Benedetta Catanzariti's profile
Name

Benedetta Catanzariti

SPS Department

Science, Technology & Innovation Studies

I am a PhD student in Science, Technology and Innovation Studies, researching on the relationship between surveillance, AI and society. My academic background is in philosophy and I am particularly interested in the way technology shapes our identity and contributes to reinforce or, alternatively, dismantle social inequalities. I am currently looking at the design of the classification techniques underpinning the development and use of automated facial and affect recognition systems. My work is informed by feminist studies and critical data studies. 

Together with friends and colleagues Sarah Bennet, Vassilis Galanos, and Yazmin Morlet Corti, I am involved in the shaping of the Edinburgh Futures Institute-supported AI Ethics & Society research group, and the organization of the Critical Perspectives on Artificial Intelligence Ethics 2020 conference (CPAIE).

In 2019, along with Antonio Ballesteros, James Lowe, and Lukas Engelmann, I became a member of the STIS seminar organizing committee.

Qualifications

  • PhD in Science, Technology and Innovation Studies, the University of Edinburgh, 2019 - onwards.
  • MSc by Research in Science and Technology Studies, the University of Edinburgh, 2019.
  • MSc in Philosophy, Università degli Studi di Torino, 2016.
  • BA in Philosophy, Università degli Studi di Torino, 2013.

Awards and Funding

  • College Research Awards, 2019.
  • Economic and Social Research Council (ESRC) Award, 2019.
  • Highly Skilled Workforce Scholarship, 2018.

Research Interests

Ethnography Inequality ICT Sociology of knowledge and science Science and technology studies Artificial Intelligence and Robotics Surveillance biopolitics and bioeconomy artificial emotional intelligence feminist studies AI ethics critical data studies Balance of power

Research Activities

Benedetta Catanzariti has not added any teaching activity to this section yet.

PhD Title

Coding the face: Design Process and Social Dynamics of AI facial and affect recognition technology (working title)

PhD Supervisors

PhD Overview

Over the last decade, automated facial recognition has become common not only in personal devices, but in a wide range of sensitive domains, such as predictive policing, immigration control, medical diagnosis, access to insurance, employment, social benefits, and credit. Controversially, experts now claim that facial recognition technology could identify age, ethnicity, gender, sexual orientation, genetic makeup, emotions and personality traits from facial features with more accuracy than humans. This raises concerns regarding human and civil rights, especially when employed for surveillance purposes. The proposed project will examine the design of the classification techniques and technologies underpinning the development and use of facial and affect recognition systems. A combination of patent analysis, semi-structured interviews with AI experts and ethnographic fieldwork within a facial recognition project will provide critical insights on the relationship between the design and development of such technology and wider systemic social inequality.

Catanzariti, B., “Feeling Machines: Emotion Recognition in Personal Assistants”, in Goldschmidt, P., Haddow, G., and Mazanderani, F., ed. (2020) Uncanny Bodies. Edinburgh: Luna Press.

Catanzariti, B., "Angelologia e burocrazia: tecnologie del potere amministrativo" in «Filosofia», Quarta Serie, Anno LXII, Mimesis, 2017, pp. 41-57.