9 citations · 21 across the 7 of their papers we have counts for
7 papers
Do Generative AI Models Output Harm while Representing Non-Western Cultures: Evidence from A Community-Centered Approach
Sourojit Ghosh, Pranav Narayanan Venkit, Sanjana Gautam +2
Our research investigates the impact of Generative Artificial Intelligence (GAI) models, specifically text-to-image generators (T2Is), on the representation of non-Western cultures…
Blind Spots and Biases: Exploring the Role of Annotator Cognitive Biases in NLP
Sanjana Gautam, Mukund Srinath
With the rapid proliferation of artificial intelligence, there is growing concern over its potential to exacerbate existing biases and societal disparities and introduce novel ones…
From Melting Pots to Misrepresentations: Exploring Harms in Generative AI
Sanjana Gautam, Pranav Narayanan Venkit, Sourojit Ghosh
With the widespread adoption of advanced generative models such as Gemini and GPT, there has been a notable increase in the incorporation of such models into sociotechnical systems…
The Sentiment Problem: A Critical Survey towards Deconstructing Sentiment Analysis
Pranav Narayanan Venkit, Mukund Srinath, Sanjana Gautam +4
We conduct an inquiry into the sociotechnical aspects of sentiment analysis (SA) by critically examining 189 peer-reviewed papers on their applications, models, and datasets. Our i…
Unmasking Nationality Bias: A Study of Human Perception of Nationalities in AI-Generated Articles
Pranav Narayanan Venkit, Sanjana Gautam, Ruchi Panchanadikar +2
We investigate the potential for nationality biases in natural language processing (NLP) models using human evaluation methods. Biased NLP models can perpetuate stereotypes and lea…
Nationality Bias in Text Generation
Pranav Narayanan Venkit, Sanjana Gautam, Ruchi Panchanadikar +2
Little attention is placed on analyzing nationality bias in language models, especially when nationality is highly used as a factor in increasing the performance of social NLP mode…