ADR Awareness Centre

This Adra-e deliverable presents an analysis of the externalities surrounding acceptability and trustworthiness in ADR-supported innovative technologies.

When deployed, machine-learning (ML) adoption depends on its ability to actually deliver the expected service safely, and to meet user expectations in terms of quality and continuity of service.

Since Alan Turing envisioned artificial intelligence, technical progress has often been measured by the ability to defeat humans in zero-sum encounters (e.g., Chess, Poker, or Go).

Advances in artificial intelligence and robotics may be leading to a new industrial revolution. This paper presents a model with the minimum necessary features to analyze the implications for inequality and output.

This paper introduces a multilingual, multispeaker dataset composed of synthetic and natural speech, designed to foster research and benchmarking in synthetic speech detection.

Code for Word-Class Embeddings (WCEs), a form of supervised embeddings especially suited for multiclass text classification.