Systems and Methods for Predicting Vulnerability to Institutional Gaslighting: A Research Program Proposal

Joshua M. Garfunkel | December 2025

Abstract: This working paper outlines a comprehensive research program addressing three critical gaps: (1) the absence of validated methods to predict who is vulnerable to institutional exploitation, (2) the lack of objective systems to detect manipulation tactics operating invisibly in real-time, and (3) the absence of metrics to quantify psychological harm that is routinely dismissed as “subjective.” We propose an interdisciplinary research framework integrating clinical psychology, computer science, neuroscience, digital ethics, and public health to develop vulnerability prediction systems, manipulation detection algorithms, harm quantification metrics, and therapeutic interventions.

Keywords: institutional manipulation, vulnerability assessment, algorithmic accountability, digital dignity, treatment-resistant conditions, epistemic injustice

Download PDF (10 pages)

Measurement Challenges in Institutional Manipulation Research: A Brief Note

Joshua M. Garfunkel | December 2025

Abstract: Research on institutional manipulation faces a fundamental methodological barrier: the phenomena we seek to study actively resist measurement. This brief note outlines three interlocking challenges—subjective experiences dismissed as unreliable, invisibly operating manipulation tactics, and unpredictable vulnerability—and proposes novel measurement innovations including composite vulnerability assessment, automated manipulation detection, and the Digital Dignity Index.

Keywords: measurement methodology, vulnerability prediction, manipulation detection, psychometrics, research design

Download PDF (6 pages)

This research program seeks to transform comprehensive theoretical frameworks into empirically validated research protocols and functional AI systems.

We are actively seeking university research partners with expertise in:

• Clinical psychology & treatment-resistant conditions
• Computer science, NLP, and machine learning
• Cognitive neuroscience & neuroimaging
• Biostatistics & psychometric validation
• Public health & implementation science

University partnership models under consideration include:

• Research License: University uses IP for research; revenue sharing for commercialization
• Joint Ownership: Shared ownership based on algorithmic contributions
• University Assignment with Royalty: IP assigned to university with inventor royalties

All models prioritize social impact alongside commercial viability, with commitments to:

• Free/low-cost access for vulnerable populations
• Pro bono evidence generation for public interest cases
• Open-source research tools
• Ethical use restrictions (no surveillance applications)

Non-provisional filing deadline: November 2026

Connect With Us