[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.

Why?
I think James said it better:

Here are a few resources and reads from the forums:

Documents:

Blog Posts:

Videos:

People to follow:

Courses:

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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.

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@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

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@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.

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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.
https://www.thetalkingmachines.com/episodes/slowed-down-conferences-and-even-more-summer-schools?context_entity_type=node&context_entity_id=27532

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.
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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?

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Yes it is.

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