On-device AI protection without compromising privacy
Generic models often struggle with local deception techniques, making scam detection harder. To address this, Google’s lightweight Gemma model was fine-tuned on local scam conversations. These ranged from impersonations of public institutions, banks, and local figures, to trending regional schemes. This ensures the fine-tuned model will be able to distinguish benign social chatter from genuine manipulation when deployed in applications installed by citizens.
Unlike traditional threat detection, which relies on server-side scanning of messages in the cloud, this model can process conversation data directly on-device. When integrated into applications, this will allow faster analysis of conversation patterns to detect manipulative intent and help citizens act before financial or credential exposure can occur.
The roll out of the model within applications will be carefully phased and developed in partnership with the Singapore Government. When deployed, the model will only be able to access on-device conversations with the user's consent, in accordance with the terms of use of that application. As the model runs entirely on-device, neither the Singapore Government nor Google, will be able to access users’ conversations through its deployment.
— Source: DeepMind Blog (https://deepmind.google/blog/on-device-ai-scam-detection-mddi/)
