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, R. Tolosana. SensitiveNets: Learning Agnostic Representations with Application to Face Images. IEEE Transactions on Pattern Analysis and Machine intelligence, 2020. [pdf][GitHub]
  • I. Serna, A. Morales, J. Fierrez, M. Cebrian, N. Obradovich and I. Rahwan. Algorithmic Discrimination: Formulation and Exploration in Deep Learning-based Face Biometrics. Proc. of AAAI Workshop on Artificial Intelligence Safety (SafeAI), New York, NY, USA, February 2020. [pdf]
  • R. Vera-Rodriguez, M. Blazquez, A. Morales, E. Gonzalez-Sosa, J. Neves and H. Proenca. FaceGenderID: Exploiting Gender Information in DCNNs Face Recognition Systems. Proc. IEEE/CVF Conference on Computer Vision and Pattern Recognition, Workshop on Bias Estimation in Face Analytics (CVPR BEFA), June 2019 (Best Paper Runner Up Award). [pdf]
  • 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. 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. 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