In this talk, I aim to address a major challenge in the adoption of user-centred privacy-enhancing technologies: Can we leverage novel architectures to provide private, trusted, personalised, and dynamically- configurable models on consumer devices to cater for heterogeneous environments and user requirements? Importantly, such properties must provide assurances for the data integrity and model authenticity/trustworthiness, while respecting the privacy of the individuals taking part in training and improving such models. Innovation and adoption in this space require collaborations between device manufacturers, platform providers, network operators, regulators, and the users.