INDUSTRIAL PROPERTY STATUS:

Spanish Patent Application (P201831278), expandable to international protection, 100% Autonoma University of Madrid (UAM).

TYPE OF COLLABORATION BEING SHOUGHT:

  • Licensing agreement.
  • R&D development agreement.

For further information we recommend:

Scientific publications:

  • A. Morales, J. Fierrez, R. Vera-Rodriguez. SensitiveNets: Learning Agnostic Representations with Application to Face Recognition. arXiv:1902.00334, 2019. [pdf][GitHub]
  • A. Acien, A. Morales, R. Vera-Rodriguez, I. Bartolome, J. Fierrez. Measuring the Gender and Ethnicity Bias in Deep Models for Face Recognition. Proc. of IAPR Iberoamerican Congress on Pattern Recognition, Madrid, Spain, 2018. [pdf]
  • B. Goodman and F. Flaxman. European Union regulations on algorithmic decision-making and a “right to explanation”. AI Magazine, 38(3), 2016.
  • R. Zemel, Y. Wu, K. Swersky, T. Pitassi, C. Dwork. Learning Fair Representations. In Proc. of the Int. Conf. on Machine Learning, Atlanta, USA, pp. 325-333, 2013.
  • J. Buolamwini and T. Gebru. Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification. In Proc. of the ACM Conf. on Fairness, Accountability, and Transparency, New York, USA, 81:1-15, 2018.
  • M. Alvi, A. Zisserman, C. Nellaker. Turning a Blind Eye: Explicit Removal of Biases and Variation from Deep Neural Network Embeddings. In Proc. of European Conf. on Computer Vision, Munich, Germany, 2018.

Fighting Bias:

How I’m fighting bias in algorithms | Joy Buolamwini (MIT MediaLab)

Recommended book:

Weapons of Math Destruction, Cathy O’Neil

How Big Data Increases Inequality and Theatens Democracy