基于区块链的毕业设计Data Ethics Club – 数据伦理俱乐部

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Data Ethics Club

Data Ethics Club - 数据伦理俱乐部

💻 🧠 📊

Welcome! Data Ethics Club is a discussion group/”journal” club about doing data science ethically. “Journal” because we will also read blog posts, (parts of) books, or watch videos. The organisers are based in Bristol, but the club is open to all.

We’re in the planning stage right now 🐛, so for now:

  • enjoy our reading list.
  • suggest reading materials.
  • get involved in organising.
  • stay in the loop to hear about our first events.

Stay in the loop

When the club emerges from it’s chrysalis 🐛 -> 🦋, we’ll advertise events through the Jean Golding Institute mailing list, we’ll advertise the dates right here, and I’ll tweet about it at #DataEthicsClub.

Get Involved

If you’re interested in joining us in organising, please email us or ping us a message on our favourite data science Discord- you don’t need to be in Bristol.

Organisers

You can also contact us separately:

  • Nina Di Cara – twitter, email
  • Natalie Thurlby – twitter, email

How to make suggestions

If you’d like to make a suggestion for what to read, please do whatever you’d prefer:

  • make an issue – use the reading suggestion(s) template.
  • email us
  • edit this readme and make a pull request

Reading list

Suggetions for reading:

  • Google’s AI principles
  • Ethical principles in machine learning and artificial intelligence: cases from the field and possible ways forward
  • The Tyranny of Structurelessness
  • Design Justice: Towards an Intersectional Feminist Framework for Design Theory and Practice
  • A toolkit for centering racial equity throughout data integration1
  • Measuring the predictability of life outcomes with a scientific mass collaboration – #3
  • Hacking the cis-tem
  • A feature not a bug
  • What is Data Ethics?
  • Algorithmic Injustices: Towards a relational ethics
  • The Financial Modelers Manifesto – #2
  • The Missing Datasets Project – #1
  • Social Biases in NLP Models as Barriers for Persons with Disabilities
  • Collectors, Allies, and Nightlights, Oh My
  • Why Open Source misses the point of Free Software
  • Which programming languages use the least electricity?
  • Machine decisions and human consequences
  • Privacy is power
  • Bropenscience is Broken Science
  • Paths to Social License for Tracking-data Analytics
  • Ethics can’t be a side hustle
  • A manifesto for team science
  • Algorithms designed to fight poverty can actually make it worse
  • Algorithms Of Opression1
    • Suggested excerpt: Social Inequality Will Not Be Solved By An App
  • Reflections on trusting trust
  • Why data is never raw
  • Ethical data science1

Suggestions for viewing/listening/experiencing

  • Critical perspectives on computer vision
  • Data Feminism Book Club1
    • Chapter 7: “Show your work”
    • The description of “co-liberatory” projects in chapter 5: “Unicorns, janitors, ninjas, wizards and rock stars”
  • AI, Ain’t I a Woman? – poem2
  • How normal am I? – interactive

  • [1]: A longer piece of work, we’d need to choose a chapter or section.
  • [2]: A shorter piece of work, perhaps to combine with something else

Contributors

Thanks goes to these wonderful people (emoji key):

Data Ethics Club - 数据伦理俱乐部
NatalieThurlby
📋 🤔
Data Ethics Club - 数据伦理俱乐部
Nina
📋 🤔

This project follows the all-contributors specification. Contributions of any kind welcome!

We use optional third-party analytics cookies to understand how you use GitHub.com so we can build better products. Learn more.


Data Ethics Club

Data Ethics Club - 数据伦理俱乐部

💻 🧠 📊

Welcome! Data Ethics Club is a discussion group/”journal” club about doing data science ethically. “Journal” because we will also read blog posts, (parts of) books, or watch videos. The organisers are based in Bristol, but the club is open to all.

We’re in the planning stage right now 🐛, so for now:

  • enjoy our reading list.
  • suggest reading materials.
  • get involved in organising.
  • stay in the loop to hear about our first events.

Stay in the loop

When the club emerges from it’s chrysalis 🐛 -> 🦋, we’ll advertise events through the Jean Golding Institute mailing list, we’ll advertise the dates right here, and I’ll tweet about it at #DataEthicsClub.

Get Involved

If you’re interested in joining us in organising, please email us or ping us a message on our favourite data science Discord- you don’t need to be in Bristol.

Organisers

You can also contact us separately:

  • Nina Di Cara – twitter, email
  • Natalie Thurlby – twitter, email

How to make suggestions

If you’d like to make a suggestion for what to read, please do whatever you’d prefer:

  • make an issue – use the reading suggestion(s) template.
  • email us
  • edit this readme and make a pull request

Reading list

Suggetions for reading:

  • Google’s AI principles
  • Ethical principles in machine learning and artificial intelligence: cases from the field and possible ways forward
  • The Tyranny of Structurelessness
  • Design Justice: Towards an Intersectional Feminist Framework for Design Theory and Practice
  • A toolkit for centering racial equity throughout data integration1
  • Measuring the predictability of life outcomes with a scientific mass collaboration – #3
  • Hacking the cis-tem
  • A feature not a bug
  • What is Data Ethics?
  • Algorithmic Injustices: Towards a relational ethics
  • The Financial Modelers Manifesto – #2
  • The Missing Datasets Project – #1
  • Social Biases in NLP Models as Barriers for Persons with Disabilities
  • Collectors, Allies, and Nightlights, Oh My
  • Why Open Source misses the point of Free Software
  • Which programming languages use the least electricity?
  • Machine decisions and human consequences
  • Privacy is power
  • Bropenscience is Broken Science
  • Paths to Social License for Tracking-data Analytics
  • Ethics can’t be a side hustle
  • A manifesto for team science
  • Algorithms designed to fight poverty can actually make it worse
  • Algorithms Of Opression1
    • Suggested excerpt: Social Inequality Will Not Be Solved By An App
  • Reflections on trusting trust
  • Why data is never raw
  • Ethical data science1

Suggestions for viewing/listening/experiencing

  • Critical perspectives on computer vision
  • Data Feminism Book Club1
    • Chapter 7: “Show your work”
    • The description of “co-liberatory” projects in chapter 5: “Unicorns, janitors, ninjas, wizards and rock stars”
  • AI, Ain’t I a Woman? – poem2
  • How normal am I? – interactive

  • [1]: A longer piece of work, we’d need to choose a chapter or section.
  • [2]: A shorter piece of work, perhaps to combine with something else

Contributors

Thanks goes to these wonderful people (emoji key):

Data Ethics Club - 数据伦理俱乐部
NatalieThurlby
📋 🤔
Data Ethics Club - 数据伦理俱乐部
Nina
📋 🤔

This project follows the all-contributors specification. Contributions of any kind welcome!

We use optional third-party analytics cookies to understand how you use GitHub.com so we can build better products. Learn more.

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