🗺️ Exploring subjects

Topics

To find a topic that I found interesting, I first wrote down the different topics that first came to mind like:

• global health

• nutrition

• mental health

• pandemic

• feminism

• gender biases

• cryptocurrencies

• Algorithmic biases

• Toeslagenaffaire

Algorithmic biases

Article on OneWorld

By reading an article I came across on the One World platform I became inspired by the topic and continued to search for more information. Eventually I came to the topic “Algorithmic Biases”. Within this topic you will find a number of sub topics such as gender, culture and ethnical biases. We often do not realize that such systems are already being applied to us because it is often invisible to the eye, but how does it feel to be biased through artificial intelligence and how can we make it visible? At the moment there are already a number of systems in our society where artificial intelligence plays a major role in making choices and risk predictions.

https://www.oneworld.nl/lezen/discriminatie/hoe-nederland-a-i-inzet-voor-etnisch-profileren/?utm_campaign=later-linkinbio-oneworldnl&utm_content=later-13527536&utm_medium=social&utm_source=instagram

A.I. and Machine learning

AI and Machine Learning

https://www.technologyreview.com/2019/02/04/137602/this-is-how-ai-bias-really-happensand-why-its-so-hard-to-fix/

A.I. and Machine Learning are currently merging in our society. The technology has already developed so far that different forms of Machine Learning are already being used in daily life. Artificial intelligence (A.I.) is not free from biases. Not only can the systems learn tasks from people, the systems can also teach themselves prejudices. The systems are developed by various companies that make a major contribution to our society. When artificial intelligence remains biased even when artificial intelligence is not knowingly used to discriminate, the technology can incite discrimination and prosecution.

From here i created a mind map to write down al the topics that have to do with A.I.

What type of algorithmic biases are there?