Master Thesis

Algorithm Fairness Label

A concept how design can be used to deal with algorithmic bias.

Research

How can design be used to minimize algorithmic biases?

Approach & Visualization

  • Designing an understandable  representation of the problem to make the debate about algorithmic systems accessible to the general public.

  • Five communication guidelines to provide guidance in dealing with algorithmic biases.

  • A concept of a seal of approval to expose algorithms that are operating unethically.
Cooperation project with Johannes Maas
My responsibility: Concept & Design

Hochschule München | Master Advanced Design 

2018

Digital ethics research

How to use design
to deal with algorithmic bias

Problem

  • Subjectivity of algorithms and the influence of their decisions
  • False, discriminating results
    -> Algorithmic Bias

Solution

  • Communication Guidelines for AI and Algorithmic Bias
  • Algorithmic Fairness Label

The label

Algorithm Fairness Label –
A kind of seal of approval for automated systems with the aim of detecting unethical algorithms in terms of fairness and transparent communication.

Prototype

  • Evaluation according to the degree of bias of the algorithm.
  • Measured by “reverse engineering” (analysis of the result and reverse engineering of the algorithm).

Communication Guidelines

What criteria are used
for the evaluation?

Sensitivity

To make an algorithm fair, it must be clearly communicated that you are dealing with automated decision making processes.

Transparency

Informations have to be retraceable and communicated transparently.

Accessibility

Information has to be fully accessible. Unpleasant information has to be communicated equally.

Human Judgement

Humans have to be integrated into the decision making process of algorithms.

Ethical Importance

Potential consequences caused by the algorithm must be assessed.

Infographic

With playful animation, simplified shapes and friendly colors, the process of algorithmic decision making is presented here. The algorithm runs through various parameters, such as gender, age, etc. to make the decision. 

Exhibition

Push Conference
2019

Daniela Schneider

User Interface | Visual Design

Privacy & Data

Daniela Schneider

User Interface | Visual Design

Quick links

Privacy & Data

Daniela Schneider

User Interface | Visual Design

Quick links

Privacy & Data