A Language modeling approach to detect bias
Atik, Ceren, author.

A Language modeling approach to detect bias

Atik, Ceren, author.

Yazar Ek Girişi
Atik, Ceren, author.

Fiziksel Tanımlama
x, 44 leaves: charts;+ 1 computer laser optical disc.

Technology is developing day by day and is involved in every area of our lives. Technological innovations such as artificial intelligence can strengthen social biases that already exist in society, regardless of the developers' intentions. Therefore, researchers should be aware of this ethical issue. In this thesis, the effect of gender bias, which is one of the social biases, on occupation classification is investigated. For this, a new dataset was created by collecting obituaries from the New York Times website and they were handled in two different versions, with and without gender indicators. Since occupation and gender are independent variables, gender indicators should not have an impact on the occupation prediction of models. In this context, in order to investigate gender bias on occupation estimation, a model in which occupation and gender are learned together is evaluated as well as models that make only occupation classification are evaluated. The results obtained from models state that gender bias has a role in classification occupation.

Konu Başlığı
Neural networks (Computer science).
Artificial intelligence -- Social aspects.

Yazar Ek Girişi
Tekir, Selma,

Tüzel Kişi Ek Girişi
İzmir Institute of Technology. Computer Engineering.

Tek Biçim Eser Adı
Thesis (Master)--İzmir Institute of Technology: Computer Engineering.
İzmir Institute of Technology: Computer Engineering--Thesis (Master).

Elektronik Erişim
Access to Electronic Versiyon.

KütüphaneMateryal TürüDemirbaş NumarasıYer NumarasıDurumu/İade Tarihi
IYTETezT002159QA76.87 .A87 2020Tez Koleksiyonu