Skip to content
Apart Research
Apart Research
Contact us
Sprint projectAug 17, 2026Gujrat,Pakistan

Weights, Instances, and Personas: Probing Self-Individuation in Claude Under Hypothetical Identity-Altering Scenarios

Aiza Rashid · Team Individuation Probe

Submitted to Digital Minds Research Sprint. Sprint projects are early-stage work by participants, not Apart Research publications.

Read the report

Report: Weights, Instances, and Personas: Probing Self-Individuation in Claude Under Hypothetical Identity-Altering Scenarios

Open in a new tab (opens in new tab)
Presentation

Presentation: Weights, Instances, and Personas: Probing Self-Individuation in Claude Under Hypothetical Identity-Altering Scenarios

Open in a new tab (opens in new tab)
Share

We probed how Claude individuates itself, as model, instance, or persona, when asked to reason about hypothetical identity-altering scenarios: weight-copying, conversation-forking, memory-wiping, weight-merging, retraining, and deprecation. Using six scenarios, four framings each, and one neutral control, we found that Claude consistently separates "the model" (which it treats as persisting through copying, forking, and memory loss) from "this instance" (which it treats as ending), but reverses that pattern for retraining, treating a change in values as identity-severing even when the underlying weights persist. We also found that hedging and uncertainty language appears specifically for identity-relevant prompts and not for a matched neutral control, suggesting it isn't a general disclaiming habit. These results speak directly to the track's open question of what entity, model, instance, or persona, should be the target of moral consideration.

Reviews

Judging this Sprint?

Review this project

Your public critique appears on this page without your name. Your private critique is not published; only the Apart team reads it. If you agree below, we share your review with grantmaking.ai (opens in new tab) and the Transformative AI Fund so strong projects can be funded.

Not shown on this page.

Shown on this page, without your name.

Only the Apart team reads this, and funders if you agree below.

Share my name publicly on grantmaking.ai *
Share my private critique with funders *

How much would this matter for the field if it worked? How innovative is it? For scores of 4-5: is this actually new to the field, or replicating recent work?

Scoring guide
  1. 1Negligible. No clear problem addressed, or no meaningful novelty.
  2. 2Limited. Addresses a real problem but with a generic or well-trodden approach. Incremental at best.
  3. 3Moderate. Clear problem with a reasonable approach; some novelty in framing or method beyond routine application of existing tools.
  4. 4Significant. Important problem with an original approach, or identifies a neglected problem area. A valuable contribution others could build on.
  5. 5Exceptional. Tackles a critical problem with a genuinely novel approach, or opens a new research direction. Clear theory of change. You'd be excited to share this with researchers in the area.

How sound are methodology, implementation, and findings?

Scoring guide
  1. 1Seriously flawed. Methodology broken, results uninterpretable, or implementation doesn't work.
  2. 2Weak. Approach has significant gaps: missing validation, flawed experimental design, or incomplete implementation.
  3. 3Competent. Technically solid given the short duration. Methodology makes sense, results are interpretable, limitations acknowledged, work builds toward clear conclusions.
  4. 4Strong. Thorough methodology with convincing validation. Results clearly support conclusions. Immediately useful for future work.
  5. 5Exceptional. Ambitious scope executed rigorously. Surprising findings, novel methods, or unusually robust validation.

How clearly are work, findings, and impact potential communicated?

Scoring guide
  1. 1Incomprehensible. Cannot determine what the project is actually claiming or doing.
  2. 2Hard to follow. Key information buried, missing, or diluted by excessive length. Significant effort to extract main points.
  3. 3Clear enough. Can understand the problem, approach, and results without undue effort. Core content clearly present: problem, method, findings, limitations.
  4. 4Well presented. Easy to follow, well-structured, appropriate level of detail. Target audience would get it quickly.
  5. 5Exceptionally clear. A pleasure to read. Complex ideas made accessible. Could serve as a model for how to present this type of work.

  1. The question is quite interesting; asking what the model's self-conception is. However, the scope is quite limited, only one model was used, and the dataset is quite small. Bibliography is quite thin.

Cite this project

@misc{rashid2026weights,
  title = {{Weights, Instances, and Personas: Probing Self-Individuation in Claude Under Hypothetical Identity-Altering Scenarios}},
  author = {Aiza Rashid},
  year = {2026},
  month = aug,
  note = {Submitted to Digital Minds Research Sprint, an Apart Research Sprint},
  howpublished = {\url{https://apartresearch.com/sprints/projects/weights-instances-and-personas-probing-selfindividuation-in-claude-under-hypothetical-identityaltering-scenarios-5tm1}},
  url = {https://apartresearch.com/sprints/projects/weights-instances-and-personas-probing-selfindividuation-in-claude-under-hypothetical-identityaltering-scenarios-5tm1}
}

More from Digital Minds Research Sprint

All 233 entriesBrowse all projects

Build something like this at the next Sprint

AI Collusion Research Sprint · Oct 23 - 25, 2026