Fairness in KI-Systemen

07/17/2023
by   Janine Strotherm, et al.
0

The more AI-assisted decisions affect people's lives, the more important the fairness of such decisions becomes. In this chapter, we provide an introduction to research on fairness in machine learning. We explain the main fairness definitions and strategies for achieving fairness using concrete examples and place fairness research in the European context. Our contribution is aimed at an interdisciplinary audience and therefore avoids mathematical formulation but emphasizes visualizations and examples. – Je mehr KI-gestützte Entscheidungen das Leben von Menschen betreffen, desto wichtiger ist die Fairness solcher Entscheidungen. In diesem Kapitel geben wir eine Einführung in die Forschung zu Fairness im maschinellen Lernen. Wir erklären die wesentlichen Fairness-Definitionen und Strategien zur Erreichung von Fairness anhand konkreter Beispiele und ordnen die Fairness-Forschung in den europäischen Kontext ein. Unser Beitrag richtet sich dabei an ein interdisziplinäres Publikum und verzichtet daher auf die mathematische Formulierung sondern betont Visualisierungen und Beispiele.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
11/08/2018

How Do Fairness Definitions Fare? Examining Public Attitudes Towards Algorithmic Definitions of Fairness

What is the best way to define algorithmic fairness? There has been much...
research
05/12/2021

An Introduction to Algorithmic Fairness

In recent years, there has been an increasing awareness of both the publ...
research
02/06/2020

On the Fairness of Name-Based Rationing System for Purchases of Masks Policy

In this paper, mathematical model and condition are built for the analys...
research
02/13/2018

A comparative study of fairness-enhancing interventions in machine learning

Computers are increasingly used to make decisions that have significant ...
research
07/20/2022

Measuring and signing fairness as performance under multiple stakeholder distributions

As learning machines increase their influence on decisions concerning hu...
research
02/07/2023

To Be Forgotten or To Be Fair: Unveiling Fairness Implications of Machine Unlearning Methods

The right to be forgotten (RTBF) is motivated by the desire of people no...
research
07/11/2022

How Robust is your Fair Model? Exploring the Robustness of Diverse Fairness Strategies

With the introduction of machine learning in high-stakes decision making...

Please sign up or login with your details

Forgot password? Click here to reset