Skip to main content

Staff Profile

Professor Jeremy Crampton

Professor of Urban Data Analysis

  • Email: jeremy.crampton@ncl.ac.uk
  • Address: School of Architecture, Planning and Landscape,
    Henry Daysh Building,
    Newcastle University,
    Newcastle upon Tyne,
    NE1 7RU
Background

I joined Newcastle University School of Architecture, Planning and Landscape in 2018 after spending most of my career in the United States. I was previously Professor of Geography at the University of Kentucky, and have also held academic posts at Georgia State University in Atlanta, and George Mason University in Virginia. I grew up in Chester and the Welsh border county of Shropshire.

My main interests are in how and why geolocational technologies affects urban and everyday experience and wellbeing. In particular, I'm very interested in the effects of surveillance on privacy, spatial Big Data and algorithmic decision-making. To address these questions, I analyze how digital landscapes of algorithms and data are planned, mapped and produced. I also have a recent interest in the geolocational implications of biometric platforms such as facial and emotional recognition technologies, and the possibilities of building AI/ML that do not treat people as data subjects.

Google Scholar: here.

My blog is here.

Twitter: @jeremycrampton


Research

I am a broadly trained geographer with interests in two complementary areas. I have a longstanding interest in the development of digital mapping and geolocational technologies including cartography and GIScience. Second, I study geographic analytics, including spatial Big Data, and digital biometric platforms (eg., facial recognition technologies), how they create new urban spaces, and their social implications.

I investigate the role of values and how they are encoded into artificial intelligence and machine learning (AI/ML). Although considerable time and investment has been made in advancing our understanding of the outputs of AI, including its ethics, bias and fairness, little attention has been made to what inputs are encoded into machine learning. I am inspired by the work of Ruha Benjamin to look at societal infrastructures which generate geospatial technologies. For this reason I argue that technology is a symptom, not a cause of injustice. How so?

To answer this question, I am currently working on the following projects:

Slow AI

Slow AI is a proposed set of societal values to underwrite national policy-making. It is formed of three principles: Think. Resist. Act Local. It was developed in response to the "rush to AI" and the bro tech posture of "disruption." Think: not everything is AI, nor is AI always needed. Resist: we should be very careful about implementing automated governance at scale. Act local:A grand challenge facing AI researchers is how to ensure AI is place-based; that is how it can be better co-produced on a local scale with communities. For example, can acting locally reduce the vast levels of energy consumption of machine learning and computation? At a time when data centers consume nearly half the global carbon footprint of the tech industry, we need to weigh the costs on the environment of algorithms, computation and machine learning.

2021. Crampton, J.W. Digital Imaginaries of the Pandemic‑Resilient City. pnd rethinking planning 2.2021. doi 10.18154/RWTH-2021-10416.

Platform Biometrics/facial/emotional recognition

Facial recognition is now a familiar technology, deployed by the Metropolitan Police in London, used at international borders and by airlines at boarding. It is part of a growing surveillance platform; an infrastructure of almost constant mass surveillance. Although its biases are well documented, researchers are now rapidly developing facial emotion (or affective) recognition. Based on suspect scientific grounds (Barrett et al. 2019) emotion recognition is the next phase of platform surveillance, with deployments in school classrooms, job interviews, gendered behaviour identification, criminal identification and the workplace.

Crampton, JW. 2019. Platform Biometrics. Surveillance and Society, 17(1-2): 52-62.

Del Casino, V., House-Peters, L. Crampton, JW., Gerhardt, H. 2020. The Social Life of Robots: The Politics of Algorithms, Governance, and Sovereignty. Antipode, 52: 1-14.

Surveillance fears and anxiety

Surveillance is constitutive of the smart city; without it the city would be dumb. We as yet know very little of the effects on wellbeing and health of both individuals and society as a whole of this always-on surveillance. In this research, I examine how surveillance may not be a universal public good and can have differential effects on different groups, including men, women and nonbinary, and among ethnic groups.

Crampton, JW., Smith, H., Graham, S., Hoover, K., Berbesque, CJ. 2020. Smart Festivals? Security and Freedom for Well-Being in Urban Smart Spaces. Annals of the American Association of Geographers, 110(2): 360-370.

Crampton, JW. 2017. Algorithmic Anxieties. Antipode Foundation.

Crampton, JW. and Leszczyski, A. 2016. Spatial Big Data and Everyday Life. Big Data and Society, July-December: 1-6.


The Spyglass and the Map: The New Geographical Analytics of Everyday Life.

I am currently writing a book under this title that will explore these topics in more detail. At this time, the book is currently contracted for publication with Verso.

Teaching

2022

I am teaching TCP1026 Understand Place (20 credits).

I am teaching CEG8720 Understanding Geospatial Data: Social, Legal and Ethical Perspectives (10 credits)

2019 and 2020

I taught a two semester course (30 credits) for post-graduate students.

POPS: Privately Owned Public Spaces. Technologies of Policing and the Politics of Resistance. Newcastle-London case studies.

Aim

To trace the history of the rise of privately owned public spaces (POPS) and how they are changing the experience of being in public. To explore how they are policed and governed (eg via surveillance) and how people resist and challenge them.

Objectives

  • To engage with residents, locals and visitors in Newcastle and London to explore their experience of using POPS
  • To map where POPS are and who owns them (case studies in Newcastle and London King’s Cross); assess other ways of measuring public space (eg., Varna’s ‘Star’ Model)
  • To explore how POPS are policed and governed, including surveillance and Public Space Protection Orders (‘geographic asbos’). What power do PSPOs have?
  • To discover how people resist, challenge or counter POPS and public space surveillance. Lessons from Hong Kong and New York City.

If you are interested in this please contact me!


Previous classes:

I have taught a range of courses at undergraduate and postgraduate levels, both face-to-face and online. These include semester-length classes on digital mapping, geographic information systems (GIS), political geography, human geography, among others. At the advanced level, I have taught GIS, Big Data, social theory, and the thought of Michel Foucault.

Most recently I taught a 10-week online class on History of Critical Mapping at the University of Kentucky for their Masters in Digital Mapping @NewMapsPlus.

I have also supervised a number of Masters students both in the UK and the United States, and been on a number of PhD student committees, assessed PhD work for National Science Foundation grant applications. At Newcastle I am looking to supervise PhD students with interests around the following topics:

Surveillance

Biometrics, especially facial recognition/emotion recognition

Spatial Big Data

Critical cartography 

Platform or algorithmic governance

Publications