This paper was prepared for an interdisciplinary conference on Gefährliche Forschung? (Dangerous Science?) held at the University of Cologne in February 2020 and is scheduled to appear in a volume of contributions from that event edited by Wilfried Hinsch and Susanne Brandstätter, the organizers, and to be published by de Gruyter. The paper delves into the question proposed to me—might population genetics or artificial intelligence undermine philosophical ideas about equality—without locating the context of this debate or offering a preview of its contents. The first section discusses the ideal of equality, the next two talk about genetics in the context of responses to racism, and the remaining two speak about possible changes that might come from the development of general Artificial Intelligence.
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The criminal justice system in the U.S. has over-incarcerated its citizen base; we have 5% of the world's population but 25% of the world's prison population. America became known as the “incarceration nation” because our prison and jail population exploded from less than 200,000 in 1972 to 2.2 million today, which became a social phenomenon known as mass incarceration. And along the way, there was a subsequent boom in querying databases for data on citizens with criminal records.
Once a person comes in contact with the U.S. criminal justice system, they begin to develop an arrest and/or conviction record. This record includes data aggregated from various databases mostly, if not exclusively, administered by affiliated government agencies. As the prison population grew, the number of background check companies rose as well. The industry has grown and continues to do so with very little motivation to wrestle with morality, data integrity standards, or the role of individual rights.
This paper address the urgent need to look towards a future where background screening decisions and artificial intelligence collide.
What is the measure of personhood and what does it mean for machines to exhibit human-like qualities and abilities? Furthermore, what are the human rights, economic, social, and political implications of using machines that are designed to reproduce human behavior and decision making? The question of personhood is one of the most fundamental questions in philosophy and it is at the core of the questions, and the quest, for an artificial or mechanical personhood.
The development of artificial intelligence has depended on the traditional Western view of personhood as rationality. However, the traditional view of rationality as the essence of personhood, designating how humans, and now machines, should model and approach the world, has always been marked by contradictions, exclusions, and inequality. It has shaped Western economic structures (capitalism’s free markets built on colonialism’s forced markets), political structures (modernity’s individualism imposed through coloniality), and discriminatory social hierarchies (racism and sexism as institutions embedded in enlightenment-era rationalized social and gender exclusions from full person status and economic, political, and social participation), which in turn shape the data, creation, and function of artificial intelligence. It is therefore unsurprising that the artificial intelligence industry reproduces these dehumanizations. Furthermore, the perceived rationality of machines obscures machine learning’s uncritical imitation of discriminatory patterns within its input data, and minimizes the role systematic inequalities play in harmful artificial intelligence outcomes.
For those who follow the politics of platforms, Monday’s great expulsion of malicious content creators was better late than never. For far too long, a very small contingent of extremely hateful content creators have used Silicon Valley’s love of the First Amendment to control the narrative on commercial content moderation. By labeling every effort to control their speech as “censorship,” these individuals and groups managed to create cover for their use of death threats, harassment, and other incitements to violence to silence opposition. For a long time, it has worked. Until now. In what looks like a coordinated purge by Twitch, Reddit, and YouTube, the reckoning is here for those who use racism and misogyny to gain attention and make money on social media.
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.
The unfortunate truth is that personal data has become the bricks and mortar used to build many AI technologies and more must be done to protect and safeguard the humans whose personal data is being used. Through a case study on AI-powered remote biometric identity verification, this paper seeks to explore the technical requirements of building AI technologies with high volumes of personal data and the implications of such on our understanding of existing data protection frameworks. Ultimately, a path forward is proposed for ethically using personal data to build AI technologies.
Neal Cohen analyzes why AI technologies fall short on privacy. While artificial intelligence (AI) powered technologies are now commonly appearing in many digital services we interact with on a daily basis, an often neglected truth is that few companies are actually building the underlying AI technology.