Not Every AI Problem Is a Data Problem

Authors

Nino Scherrer (ORCID: https://orcid.org/0000-0001-5976-4257)
Natasha F. Noy (ORCID: https://orcid.org/0000-0002-7437-0624)
Tanya Rodchenko

Institutions

Google (United States) (US)

Publication Details

Journal: Communications of the ACM
Published: 2025-09-23
DOI: https://doi.org/10.1145/3731656
Citations: 1
Primary Topic: Topological and Geometric Data Analysis
Type: article
Field-Weighted Citation Impact: 1.50

Controls

|||

ALL TIME

JAN

FEB

MAR

APR

MAY

JUN

JUL

AUG

SEP

OCT

article

Not Every AI Problem Is a Data Problem

Nino Scherrer, Natasha F. Noy, Tanya Rodchenko

Sep 23, 2025

1 citations

Communications of the ACM

Topological and Geometric Data Analysis

1.50

article

Not Every AI Problem Is a Data Problem

Nino Scherrer, Natasha F. Noy, Tanya Rodchenko

September 23, 2025article en

1 citations

Abstract

No abstract available for this paper.

Communications of the ACMVol. 68(10)

Google (United States) (US)

Openalex Percentile: Top 13%

Topological and Geometric Data Analysis

1.50

DOI Source OpenAlex

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.

Not Every AI Problem Is a Data Problem — Nino Scherrer, Natasha F. Noy, et al. · Communications of the ACM (2025) | TGRS Research Map | TGRS