Trustworthy AI

Modern AI systems have become of widespread use in almost all sectors with a strong impact on our society. However, the very methods on which they rely, based on Machine Learning techniques for processing data to predict outcomes and to make decisions, are opaque, prone to bias and may produce wrong answers. Objective functions optimized in learning systems are not guaranteed to align with the values that motivated their definition. Properties such as transparency, verifiability, explainability, security, technical robustness and safety, are key to build operational governance frameworks, so that to make AI systems justifiably trustworthy and to align their development and use with human rights and values.

  • Published in:
    Reflections on Artificial Intelligence for Humanity
  • Type:
    Inbook
  • Authors:
    R. Chatila, V. Dignum, M. Fisher, F. Giannotti, K. Morik, S. Russell, K. Yeung
  • Year:
    2021

Citation information

R. Chatila, V. Dignum, M. Fisher, F. Giannotti, K. Morik, S. Russell, K. Yeung: Trustworthy AI, Reflections on Artificial Intelligence for Humanity, 2021, 18-45, https://doi.org/10.1007/978-3-030-69128-8, Chatila.etal.2021,