@article{1476050,
      recid = {1476050},
      author = {Duke, Toju.},
      title = {Building responsible AI algorithms : a framework for  transparency, fairness, safety, privacy, and robustness /},
      publisher = {Apress L. P.,},
      address = {Berkeley, CA :},
      pages = {1 online resource (196 p.)},
      year = {2023},
      note = {Use Pretrained Models and Cloud APIs},
      abstract = {This book introduces a Responsible AI framework and guides  you through processes to apply at each stage of the machine  learning (ML) life cycle, from problem definition to  deployment, to reduce and mitigate the risks and harms  found in artificial intelligence (AI) technologies. AI  offers the ability to solve many problems today if  implemented correctly and responsibly. This book helps you  avoid negative impacts that in some cases have caused loss  of life and develop models that are fair, transparent,  safe, secure, and robust. The approach in this book raises  your awareness of the missteps that can lead to negative  outcomes in AI technologies and provides a Responsible AI  framework to deliver responsible and ethical results in ML.  It begins with an examination of the foundational elements  of responsibility, principles, and data. Next comes  guidance on implementation addressing issues such as  fairness, transparency, safety, privacy, and robustness.  The book helps you think responsibly while building AI and  ML models and guides you through practical steps aimed at  delivering responsible ML models, datasets, and products  for your end users and customers. What You Will Learn Build  AI/ML models using Responsible AI frameworks and processes  Document information on your datasets and improve data  quality Measure fairness metrics in ML models Identify  harms and risks per task and run safety evaluations on ML  models Create transparent AI/ML models Develop Responsible  AI principles and organizational guidelines.},
      url = {http://library.usi.edu/record/1476050},
      doi = {https://doi.org/10.1007/978-1-4842-9306-5},
}