With facial recognition technology becoming a greater part of our everyday lives the ethicalimplications it may bring is something worth exploring, and according to scientists the technology could already be incorporated in video surveillance. Previous studies have shown thatwomen and men see things differently within this context, something that will be explored inthis paper. Through focus group interviews and a survey study the students could not confirmthis statement, and found that in only one specific context women and men had significantdifferent standpoints. Further the study found that there is a fear of what this technology couldresult in, in the form of abuse of the information gathered about people and how society couldchange with the incorporation of said technology in video surveillance. / Eftersom ansiktsigenkänningsteknologi blir en större del av vår vardag är de etiska konsekvenserna det kan ge något som är värt att utforska, och enligt forskare kan tekniken redanfinnas implementerad i videoövervakning. Tidigare studier har visat att kvinnor och män uppfattar saker annorlunda inom detta sammanhang, något som kommer att undersökas i dennauppsats. Genom fokusgruppsintervjuer och en enkätstudie kunde studenterna inte bekräftadetta uttalande och fann endast att kvinnor och män i ett specifikt sammanhang hade märkbartolika uppfattningar. Vidare fann studien att det finns en rädsla för vad denna teknik kan resultera i, i form av missbruk av den information som samlats in om människor och hur samhälletkan förändras genom införandet av nämnd teknik i videoövervakning.

The concept and practice of surveillance has long existed in our society, yet with the development of technology, it has taken on new forms and capabilities. As a result, surveillance technology has become integrated in our society, influencing norms and shaping imaginaries surrounding it. While many existing studies have thoroughly examined people's experiences with surveillance technologies, there has been little attention paid to the efforts of advocacy groups in challenging and reshaping the mainstream imaginaries regarding surveillance technology. Using narrative analysis, this thesis aims to address this gap and explore the sociotechnical imaginaries surrounding facial recognition technology of four advocacy groups: a) Fight for the Future, b) Big Brother Watch, c) Electronic Frontier Foundation, d) Surveillance Technology Oversight Project. This study uncovers that these groups' shared sociotechnical imaginary aligns closely with modern liberal ideals, highlighting the possibility of separating public and private life, the necessity for not only moderate government intervention, but healthy commercial competitions, as well as public education. In other words, I argue that resisting against a particular technology and its associated power dynamics does not always represent a challenge to the fundamental power structure.

Facial recognition technology has become a ubiquitous tool in security and personal identification. However, the rise of this technology has been accompanied by concerns over inherent biases, particularly regarding ethnic and gender. This thesis examines the extent of these biases by focusing on the influence of dataset imbalances in facial recognition algorithms. We employ a structured methodological approach that integrates AI-generated images to enhance dataset diversity, with the intent to balance representation across ethnics and genders. Using the ResNet and Vgg model, we conducted a series of controlled experiments that compare the performance impacts of balanced versus imbalanced datasets. Our analysis includes the use of confusion matrices and accuracy, precision, recall and F1-score metrics to critically assess the model’s performance. The results demonstrate how tailored augmentation of training datasets can mitigate bias, leading to more equitable outcomes in facial recognition technology. We present our findings with the aim of contributing to the ongoing dialogue regarding AI fairness and propose a framework for future research in the field.