When is Automated Decision Making Legitimate? A book chapter summary by Esha Srivastava

Chapter 2 of Fairness & ML strongly emphasizes on the need for justifiable and interpretable decisions — not just accurate ones.

𝐁𝐥𝐨𝐠 𝐋𝐢𝐧𝐤: aiineverything.blogspot.com/2025/07/when...

@tsonika.bsky.social @tyagilab.bsky.social

#AIethics #FairML #ResponsibleAI #DigitalHealthReadingGroup #TyagiLab

Legitimacy vs Fairness in automated decision making.

A summary from our recent book club reading by @esha4.bsky.social of the #TyagiLab

aiineverything.blogspot.com/2025/07/when...

@tsonika.bsky.social

Lab represents at Monash Translation Medicine student symposium and 3MT competition.

Well done!

#3mt #threeminutesthesis #phd #ecr #tyagilab

New Blog: Interpretability vs Explainability in ML
Why understanding model decisions matters for ethical AI.

👉 aiineverything.blogspot.com/2025/07/mach...

With @tyagilab.bsky.social, A/Prof. Sonika Tyagi & Navya Tyagi
#XAI #AIethics #ML #TyagiLab

Navigating the Multiverse: a Hitchhiker’s guide to selecting harmonization methods for multimodal biomedical data Abstract. The application of machine learning (ML) techniques in predictive modelling has greatly advanced our comprehension of biological systems. There i

New publication from the lab @tyagilab.bsky.social academic.oup.com/biomethods/a...

#multimidaldata #biomedicaldata #dataharmonisation #tyagilab

Our updated preprint on @medrxivpreprint.bsky.social from the #TyagiLab

a beginners guide to planing multimodal machine learning analysis on bio/medical data.

LinkedIn This link will take you to a page that’s not on LinkedIn

#hotoffthepress #newpublication from the #TyagiLab

"EHR-ML: A Data-Driven Framework for Designing Machine Learning Applications with Electronic Health Records “

Pre-proof is online now: lnkd.in/gHHrFEGF