Dark matters: on the surveillance of blackness

By R. Gonzales. 2016

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Social Sciences & Humanities

Citations in the corpus

Learning Transferable Visual Models From Natural Language Supervision (2021, background): “Our inclusion of surveillance is not intended to indicate enthusiasm for this domain - rather, we think surveillance is an important domain to try to make predictions about given its societal implications (Zuboff, 2015; Browne, 2015).”
Towards a critical race methodology in algorithmic fairness (2019, neutral): “It may indeed be the most signiﬁcant axis, given attention by investigative journalists (e.g. [7]) and critical race and technology scholars (e.g. [11, 20, 21, 24, 85]).”
A Survey of Race, Racism, and Anti-Racism in NLP (2021, background): “…of tools for predicting demographic information (Tat-man, 2020) and automatic prison term prediction (Leins et al., 2020), motivated by the history of using technology to police racial minorities and re-lated criticism in other ﬁelds (Browne, 2015; Buo-lamwini and Gebru, 2018; McIlwain, 2019).”
Seeing without knowing: Limitations of the transparency ideal and its application to algorithmic accountability (2018, methodology): “Technologies of seeing and surveillance were inseparable from material architectures of domination as everything “from a candle flame to the white gaze” were used to identify who was in their rightful place and who required censure (Browne, 2015: 25).”
Big Data Surveillance: The Case of Policing (2017, background): “…can be traced back to at least the sixteenth century, during the appearance of the nation-state (Marx 2016), through the transatlantic slave trade (Browne 2015), bureaucratization, rationalization, and modern management in the nineteenth and twentieth centuries (Braverman 1974; Rule 1974; Weber…”
Terms of inclusion: Data, discourse, violence (2020, background): “” As Simone Browne (2015) has demonstrated, today’s data-based digital surveillance systems are deeply rooted in longer standing norms of White supremacy that actively construct Black communities and bodies as dangerous or deviant. Consequently, supposedly “objective” data can amplify, rather than a”
Truth from the machine: artificial intelligence and the materialization of identity (2021, background): “…her work is largely focused on surveillance and racialized violence, Simone Browne makes a similar argument in calling for a ‘ critical biometric consciousness ’ that understands technologies such as facial recognition as the latest evolution in a long line of similar mechanisms (Browne 2015).”
GPT-4V(ision) System Card (2023, background): “[18, 19] OpenAI has thus added refusals for most instances of sensitive trait requests-you can read more about how in Section 2.4.”
Critical Race Theory for HCI (2020, background): “They highlight negative representations of racial minorities [3, 89], reveal racist applications of technology [10, 22], celebrate the unique use of technology by specific racial groups [10, 19, 87], and showcase ways to fight racism [11, 83].”
Evaluating CLIP: Towards Characterization of Broader Capabilities and Downstream Implications (2021, background): “These capabilities, while exciting, come with associated risks because of the significant societal sensitivity of many of the tasks that CV models power [8], [5] [9].”
DALL-EVAL: Probing the Reasoning Skills and Social Biases of Text-to-Image Generation Models (2022, background): “Because race is not naturally inherent, fixed, or mutually exclusive [10, 62], inferring one’s racial identity from appearance and assuming that one’s race falls into a single category could lead to an inaccurate inference of one’s racial identity.”
Facial recognition is the plutonium of AI (2019, background): “As Browne [5] and other scholars have observed, facial recognition technologies and other systems for visually classifying human bodies through data are inevitably and always means by which “race,” as a constructed category, is defined and made visible.”