Emma Ahmed-Rengers

Emma Ahmed-Rengers

Birmingham Law School
Doctoral researcher

Contact details

Qualifications

  • LLM, University of Cambridge (Queens’ College)
  • BSc, University of Amsterdam

Biography

I hold a BSc in Politics, Psychology, Law, and Economics (PPLE) from the University of Amsterdam (2017) and an LLM from Queens’ College, the University of Cambridge (2018). During my LLM, I specialised in international human rights law and legal and political theory.

Before starting the PhD, I worked as a junior researcher and academic tutor at the University of Amsterdam. I taught courses on public international law, legal theory, political theory, philosophy of the social sciences, and human rights. My research was on international law and social justice.

To complement my legal training, I am currently taking courses in Computer Science, specifically focused on machine learning and computer vision.

My research interests include: algorithmic accountability, AI regulation, machine ethics, human rights, legal theory, theories of justice and morality.

Doctoral research

PhD title
The Responsible Governance of Computer Vision Technologies
Supervisors
Professor Karen Yeung and Dr Hyung Jin Chang
Course
Law PhD / PhD by Distance Learning / MPhil / MJur

Research

Current developments in artificial intelligence (AI) have made it possible to create and analyse data on an unprecedented scale and at unprecedented speed. The possibility of AI-assisted decision-making does not only promise efficiency. It also enhances surveillance capabilities, encourages large-scale data collection, and facilitates population-wide manipulation. Moreover, it does so in a manner largely hidden from the public. Therefore, certain applications of AI may present a significant threat to human rights. My research focuses on one specific application of AI technology: computer vision. This is AI which can collect, analyse, and make decisions on the basis of visual data. My aims are (1) to clarify the workings of computer vision to a non-technical audience, (2) to identify societal risks and ethical challenges associated with computer vision technologies, and (3) to discover which legal, political, and economic interventions are needed to ensure responsible governance of computer vision technologies.

Source of Funding: CALS Studentship