Trustworthy data-centric geotechnics

There are two major technology related changes that are widely viewed as seismic. One is the emergence of artificial intelligence (AI) that is close to passing the Turing test. The second is the introduction of the first AI Act in the European Union (EU). The former portends business opportunities that are too large to ignore in all industries. The latter mandates businesses to manage risks appropriately depending on the impact of AI systems on individuals and society. Machine learning (ML) and AI are at most deployed as proofs of concept in geotechnics. This perspectives article advocates a greater appetite for data-driven innovations in practice to take advantage of major breakthroughs occurring elsewhere. Besides the obvious benefits to practice and to the stakeholders that we serve, embracing data-centric geotechnics is the only way for geotechnical engineers to remain in the driver seat to deploy ML/AI responsibly and safely. This agenda to introduce trustworthiness explicitly in research and practice is called “trustworthy data-centric geotechnics”. Pockets of preliminary research that relate to trustworthiness are highlighted.

Authors

Institutions

Publication Details

Journal
Geodata and AI.
Published
2024-09-01
DOI
https://doi.org/10.1016/j.geoai.2025.100008
Citations
15
Primary Topic
Geological Modeling and Analysis
Type
article
Field-Weighted Citation Impact
5.19
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Trustworthy data-centric geotechnics

Kok‐Kwang Phoon
15 citations
Geodata and AI.
Geological Modeling and Analysis
5.19
article

Trustworthy data-centric geotechnics

Kok‐Kwang Phoon
article en
15 citations

Abstract

There are two major technology related changes that are widely viewed as seismic. One is the emergence of artificial intelligence (AI) that is close to passing the Turing test. The second is the introduction of the first AI Act in the European Union (EU). The former portends business opportunities that are too large to ignore in all industries. The latter mandates businesses to manage risks appropriately depending on the impact of AI systems on individuals and society. Machine learning (ML) and AI are at most deployed as proofs of concept in geotechnics. This perspectives article advocates a greater appetite for data-driven innovations in practice to take advantage of major breakthroughs occurring elsewhere. Besides the obvious benefits to practice and to the stakeholders that we serve, embracing data-centric geotechnics is the only way for geotechnical engineers to remain in the driver seat to deploy ML/AI responsibly and safely. This agenda to introduce trustworthiness explicitly in research and practice is called “trustworthy data-centric geotechnics”. Pockets of preliminary research that relate to trustworthiness are highlighted.

Geodata and AI.Vol. 1
Singapore University of Technology and Design (SG)
Openalex Percentile: Top 4%
Geological Modeling and Analysis
5.19
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.

Trustworthy data-centric geotechnics — Kok‐Kwang Phoon · Geodata and AI. (2024) | TGRS Research Map | TGRS