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Multidisciplinary Thinking

We believe that the best way to understand ethical challenges in relation to technology is by combining the expertise of multiple disciplines.

Technological changes are influencing and being influenced by diverse areas and perspectives, and in this section, you will find a selection of resources from disciplines, such as economics, engineering, philosophy, law, design, and others related to technology and its applications to society.

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Lex Fridman Podcast

by Lex Fridman

Conversations about the nature of intelligence, consciousness, love, and power.

Lex Fridman is an AI researcher working on autonomous vehicles, human-robot interaction, and machine learning at MIT and beyond. This podcast is 


Introduction to Value Sensitive Design

by Delft University of Technology

This course covers briefly how Value Sensitive Design arose as a concept. When computers first came into use in the 50s and 60s, their technical features were of most interest. However, as they became more embedded in some of the largest organizations, many realised that the social and behavioural changes that computing was also significant..


Improve the News

by Improve the News Foundation

Improve the News is a free AI-powered news aggregator with sliders that puts you in charge, making it easy to find underreported topics and perspectives

This is a news aggregator site developed by a group of researchers at MIT and elsewhere to give you control of your news consumption.


Philosophy of Technology

By University of Twente

In every aspect of our lives we make use of all kinds of technologies. Technologies can anticipate needs or solve problems, and they can extend or enhance human capacities and activities. Technologies have made life easier, but also complicated our world.

In this course you will get acquainted with some key approaches in philosophy of technology and design.


A Right to Reasonable Inferences:

Data Protection Law in the Age of Big Data and AI

by Sandra Watcher and  Brent Mittelstadt

Big Data analytics and artificial intelligence (AI) draw non-intuitive and unverifiable inferences and predictions about the behaviors, preferences, and private lives of individuals. These inferences draw on highly diverse and feature-rich data of unpredictable value, and create new opportunities for discriminatory, biased, and invasive decision-making.


Humans in the Loop

by Towards Data Science

Human beings are collaborating with artificial intelligences on an increasing number of high-stakes tasks. Every day, social media apps recommend content to us that quite literally shapes our worldviews and our cultures.

However very few of us even have a basic idea of how these all-important recommendations are generated

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