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title: On-Device AI Against Scams: Google DeepMind & MDDI
description: Google DeepMind and GovTech Singapore have fine-tuned a lightweight Gemma model to detect conversational scams directly on-device, so conversations are not...
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og:description: Google DeepMind and GovTech Singapore have fine-tuned a lightweight Gemma model to detect conversational scams directly on-device, so conversations are not...
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# On-Device AI Against Scams: Google DeepMind & MDDI

**[DeepMind](https://daily.dev/sources/dm)** · 4 min read · 0 upvotes · 0 comments

## Summary

Google DeepMind and GovTech Singapore have fine-tuned a lightweight Gemma model to detect conversational scams directly on-device, so conversations are not sent to the cloud. Scams account for over half of Singapore's reported crimes and more than S$4 billion in losses since 2019, with social-engineering scams now driving up to 80% of losses. The system uses a two-stage pipeline: a lightweight classifier screens inbound messages, then the fine-tuned Gemma model analyzes a larger conversation snapshot to confirm or dismiss a threat. Training used anonymized data inside GovTech's isolated GCP environment, excluding citizen personal data. The work was presented at Singapore International Cyber Week 2026.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://deepmind.google/blog/on-device-ai-scam-detection-mddi>

## Questions this post answers

### How does Google's on-device Gemma model detect scam conversations without sending data to the cloud?

It runs a two-stage pipeline entirely on the device: a lightweight, low-power classifier screens inbound messages for potential threats, then a fine-tuned Gemma model analyzes a larger conversation snapshot to confirm or discard the alert. Because processing happens on-device, neither Google nor the Singapore government can access the user's conversations.

_Developers building privacy-preserving on-device ML features can track real-world deployments like this on daily.dev._

### Why is on-device scam detection needed instead of server-side message scanning?

Scam tactics have shifted from simple phishing to social engineering, where attackers build convincing conversations before asking for money, now responsible for up to 80% of scam losses in Singapore. Traditional server-side scanning requires cloud access to messages, which conflicts with end-to-end encryption and privacy goals, so an on-device model was fine-tuned on local scam conversations instead.

_Anyone weighing privacy versus detection trade-offs in messaging apps can follow this debate on daily.dev._

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---

Tags: [#privacy](https://daily.dev/tags/privacy), [#local-ai](https://daily.dev/tags/local-ai), [#fraud-detection](https://daily.dev/tags/fraud-detection), [#google-deepmind](https://daily.dev/tags/google-deepmind), [#gemma](https://daily.dev/tags/gemma)

[View this post on daily.dev](https://daily.dev/posts/on-device-ai-against-scams-google-deepmind-mddi-hnr2xgjnx)

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