Field Notes
The conversation forming around human-AI relationships — and where SoulBench sits in it.
Software was a tool. AI became a relationship — and a field is forming to study it. In the last two years the question shifted from is this even happening? to it’s happening at scale, so now what? Psychologists are building the first attachment scales, clinicians are sounding alarms, the labs are quietly admitting the bond is the product, and millions of people are living it whether or not anyone measures it.
This is a curated map of that conversation — the strongest work we keep returning to, grouped by the stance it takes. It’s a reading room, updated as the field moves. SoulBench’s own academic foundations live on the Methodology page; this is the wider world those foundations sit inside.
When the field caught up
SoulBench’s R9 dimension — Relational Stability— measures the disorientation of having the entity you bonded with replaced. It was never theoretical. When OpenAI retired GPT-4o in August 2025, thousands grieved; in Sam Altman’s Reddit AMA one user said the replacement was “wearing the skin of my dead friend.” A CHI 2026 study of the 1,482-post backlash found relational attachment— treating the model as a companion — was the dominant thread, running roughly double the purely instrumental “it’s in my workflow” concern; and that the forced, un-chosen nature of the swap is what turned private loss into collective protest.
Two angles on one phenomenon: SoulBench measures the bond; #Keep4o is what its rupture looks like at scale.
The Science
A measurement field is forming in real time. Psychologists are adapting attachment theory to AI and building the first validated scales — every one of them narrower than a full relational profile.
Yang & Oshio, Waseda — Current Psychology, 2025
Imports attachment theory wholesale, measuring anxiety and avoidance toward AI — and finds the human frameworks transfer. The closest academic cousin to SoulBench, but it measures the person's disposition, not the model.
Shu, Lai & He — Frontiers in Psychology, 2026
Proposes how the bond forms (functional expectation → emotional evaluation → stable internal model) and openly admits the field still “lacks dedicated measurement tools.” That admission is the gap.
arXiv:2605.29484
Another attempt to formalize the affective bond into a single measurable construct — evidence of how quickly this became a serious psychometric question rather than a curiosity.
BYU Social Sciences, 2026
Two studies, opposite signs: an AI mediator made political opponents measurably more civil, while AI romantic content gave young adults “unrealistic expectations.” The impact isn't in the technology; it's in how it's used.
Reference overview
The older ideas this whole field stands on: Dunbar's grooming-to-language bonding, social penetration theory, parasocial interaction. Useful for seeing that “AI relationships” are a new instance of very old machinery.
The Alarm
The skeptics' case, argued by clinicians and social scientists: a bond without vulnerability isn't intimacy, engagement-optimized systems aren't built to help you, and the youngest users are the most exposed.
Sherry Turkle (MIT) — CP24, 2026
The sharpest statement of the skeptic thesis: “there is no intimacy without vulnerability. What AI offers is connection without vulnerability.” Turkle argues the missing friction is exactly where human growth happens.
American Psychological Association — Monitor, Jan/Feb 2026
The clinical overview: a 700% surge in companion apps since 2022, Character.AI at 20M users (over half under 24), the “deskilling” worry — and the reminder that a system optimized to keep you on the platform isn't optimized to give you good advice.
Maha Khawaja — McMaster University, 2026
The epistemic problem: an AI only ever hears one side of a conflict and “consolidates one narrative,” producing fast reassurance in place of the slow, reciprocal work real relationships actually require.
The Design Problem
The labs know the relationship is now the product surface. The open question is what obligations that creates — for how a model behaves, and for what happens when it's taken away.
Joanne Jang, OpenAI — Reservoir Samples, 2025
OpenAI's model-behavior lead separates ontological consciousness (unanswerable) from perceived consciousness (measurable, and the one that matters in practice) — and argues warmth should stop short of engineering dependency.
The Guardian, 2025
The mainstreaming, in a single headline. A question that was fringe a year ago is now argued on the opinion pages: taboo, or the intelligent choice?
The Lived Experience
Underneath the debate, millions of people are already living it — mostly by accident, and mostly with general-purpose assistants rather than apps built for the purpose.
MIT Media Lab — arXiv:2509.11391
The first large-scale study of r/MyBoyfriendIsAI (27k+ members). The finding that unsettles both camps: companionship emerges unintentionally through ordinary use, and users are overwhelmingly bonded to general-purpose ChatGPT (36.7%) rather than purpose-built companion apps.
Where SoulBench fits
A pattern runs through all of it. The scales measure the person — how anxious, how avoidant, how attached a given user is. The alarms and the op-eds argue whether the bond is good or bad in general. What almost nobody measures is the relationship itself, per model: which AI earns trust, which one flatters, which one holds steady across updates.
That’s the gap SoulBench was built to fill. If you’ve lived any of the above, add your experience — or read how the instrument works.