Banca de QUALIFICAÇÃO: DANIEL BONATTO SECO

Uma banca de QUALIFICAÇÃO de MESTRADO foi cadastrada pelo programa.
STUDENT : DANIEL BONATTO SECO
DATE: 25/03/2024
TIME: 09:00
LOCAL: remoto
TITLE:

BIAS IN NATURAL LANGUAGE GENERATION IN THE LARGE ERA
LANGUAGE MODELS (LLMS) FROM THE PERSPECTIVE OF THE HUMANITIES
DIGITAL

KEY WORDS:

language models; bias in language models; digital humanities; artificial intelligence

PAGES: 106
BIG AREA: Outra
AREA: Multidisciplinar
SUMMARY:

The rapid spread and adoption of artificial intelligence technologies, especially
language models, represents a milestone in the evolution of contemporary digital society. These models, powered by advanced algorithms and trained on large
volumes of data, have the potential to transform a wide range of industries, from
industry to public services. The scalability and versatility of these solutions have
leading them to exponential use (HAAN, 2023) in various applications, creating a scenario where interaction between humans and machines is increasingly common and intrinsic to everyday life.

The present work aims to evaluate biases in language models, especially
large-scale ones, and their impact on the production of contemporary knowledge. O
study seeks to identify how these models reproduce prejudices and stereotypes
from training data, influencing automated decisions and dissemination of
information. Furthermore, it highlights the need for regulation in the area and the importance
of cultural representation in data sets to promote the production of
more equitable and socially responsible knowledge.

COMMITTEE MEMBERS:
Presidente - 1800852 - LEANDRO GUIMARAES MARQUES ALVIM
Externa à Instituição - ADRIANA SILVINA PAGANO - UFMG
Externo à Instituição - CARLOS EDUARDO RIBEIRO DE MELLO - UNIRIO