DeepAI AI Chat
Log In Sign Up

Dimensions of Transparency in NLP Applications

01/02/2021
by   Michael Saxon, et al.
7

Broader transparency in descriptions of and communication regarding AI systems is widely considered desirable. This is particularly the case in discussions of fairness and accountability in systems exposed to the general public. However, previous work has suggested that a trade-off exists between greater system transparency and user confusion, where `too much information' clouds a reader's understanding of what a system description means. Unfortunately, transparency is a nebulous concept, difficult to both define and quantify. In this work we address these two issues by proposing a framework for quantifying transparency in system descriptions and apply it to analyze the trade-off between transparency and end-user confusion using NLP conference abstracts.

READ FULL TEXT
12/07/2018

What Are You Hiding? Algorithmic Transparency and User Perceptions

Extensive recent media focus has been directed towards the dark side of ...
11/07/2021

A Word on Machine Ethics: A Response to Jiang et al. (2021)

Ethics is one of the longest standing intellectual endeavors of humanity...
03/27/2021

A Multistakeholder Approach Towards Evaluating AI Transparency Mechanisms

Given that there are a variety of stakeholders involved in, and affected...
04/26/2020

PTPARL-D: Annotated Corpus of 44 years of Portuguese Parliament debates

In a representative democracy, some decide in the name of the rest, and ...
10/24/2022

Good governance and national information transparency: A comparative study of 117 countries

Information transparency is a major building block of responsible govern...
06/03/2018

Two-dimensional optomechanics formed by the graphene sheet and photonic crystal cavity

We theoretically study photon transmission and mechanical ground state c...
06/10/2021

TIRA: An OpenAPI Extension and Toolbox for GDPR Transparency in RESTful Architectures

Transparency - the provision of information about what personal data is ...