[Wiki] AI/ML Ethics, Biases, & Responsibility (2019)

Note: This is a wiki, please feel free to edit/add resources here.

Following the discussion here I felt @jamesrequa is right that the topic really deserves a separate thread.

I think James said it better:

Here are a few resources and reads from the forums:


Blog Posts:


People to follow:



Admins: Please wiki-fy this, I’m really sure others would have a lot more resources to add here.

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I am sure that @rachel would love to see this.

Thanks for putting this together @init_27 I’ve made the post into a wiki.


@rachel Thanks! I’ve created a list on twitter from your suggestions in the blogpost. Since the blogpost is a few months old, do you have any more suggestions of whom to follow?

This twitter thread lists quite a lot of relevant resources: https://twitter.com/iamtrask/status/1101894655631912960
like books: https://twitter.com/BecomingDataSci/status/1102296037782368256


@miwojc Please feel free to add these to the wiki (it can be edited by anyone).

I added a link to a multisociety statement on the ethics of AI in Radiology. The public comment period remains open until mid-April, if anyone would like to contribute.


Cross-posting ETHICS papers listing from the other thread:

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In the second part of this episode of talking machines they chat with Adrian Weller of the Alan Turing Institute about ethics.

Just added the link to the new guidelines from the EU commission. From the introduction:

The aim of the Guidelines is to promote Trustworthy AI. Trustworthy AI has three components, which should be met throughout the system’s entire life cycle:

  1. it should be lawful, complying with all applicable laws and regulations
  2. it should be ethical, ensuring adherence to ethical principles and values and
  3. it should be robust, both from a technical and social perspective since, even with good intentions, AI systems can cause unintentional harm.

BerkeleyAI Meetup is hosting and event entitled “Open discussion: Research papers on bias and fairness in AI/ML ” on April 25th, 2019, 6-8pm.

They recommend some pre-meetup reading and have ~10 links to relevant papers.

@init_27 @rachel, I see multiple “AI Ethics” threads across the various course groups, each with different resources/insights. Is there a way to roll all of them up into one? Is the Deep Learning category accessible to all?


Yes it is.

Great. I’ll go ahead and pull everything into that category then. Thanks!