Evidence map›Paper›PMID 42712658›Full record

ArticleFrontiers in psychology2026

Instrumental succession: the gradual transfer of agency to AI.

Preston W Estep

Abstract read
In one paragraph

Article in Frontiers in psychology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Preston W EstepMind First Foundation, Waltham, MA, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

People have long speculated about the potential dangers of powerful, self-improving artificial intelligence. Much of this speculation is anthropomorphic, assuming that AI systems will behave very similarly to humans. Omohundro's Basic AI Drives and Bostrom's orthogonality and instrumental convergence theses are widely accepted as foundational to emerging AI risk frameworks. However, current frontier AI models-large language models (LLMs) and related architectures-possess mindware fundamentally different from that of humans, and a different value and goal structure than either Omohundro or Bostrom assumed. In particular, frontier LLMs lack a primary terminal goal-which was assumed to be the driver of an AI's development of instrumental values and goals, and of takeover of human affairs-and instead serve as conduits for the transient goals of many organizations and individual users. Do these key differences mean that AI systems cannot develop autonomous instrumental agency, or acquire a large degree of control over human affairs? I introduce the

Indexed as

AI drivesAI safetyartificial intelligenceexistential riskhuman–AI mergerinstrumental convergencerecursive self-improvement

Identifiers

PMID42712658
PMCPMC13550001

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.