy-related harms is different in immersive technologies, due to the ability to connect your identity to your innermost thoughts, wants, and desires. Finally, she describe foreseeable developments in the immersive industry, with an eye toward identifying and mitigating future human rights challenges. The paper concludes with five recommendations for actions that the industry and lawmakers can take now, as the industry is still emerging, to build human rights into its DNA.
 



Steven Livingston and Mathias Risse. 6/7/2019. “The Future Impact of Artificial Intelligence on Humans and Human Rights.” Ethics and International Affairs, 33, 2, Pp. 141-158. See full text.Abstract

What are the implications of artificial intelligence (AI) on human rights in the next three decades?

Precise answers to this question are made difficult by the rapid rate of innovation in AI research and by the effects of human practices on the adaption of new technologies. Precise answers are also challenged by imprecise usages of the term “AI.” There are several types of research that all fall under this general term. We begin by clarifying what we mean by AI. Most of our attention is then focused on the implications of artificial general intelligence (AGI), which entail that an algorithm or group of algorithms will achieve something like superintelligence. While acknowledging that the feasibility of superintelligence is contested, we consider the moral and ethical implications of such a potential development. What do machines owe humans and what do humans owe superintelligent machines?

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Drew Bowlsby, Erica Chenoweth, Cullen Hendrix, and Jonathan D. Moyer. 2/20/2019. “The Future is a Moving Target: Predicting Political Instability.” British Journal of Political Science. See full text.Abstract

Journal article on: The Future is a Moving Target: Predicting Political Instability

Previous research by Goldstone et al. (2010) generated a highly accurate predictive model of state-level political instability. Notably, this model identifies political institutions – and partial democracy with factionalism, specifically – as the most compelling factors explaining when and where instability events are likely to occur. This article reassesses the model’s explanatory power and makes three related points: (1) the model’s predictive power varies substantially over time; (2) its predictive power peaked in the period used for out-of-sample validation (1995–2004) in the original study and (3) the model performs relatively poorly in the more recent period. The authors find that this decline is not simply due to the Arab Uprisings, instability events that occurred in autocracies. Similar issues are found with attempts to predict nonviolent uprisings (Chenoweth and Ulfelder 2017) and armed conflict onset and continuation (Hegre et al. 2013). These results inform two conclusions: (1) the drivers of instability are not constant over time and (2) care must be exercised in interpreting prediction exercises as evidence in favor or dispositive of theoretical mechanisms.



Erica Chenoweth and Margherita Belgioioso. 8/5/2019. “The Physics of Dissent and the Effects of Movement Momentum.” Nature Human Behaviour. See full text.Abstract

How do ‘people power’ movements succeed when modest proportions of the population participate?

Here we propose that the effects of social movements increase as they gain momentum. We approximate a simple law drawn from physics: momentum equals mass times velocity (p = mv). We propose that the momentum of dissent is a product of participation (mass) and the number of protest events in a week (velocity). We test this simple physical proposition against panel data on the potential effects of movement momentum on irregular leader exit in African countries between 1990 and 2014, using a variety of estimation techniques. Our findings show that social movements potentially compensate for relatively modest popular support by concentrating their activities in time, thus increasing their disruptive capacity. Notably, these findings also provide a straightforward way for dissidents to easily quantify their coercive potential by assessing their participation rates and increased concentration of their activities over time.

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