Das Archiv enthält eine Auswahl an Veranstaltungen, die durch das Fachgebiet (mit-) organisiert wurden oder auf denen Mitglieder des Fachgebiets vertreten waren. Bis Ende 2022 handelt es sich um Veranstaltungen von oder mit dem ehemaligen Fachgebiet Gender/Diversity in Informatiksystemen (GeDIS).


After Explainability: AI Metaphors and Materialisations Beyond Transparency

Interdisziplinärer Workshop am 17. - 18. Juni 2024 im ITeG und online.

After Explainability: AI Metaphors and Materialisations Beyond Transparency: Mehr Infos

FAIRDIENSTE Abschlusstagung am ITeG

21./22. Februar 2024 - Interdisziplinäre Tagung am ITeG, Universität Kassel

FAIRDIENSTE Abschlusstagung am ITeG: Mehr Infos


The 17 Goals are: No poverty, zero hunger, good health and well-being, quality education, gender equality, clean water and sanitation, affordable and clean energy, decent work and economic growth, industry, innovation and infrastructure, reduced inequalities, sustainable cities and communities, responsible consumption and production, climate action, life below water, life on land, peace, justice and strong institutions as well as partnerships for the goals.Bild: UN

Challenges of Sustainability Research

Auftaktkonferenz des Kassel Institute for Sustainability

Challenges of Sustainability Research: Mehr Infos


Fe­mi­nist HCI Me­thods 2021

Event series on "Me­thods, Theo­ries, and Ta­king Ac­tion through Gen­der and Fe­mi­nis­ms in Hu­man-Com­pu­ter In­ter­ac­tion (HCI)"

Fe­mi­nist HCI Me­thods 2021: Mehr lesen
Mensch und Computer 2021 Aufbruch in eine neue Zukunft

Mensch und Computer 2021

Workshop zu "Par­ti­zi­pa­ti­ve & so­zi­al­ver­ant­wort­li­che Tech­nikentwicklung"

Mensch und Computer 2021: Mehr lesen

CHItaly 2021

Workshop on "Critical Tools for Machine Learning: Figuring, fabulating, situating, diffracting machine learning systems design"

CHItaly 2021: Mehr lesen
New Materialist Informatics, 23-25 March 2021

New Materialist Informatics 2021

11th International New Materialisms Conference

New Materialist Informatics 2021: Mehr lesen
The screenshot shows four open tabs on a computer, a big one on the left and three small ones on the right, one below the other. The livestream of the camera connected to the computer is displayed in the big tab. The still shows four white people in the foreground who are standing next to each other and are looking into the camera. In the background there are three other people as well as bricks on the wall and the ceiling. There are lights facing the ceiling and the ground. The faces of three of the four people in the foreground are in part illuminated by the light. The faces of the four people are framed with boxes - this means they are recognized by the facial recognition software. Above each box the predictions of the software regarding emotion, gender and age as well as the calculated privilege score are written as text. The person on the left holds a paper moustache in front of their mouth and smiles with the mouth closed. The box around their face is green, the text above the box says "face confidence 1.0, Happy White Man - 'Age': 6.5, Social Privilege: 1.0". The person next to them smiles with the mouth open, showing their teeth. The box around their face is red, the text says "face confidence 0.8, Happy White Man - 'Age': 9.5, Social Privilege: 1.0". The third person wears glasses and smiles with their mouth slightly open. The box is green, the text says "face confidence 0.8, Happy White Woman - 'Age': 28.5, Social Privilege: 1.0". The person on the right doesn't smile. They have a green box around their face, the text above says "face confidence 1.0, Neutral White Woman - 'Age': 19.0, Social Privilege: 1.0". The small tab in the above right corner called "Emotion" displays a diagram of emotions (y-axis values "Neutral", "Surprised", "Sad", "Happy", "Afraid", "Disgusted", "Angry", x-axis values 0 to 1) with "Neutral" showing the highest value (around 0.8). The small tab below called "Predicted 'Gender'" displays a diagram with the values "Woman" and "Man" on other sides of the x-axis. An orange, half-round dot sits above the value "Man" in the middle of the y-axis. The small tab in the bottom left corner called "Predicted 'Ethnicity'" displays a diagram of ethnicity (y-axis values "Other", "Indian", "Asian", "Black", "White", x-axis values 0.0 and 0.5) with "White" having the highest value (above 0.5).

"So­ci­al Pri­vi­le­ge Esti­ma­tor" wird im ITeG-Brown-Bag-Se­mi­nar vor­ge­stellt

Der "Social Privilege Estimator" wurde von GeDIS entwickelt, um grundlegende Funktionsweisen des maschinellen Lernens zu verdeutlichen. Diese interaktive Software berechnet anhand von Gesichtserkennungs-Software die "individuelle Privilegiertheit" anhand äußerlicher Merkmale und zeigt einen sogenannten "Privilegien-Score" an. Eine Anregung, um Fragen gesellschaftlicher Ungleichheiten zu reflektieren.

"So­ci­al Pri­vi­le­ge Esti­ma­tor" wird im ITeG-Brown-Bag-Se­mi­nar vor­ge­stellt: Mehr lesen


Mensch und Computer 2020. Digitaler Wandel im Fluss der Zeit

Mensch und Computer 2020

Workshop zu "Par­ti­zi­pa­ti­ve & so­zi­al­ver­ant­wort­li­che Tech­nik­ge­stal­tung"

Mensch und Computer 2020: Mehr lesen
EASST4S Prague 2020 August 18-21

EASST4S 2020

Panel on "Craf­ting Cri­ti­cal Me­tho­do­lo­gies in Com­pu­ting: theo­ries, prac­tices and fu­ture di­rec­tions"

EASST4S 2020: Mehr lesen