About the non-technical aspects of AI and ML

09 Aug 2019 (regularly updated)

I believe that while working on AI projects, one should also be aware of the non-technical aspects of AI. While everything is digital and out of sight, AI actually has a profound impact on the environment and society. The ethical challenges of self-driving car accidents and the alarming energy consumption of deep learning algorithms are some examples. It is crucial to stay up to date with these challenges in order to have a holistic view of the consequences of AI research.

In this post, I suggest some very interesting references revolving around the impact of AI. Naturally, like all opinion pieces, some of them should be read with hindsight and a critical mind.

Table of Contents:

Some resources on AI

Some newsletters:

Some interesting reports on AI

About the environment

Also see Climate Change AI (CCAI), a group of volunteers from academia and industry who believe that tackling climate change requires concerted societal action, in which machine learning can play an impactful role.

About ethics and social impact

About bias and fake news

About privacy

About the data scientist job