Warnings!!

I T E this at the end of October 2024, artificial intelligence (AI) continues to be Topic A in many discussions.So too are recommendation algorithms in social media.Misinformation and disinformation rank high across many areas of socioeconomic concerns.We are even seeing misinformation about the Federal response to severe storms interfering with our ability to render aid.Why is it that we are attracted to and respond so readily to alarming information?I have a rather unscientific theory about this.Well, it isn't grounded in solid data, but it is a cartoon model of the way I think of the phenomenon.I think sensitivity to warnings is likely a genetic survival trait for all species, especially those with some level of cognition.I include non-human species in that category.Warning calls are common across many species.Humans have benefited from such warnings by surviving to contribute to the gene pool.Many who ignored warnings did not survive and did not contribute.Thus, when we read, see, or hear warnings, we respond almost automatically."It's a bear!Run!" (Actually, I hear running from a bear is actually bad advice).Social media influencers take advantage of recommendation algorithms that steer users toward perceived interests and the scale at which these systems operate.The same mechanisms that might select advertisements of interest may also steer users toward information, including warnings that appear to be of interest or concern.None of this is a new realization.My longtime friend and colleague, Peter G.

Authors

Institutions

Publication Details

Journal
Communications of the ACM
Published
2024-11-22
DOI
https://doi.org/10.1145/3701556
Primary Topic
Risk and Safety Analysis
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Warnings!!

Vinton G. Cerf
Communications of the ACM
Risk and Safety Analysis
article

Warnings!!

Vinton G. Cerf
article en

Abstract

I T E this at the end of October 2024, artificial intelligence (AI) continues to be Topic A in many discussions.So too are recommendation algorithms in social media.Misinformation and disinformation rank high across many areas of socioeconomic concerns.We are even seeing misinformation about the Federal response to severe storms interfering with our ability to render aid.Why is it that we are attracted to and respond so readily to alarming information?I have a rather unscientific theory about this.Well, it isn't grounded in solid data, but it is a cartoon model of the way I think of the phenomenon.I think sensitivity to warnings is likely a genetic survival trait for all species, especially those with some level of cognition.I include non-human species in that category.Warning calls are common across many species.Humans have benefited from such warnings by surviving to contribute to the gene pool.Many who ignored warnings did not survive and did not contribute.Thus, when we read, see, or hear warnings, we respond almost automatically."It's a bear!Run!" (Actually, I hear running from a bear is actually bad advice).Social media influencers take advantage of recommendation algorithms that steer users toward perceived interests and the scale at which these systems operate.The same mechanisms that might select advertisements of interest may also steer users toward information, including warnings that appear to be of interest or concern.None of this is a new realization.My longtime friend and colleague, Peter G.

Communications of the ACMVol. 67(12)
Google (United States) (US)
Openalex Percentile: Top 79%
Risk and Safety Analysis
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.