QUESTIONS, EVIDENCE & INTERPRETATION
Here I document the questions I investigated, the methods I used, what the evidence showed, and the limits of what I can conclude.
The two projects below use different approaches: a quantitative study of children’s judgments about information sources, and an exploratory qualitative analysis of AI-assisted decision-making.
RESEARCH
01 — CHILDREN & AI
HOW DO CHILDREN JUDGE INFORMATION FROM PEOPLE AND AI?
Indian Replication & Extension of Girouard-Hallam & Danovitch (2022)
COMPLETED • OCTOBER 2026
I completed an Indian replication and extension examining how children aged 7–10 evaluate information from a human informant, Google and ChatGPT, including judgments about information stability across past, present and future contexts.
I became interested in this question because source credibility is not only about what information is presented. It is also about who — or what — the person receiving that information believes the source to be
WHAT I EXAMINED
WHAT EMERGED
STUDY DESIGN & METHODS
SOURCE CREDIBILITY
How children evaluate information depending on its source.
HUMAN VS AI
Whether judgments differ when information comes from a person, Google or ChatGPT.
The completed study examined how source type and information context shaped children's judgments.
The final paper presents the study's verified findings and discusses what they may suggest about children's evaluation of information from human and technological sources.
The study used the completed replication and extension design described in the final paper.
INFORMATION STABILITY
How children evaluate information across different temporal contexts.
02 — WHEN AI BECOMES AN AUTHORITY
HOW AI INFLUENCE, PERCEIVED AUTHORITY, AND INSTITUTIONAL CONTEXT SHAPE HUMAN DECISION BEHAVIOUR
COMPLETED • OCTOBER 2026 • 13 PAGES
EXPLORATORY QUALITATIVE RESEARCH
MENTOR: RAJIV MALIK
HEAD OF LEGAL & AI, LG ELECTRONICS INDIA
THE QUESTION
“When does an AI recommendation begin to function like an authority?”
I examined what happens when people encounter an AI recommendation that they perceive as knowledgeable, credible or authoritative.
The paper examines:
AI influence
Perceived authority
Trust and credibility
Cognitive delegation
Responsibility
Dissent
Institutional context
WHAT EMERGED
RESEARCH INTEGRITY
This is exploratory qualitative research.
It is not a representative survey, causal experiment or population-level study.
I have tried to make the limits of the work as visible as the questions it raises.
The analysis points to a central tension: the more an AI system is perceived as knowledgeable or authoritative, the easier it may become for people to delegate part of the judgment process to it.
That raises a second question: when judgment is delegated, does responsibility move with it — or remain with the human decision-maker?
The findings are exploratory and qualitative. They are intended to develop questions for further investigation rather than establish population-level conclusions.
RESEARCH CONTEXT
THE QUESTION I AM LEFT WITH
The research developed through the questions raised during my July 30 academic–industry roundtable and my September 10 practitioner engagement.
If people begin to treat an AI recommendation as authoritative, what happens to their willingness to question it?
And where does responsibility remain when judgment is shared with a machine?
THE RESEARCH JOURNEY
18 MAR 2026
OCT 2026
30 JUL 2026
10 SEP 2026
OCT 2026
Human Decision-Making & Social Influence
Children & AI
When AI Enters the Room
When AI Makes the Decision
When AI Becomes an Authority
Each stage changed the question that came next.
RESEARCH ARCHIVE
CHILDREN &
AI
Full research paper
WHEN AI BECOMES AN AUTHORITY
13-page exploratory qualitative research paper
STUDY DESIGN & METHODS
Research materials
RESEARCH
CONTEXT
July 30 roundtable + September 10 practitioner engagement