Element 68Element 45Element 44Element 63Element 64Element 43Element 41Element 46Element 47Element 69Element 76Element 62Element 61Element 81Element 82Element 50Element 52Element 79Element 79Element 7Element 8Element 73Element 74Element 17Element 16Element 75Element 13Element 12Element 14Element 15Element 31Element 32Element 59Element 58Element 71Element 70Element 88Element 88Element 56Element 57Element 54Element 55Element 18Element 20Element 23Element 65Element 21Element 22iconsiconsElement 83iconsiconsiconsiconsiconsiconsiconsiconsiconsiconsiconsiconsiconsiconsiconsiconsiconsiconsiconsiconsiconsiconsiconsiconsiconsElement 84iconsiconsElement 36Element 35Element 1Element 27Element 28Element 30Element 29Element 24Element 25Element 2Element 1Element 66
1.
Juli 2019

Our Lives with Algorithms

From detecting anomalies in the landscape of medical images to drone footage to the influencing of elections, machine learning algorithms are transforming radically how we make sense in society. Deep neural net algorithms condense the features of a scene to an output of meaning – such as “a man is throwing a frisbee in a park”, “a woman is standing at the border fence with a crowd in the background”, “the protesters are gathering in the city square”. They reduce the intractable difficulties and the undecidability of what could be happening in a scene into a single meaning that is informing decisions and actions. Is that hate speech or freedom of speech, are people pickpocketing or cuddling, is this a protestor or a terrorist?
 
In order to learn how to make distinctions, however, today’s algorithms require interactions with us and our data. The training and adaptation of algorithms take place through the attributes of our lives and the lives of others. This is problematic because the meaning of our relationships with other beings, how they come to make sense, precisely cannot be condensed. How do we begin to locate these aspects within the algorithm’s programme of sense-making in the digital society? Are there counter-methods available to us that resist the clustering of human attributes via machine learning? What remains in the digital society of that which is unattributable, that which cannot be translated into a single numeric output?

Louise Amoore is Professor of Geography at Durham University, UK. She researches and teaches in the areas of global geopolitics and security. She has particular interests in how contemporary forms of data, analytics and risk management are changing the techniques of border control and security. Amoore has been awarded a Leverhulme Major Research Fellowship (2016-18) for her work on the ethics of algorithms. Her most recent book is The Politics of Possibility: Risk and Security Beyond Probability (Duke University Press, 2013).
 
Programme
6:30 p.m.             Doors open
7:00 – 7:15 p.m.   Welcome and Introduction
7:15 – 8:00 p.m.   Our Lives with Algorithms, Louise Amoore (Durham University)
8:00 – 9:00 p.m.   Moderated discussion and questions from the audience
9:00 – 10:00 p.m. Get-together
 
The event will be held in English and simultaneously translated into German. For press accreditation, please contact Florian Lüdtke.

This event will be recorded and broadcasted live. By signing up you consent to be photographed, filmed and/or otherwise recorded during the event and to the use of the content in connection with the promotion and public relations of the event.
 
Making Sense of the Digital Society
The current rapid pace of technological change creates enormous uncertainties – and thus the need for explanations that help us better understand our situation and shape the future. The Alexander von Humboldt Institute for Internet and Society (HIIG) and the Federal Agency for Civic Education (bpb)  are therefore continuing the Lecture Series Making Sense of the Digital Society that was launched in 2017. The aim of the format is to develop a European perspective on the current processes of transformation and its societal impact. The first speaker of this year’s series was sociologist Eva Illouz, followed by Dirk Baecker and José van Dijck.

Infos zur Veranstaltung

Adresse

HAU Hebbel am Ufer (HAU 1)
Stresemannstraße 29
10963 Berlin

Contact person

Christiane Matzen, M. A.
Head of Science Communication

Christiane Matzen, M. A.

Leibniz-Institut für Medienforschung | Hans-Bredow-Institut (HBI)
Rothenbaumchaussee 36
20148 Hamburg

Tel. +49 (0)40 45 02 17 41
 

Send Email

MAYBE YOU ARE ALSO INTERESTED IN THESE TOPICS?

Newsletter

Subscribe to our newsletter and receive the Institute's latest news via email.

SUBSCRIBE!