My AI-Assisted Research
My principles on AI-assisted research process, responsible innovation, and the evolving role of researchers in this AI-enabled world.
Augmentation First
Research begins with human curiosity, context, and interpretation. I use AI to create more opportunities to expand research thinking. My search-heavy work is accelerated through fast access to knowledge, while siloed work is enriched using a readily available partner for collaboration, exploration, and critique
How this shows up in my work:
Research planning and brainstorming
Consolidation and information organization
Critique and challenge exercises
Extended Reflexivity
With AI introducing its own assumptions and biases into the research process, reflexivity must extend beyond the researcher to include the systems we work with. I use AI to behave as an external auditor to challenge both our my assumptions to achieve a self-reflective practice.
How this shows up in my work:
Agent-assisted reflexivity
Assumption checks
Bias exploration form multiple perspectives
Deliberate Guardrails
Through my Responsible AI work, I've become advocate of UXRs defining where AI should support research and where human judgment should remain central. I treat Responsible AI as an ongoing practice. As technology evolves, guardrails help preserve rigor, accountability, and human agency.
How this shows up in my work:
Advocacy for appropriate AI usage
Alternative framing generation
AI readiness and adoption work
Research governance discussions
Cross-LLM validation
Responsible AI guidelines development
AI continues to reshape both the products we build and the way research is practiced. My goal is to thoughtfully evolve it.
How I Work
I use attention as leverage at every stage of research.
Asking questions about the entire work context- what decision will it inform? What risks must it reduce?
Purposeful Positioning
From behavioral nuance to larger ecosystems- insight lies where small interaction patterns reflect larger systemic forces.
Leveraging Layers
Making tradeoffs explicit so teams move with clarity on what they are choosing, and not choosing, to build.
Tension and Tradeoffs
Research is a connective discipline. I partner closely with Product, Design, and Engineering from the outset to align on the decision to be made, defining success criteria together, and agreeing on how evidence will inform direction. Accountability for decisions is shared, not delegated to research.
When there is pushback or competing priorities, I surface tradeoffs explicitly, especially for high stakes, highly ambiguous, and difficult to reverse decisions:
Decision: What are we actually trying to shape using the research?
Risk: What happens if we’re wrong?
Evidence: What signals support certain directions?
For me, this is the power of research- the decisions it enables and the futures it shapes.