Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 367

The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.

AI Anxiety

Open access
Johnson, Deborah G., Verdicchio, Mario·2017·Journal of the Association for Information Science and Technology

Abstract

Recently a number of well‐known public figures have expressed concern about the future development of artificial intelligence (AI), by noting that AI could get out of control and affect human beings and society in disastrous ways. Many of these cautionary notes are alarmist and unrealistic, and while there has been some pushback on these concerns, the deep flaws in the thinking that leads to them have not been called out. Much of the fear and trepidation is based on misunderstanding and confusion about what AI is and can ever be. In this work we identify 3 factors that contribute to this “AI anxiety”: an exclusive focus on AI programs that leaves humans out of the picture, confusion about autonomy in computational entities and in humans, and an inaccurate conception of technological development. With this analysis we argue that there are good reasons for anxiety about AI but not for the reasons typically given by AI alarmists.

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 · 10.1002/asi.23867

Cites

3 of 3 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 3 references

Research works printed but not linked: 2

  1. Dreyfus H.L., 1978, What computer can't do
  2. Dreyfus H.L., 1992, What computer still can't do

Cited by

See all 367

Metadata

Authors
Johnson, D. G., & Verdicchio, M.
Venue
Journal of the Association for Information Science and Technology
Publisher
Wiley
Published
2017-06-22
Volume
68
Issue
9
Pages
2267-2270
ISSN
  • 2330-1635 (ISSN-L)
  • 2330-1643
OpenAlex
W4243249985
Cited by
367
References
3
FWCI
9.15
Type
journal article
Language
en
Open access
green

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: AI Anxiety. https://app.cochat.ai/papers/10.1002/asi.23867
The paper
Johnson, D. G., & Verdicchio, M. (2017). AI Anxiety. Journal of the Association for Information Science and Technology. https://doi.org/10.1002/asi.23867

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.