Sanchaita Hazra - UoU Econ

Sanchaita Hazra
sanchaita.hazra[at]utah.edu
Department of Economics
University of Utah

I am a fourth-year PhD student in Economics at the University of Utah. I am advised by Prof. Haimanti Bhattacharya and Prof. Subhasish Dugar. I also actively collaborate with Allen Institute for Artificial Intelligence.

My research interests are behavioral economics, experimental economics (Lab/Field), applied microeconomics, and artificial intelligence (AI). My work focuses on applying the methodologies of experimental economics in neoclassical economics to explore and gain deeper insights into the potential of AI in influencing human decision-making.

Previously, I worked as a statistician at DeepFlux (now accquired by Pivot Roots) and a research assistant at ISI Kolkata. My mentors include Prof. Priyodarshi Banerjee and Prof. Saibal Kar. In 2021, I was also a Lecturer of Economics at Women's Christian College, University of Kolkata. I founded Alankar, a women-run online jewelry brand fostering positive social impact on employbility.


CV  |  LinkedIn

Research·Awards·Talks·Teaching
Research
Published Works

Data-driven Discovery with Large Generative Models
with Bodhisattwa P. Majumder, Harshit Surana, Dhruv Agarwal, Ashish Sabharwal, Peter Clark
Published, July 2024
International Conference on Machine Learning (ICML), 2024
paper

A practical first step toward an end-to-end automation for scientific discovery. We posit that Large Generative Models (LGMs) present an incredible potential for automating hypothesis discovery, however, LGMs alone are not enough.

To Tell The Truth: Language of Deception and Language Models
with Bodhisattwa P. Majumder
Published, June 2024
North American Chapter of the Association for Computational Linguistics (NAACL, Oral), 2024
paper

We analyze a novel TV game show data where conversations in a high-stake environment between individuals with conflicting objectives result in lies in the presence of an objective truth, a distinguishing feature absent in previous text-based deception datasets. We show that there exists a class of detectors with similar truth detection performance as humans, even when the former accesses only the language cues while the latter detects lies using both language and audio-visual cues. Our model detects novel but accurate language cues in many cases where humans failed to detect deception, opening up the possibility of humans collaborating with algorithms and ameliorating their ability to detect the truth.

Experience, Learning and the Detection of Deception
with Priyodarshi Banerjee and Sanmitra Ghosh
Published, July 2023
Journal of Economic Criminology
paper | slides

Deceptive communication or behavior can inflict loss, making it important to be able to distinguish these from trustworthy ones. This article pursues the hypothesis that repeated exposure or experience can cause learning and hence better detection of deception. We investigate using data culled from events in a TV game show. Decision-makers in the show repeatedly faced situations where they had to correctly identify an individual from within a group all claiming to be that individual. Increased experience reduced average detection error in the sample. Analysis of the data suggested this relationship was significant and driven by learning.


Working Papers

The Good, the Bad and the Ugly: Effects of AI Quality Information on Detecting Text-Based Lies
with Bodhisattwa P. Majumder, Haimanti Bhattacharya, and Subhasish Dugar
Work in Progress

Lies in textual form are pervasive on social media, yet evidence regarding individuals' ability to discern truth from deceptive textual content is scarce. To address this knwoeldge gap, we conduct an experiment on Prolific to investigate (1) people's ability in detecting lies in text, and additionally, (2) how their willingness to seek assistance from an artificial intelligence system (AI) in identifying lies varies with and without information about the AI's efficacy.

Hallucination and LLMs
with Marta Serra-Garcia
Work in Progress

We examine whether individuals can identify factual incorrectness in an LLM (GPT) when asked questions about different US and international policy-relevant topics. Detecting hallucinations is challenging, and current LLMs struggle with this task, making it crucial to distinguish between hallucinated text and factual statements, especially given GPT's dominance in internet search platforms.

Adoption of AI-assistance in Scientific Writing
with Bodhisattwa P. Majumder, Sachin Kumar
Work in Progress

A less studied use case of generative AI, which we plan to focus on in this work, is scientific writing. Scientific writing is an inherently iterative process, often involving multiple revisions to refine clarity, accuracy, coherence, and readability while presenting complex scientific ideas. Not all writers have the same domain expertise. We envision a three-phase randomized controlled trial of increasing complexity to conduct this evaluation simulating a peer-reviewed process in a journal or conference publication.

Funding Fanny - Microfinance and Empowerment of Women in India
with Sanchita Sen
Bachelors Thesis
Oral presentation at International Conference on Sustainable Development and Education, 2020
Oral presentation at Research Scholar's Workshop 2020, Visva-Bharati

paper

Women make up a substantial majority of India's poor and they are the cruelest victims of the society. Organizing women through Self Help Groups and equipping them to undertake income-generating activities through the formation of microenterprises have created an economic revolution in the country. The paper focuses on the scope and rationale of microfinance in India and how the Self Help Group-Bank Linkage Programme by NABARD has played its part in empowering rural women financially. We find positive increase in loan disbursements, but sheer increase in loan outstanding over a period of ten years.

Awards
  • [2024] CSBS Graduate Travel Awards, The University of Utah
  • [2024] Haskell Graduate Student Research Award of $1,500, Department of Economics, The University of Utah
  • [2023] Research Award of $3,000, Global Change and Sustainability Center and the Wilkes Center for Climate Science & Policy, The University of Utah
  • [2023] Graduate Student Travel Assistance Award, The University of Utah
Talks
  • [2024] The Good, the Bad and the Ugly: Effects of AI Quality Information on Detecting Text-Based Lies at NABETech, Seattle.
  • [2024] The Good, the Bad and the Ugly: Effects of AI Quality Information on Detecting Text-Based Lies at ESA, Columbus.
  • [2024] The Good, the Bad and the Ugly: Effects of AI Quality Information on Detecting Text-Based Lies at Summer School, Soleto, Italy.
  • [2024] Humans, Artificial Intelligence, and (Text-based) Misinformation at WEAI, Seattle.
  • [2023] Humans, Artificial Intelligence, and (Text-based) Misinformation at North American ESA.
  • [2023] Experience, Learning and the Detection of Deception at WEAI, San Diego.
  • [2021] Experience, Learning and the Detection of Deception at Behavioral Econ Workshop, UofU.
  • [2020] Funding Fanny--Microfinance and Empowerment of Women in India at Intl Conf on Sustainable Dev & Edu.
Teaching
  • Instructor, Principles of Macroeconomics, Econ 2010, Summer24, UofU
  • Instructor, Principles of Microeconomics, Econ 2010, Fall24, Spring24, Fall23, UofU
  • Instructor, Intermediate Microeconomics, Econ 4010; Summer23, UofU
  • Instructor, Intermediate Microeconomics, Econ 6010; Summer23, UofU
  • Instructor, Q-Pod Tutoring; Spring24, Spring23, Fall22
  • Lecturer, Spring Semester 2021, Women's Christian College, University of Calcutta

© Sanchaita Hazra
Thanks to Jon Barron for this nice template
Vibrant Kolkata skyline art is from here