Evidence map›Paper›PMID 40919363›Full record

ArticlePerspectives on behavior science2025

Ethical Behavior Analysis in the Age of Artificial Intelligence (AI): The Importance of Understanding Model Building while Formal AI Literacy Curricula are Developed.

David J Cox

Abstract read
In one paragraph

Article in Perspectives on behavior science, 2025. 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.

David J CoxInstitute for Applied Behavioral Science, Endicott College, Beverly, MA USA.ORCID 0000-0003-4376-2104

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Ethics is fundamentally concerned with claims of "right," "wrong," "good," "bad," and how we might know those claims are accurate. Artificial intelligence (AI) is a term that represents a suite of tools where nonbiological systems process data and information to generate an output considered "intelligent." As with any suite of technologies, choosing the right tool requires the tool user to critically evaluate which tool is best for the task (if one exists). Harnessing the power of AI systems to maximize benefit and minimize harm requires basic AI literacy. AI literacy requires a basic understanding of how mathematical models function. All future behavior analysts will need to be AI literate. This will require changes to education and training programs to ensure students have a basic understanding of model building, especially as we wait for the scholarship and research to unfold that outlines AI literacy skills specific to behavior analysts.

Indexed as

AI ethicsAI literacyArtificial intelligenceBehavior analysisQuantitative models

Identifiers

PMID40919363
PMCPMC12411336

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.