Requirements

• Python 3.6+

Installation

Install responsibly with pip:

$ pip install responsibly

or directly from the source code:

$ git clone https://github.com/ResponsiblyAI/responsibly.git
$ cd responsibly
$ python setup.py install

Citation

If you have used Responsibly in a scientific publication, we would appreciate citations to the following:

@Misc{,
  author = {Shlomi Hod},
  title =  {{Responsibly}: Toolkit for Auditing and Mitigating Bias and Fairness of Machine Learning Systems},
  year =   {2018--},
  url =    "http://docs.responsibly.ai/",
  note =   {[Online; accessed <today>]}
}

0.1.3 (2021/04/02)

• Fix new pagacke dependencies

• Switch from Travis CI to Github Actions

0.1.2 (2020/09/15)

• Fix Travis CI issues with pipenv

• Fix bugs with word embedding bias

0.1.1 (2019/08/04)

• Fix a dependencies issue with smart_open

• Change URLs to https

0.1.0 (2019/07/31)

• Rename the project to responsibly from ethically

• Word embedding bias

  • Improve functionality of BiasWordEmbedding

• Threshold fairness interventions

  • Fix bugs with ROCs handling

  • Improve API and add functionality (plot_thresholds)

0.0.5 (2019/06/14)

• Word embedding bias

  • Fix bug in computing WEAT

  • Computing and plotting factual property association to projections on a bias direction, similar to WEFAT

0.0.4 (2019/06/03)

• Word embedding bias

  • Unrestricted most_similar

  • Unrestricted generate_analogies

  • Running specific experiments with calc_all_weat

  • Plotting clustering by classification of biased neutral words

0.0.3 (2019/04/10)

• Fairness in Classification

  • Three demographic fairness criteria

    • Independence

    • Separation

    • Sufficiency

  • Equalized odds post-processing algorithmic interventions

  • Complete two notebook demos (FICO and COMPAS)

• Word embedding bias

  • Measuring bias with WEAT method

• Documentation improvements

• Fixing security issues with dependencies

0.0.2 (2018/09/01)

• Word embedding bias

  • Generating analogies along the bias direction

  • Standard evaluations of word embedding (word pairs and analogies)

  • Plotting indirect bias

  • Scatter plot of bias direction projections between two word embedding

  • Improved verbose mode

0.0.1 (2018/08/17)

• Gender debiasing for word embedding based on Bolukbasi et al.