Student or educator? Sign up with your school email and get 6 months of Pro free.
CoChat
Sign Up
Cited by 348

The DOI matches its Crossref record; 42 of the 42 references it cites were found in a registry or an index.

Artificial Intelligence (AI) or Intelligence Augmentation (IA): What Is the Future?

Open access
Hassani, Hossein, Silva, Emmanuel Sirimal, Unger, Stephane, TajMazinani, Maedeh, Mac Feely, Stephen·2020·AI
DOI 10.3390/ai1020008
Open this paper in CoChat — free account

Abstract

Artificial intelligence (AI) is a rapidly growing technological phenomenon that all industries wish to exploit to benefit from efficiency gains and cost reductions. At the macrolevel, AI appears to be capable of replacing humans by undertaking intelligent tasks that were once limited to the human mind. However, another school of thought suggests that instead of being a replacement for the human mind, AI can be used for intelligence augmentation (IA). Accordingly, our research seeks to address these different views, their implications, and potential risks in an age of increased artificial awareness. We show that the ultimate goal of humankind is to achieve IA through the exploitation of AI. Moreover, we articulate the urgent need for ethical frameworks that define how AI should be used to trigger the next level of IA.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.3390/ai1020008

Cites

42 of 42 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 42 references

Cited by

See all 348

Metadata

Authors
Hassani, H., Silva, E. S., Unger, S., TajMazinani, M., & Mac Feely, S.
Venue
AI
Publisher
MDPI AG
Published
2020-04-12
Volume
1
Issue
2
Pages
143-155
ISSN
2673-2688 (ISSN-L)
DOI
10.3390/ai1020008
OpenAlex
W3016094225
Cited by
348
References
42
FWCI
40.20
Type
journal article
Language
en
Open access
gold

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Artificial Intelligence (AI) or Intelligence Augmentation (IA): What Is the Future? https://app.cochat.ai/papers/10.3390/ai1020008
The paper
Hassani, H., Silva, E. S., Unger, S., TajMazinani, M., & Mac Feely, S. (2020). Artificial Intelligence (AI) or Intelligence Augmentation (IA): What Is the Future? AI. https://doi.org/10.3390/ai1020008

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.