Browsing by Subject "face recognition"

This master's thesis seeks to conceptually replicate psychologist Michael Kosinski's study, published in 2021 in Nature Scientific Reports, in which he trained a cross-validated logistic regression model to predict political orientations from facial images. Kosinski reported that his model achieved an accuracy of 72\%, which is significantly higher than the 55\% accuracy measured in humans for the same task. Kosinski's research attracted a huge amount of attention and also accusations of pseudoscience. Where Kosinski trained his model with facial features containing information for example about head position and emotions, in this thesis I use a deep learning convolutional neural network for the same task. Also, I train my model with Finnish data, consisting of photos of the faces of Finnish left- and right-wing candidates gathered from the 2021 municipal elections. I research whether a convolutional neural network can learn to predict from candidates' faces whether a member of a Finnish party belongs to either the right-wing Coalition Party (Coalition) or the left-wing Left Alliance (Left Alliance) with better than 55\% accuracy, and what is the possible role of color information on the classification accuracy of the model. On this basis, I also consider the wider ethical issues surrounding these types of models and the technological advances they bring. There has been a recent ethical debate on the widespread use of facial recognition technology in relation to issues such as human autonomy, privacy, and civil liberties. In the context of previous scientific findings, there has also been debate about the potential ability of facial recognition technologies to reveal information about our most personal traits, such as sexual orientation, personality, and emotional states. Thus, facial recognition technologies are also closely related to privacy issues. In his original article, Michael Kosinski did not underestimate the many problematic ethical issues that the use of facial recognition technology can raise. He did, however, underline the role of science in trying to determine the function, capability, and accuracy of these technologies. Only through research can we gain insights into these technologies, which can then potentially be used to inform societal decision-making. This research approach is also the aim of this Master's thesis.