Evidence map›Paper›PMID 37680588›Full record

ArticleFrontiers in artificial intelligence2023

Machine vs. human, who makes a better judgment on innovation? Take GPT-4 for example.

Mark Du

Abstract read
In one paragraph

Article in Frontiers in artificial intelligence, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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.

Mark DuDepartment of Computer Science, National Taiwan University, New Taipei, Taiwan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Human decision-making is a complex process that is often influenced by various external and internal factors. One such factor is noise, random, and irrelevant influences that can skew outcomes. Methods: This essay uses the CAT test and computer simulations to measure creativity. Results: Evidence indicates that humans are intrinsically prone to noise, leading to inconsistent and, at times, inaccurate decisions. In contrast, simple rules demonstrate a higher level of accuracy and consistency, while artificial intelligence demonstrates an even higher capability to process vast data and employ logical algorithms. Discussion: The potential of AI, particularly its intuitive capabilities, might be surpassing human intuition in specific decision-making scenarios. This raises crucial questions about the future roles of humans and machines in decision-making spheres, especially in domains where precision is paramount.

Indexed as

artificial intelligencecreativityGPT-4large language models (LLM)noise

Identifiers

PMID37680588
PMCPMC10482032

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.