With the increasing use of AI in high-stakes domains such as medicine, law, and defense, organizations spend a lot of time and money to make ML models trustworthy. Many books on the subject offer deep dives into theories and concepts. This guide provides a practical starting point to help development teams produce models that are secure, more robust, less biased, and more explainable. Authors Yada Pruksachatkun, Matthew McAteer, and Subhabrata Majumdar translate best practices in the academic literature for (...) curating datasets and building models into a blueprint for building industry-grade trusted ML systems. With this book, engineers and data scientists will gain a much-needed foundation for releasing trustworthy ML applications into a noisy, messy, and often hostile world. (shrink)

A Scientific Integrity Consortium developed a set of recommended principles and best practices that can be used broadly across scientific disciplines as a mechanism for consensus on scientific integrity standards and to better equip scientists to operate in a rapidly changing research environment. The two principles that represent the umbrella under which scientific processes should operate are as follows: Foster a culture of integrity in the scientific process. Evidence-based policy interests may have legitimate roles to play in influencing aspects of (...) the research process, but those roles should not interfere with scientific integrity. The nine best practices for instilling scientific integrity in the implementation of these two overarching principles are Require universal training in robust scientific methods, in the use of appropriate experimental design and statistics, and in responsible research practices for scientists at all levels, with the training content regularly updated and presented by qualified scientists. Strengthen scientific integrity oversight and processes throughout the research continuum with a focus on training in ethics and conduct. Encourage reproducibility of research through transparency. Strive to establish open science as the standard operating procedure throughout the scientific enterprise. Develop and implement educational tools to teach communication skills that uphold scientific integrity. Strive to identify ways to further strengthen the peer review process. Encourage scientific journals to publish unanticipated findings that meet standards of quality and scientific integrity. Seek harmonization and implementation among journals of rapid, consistent, and transparent processes for correction and/or retraction of published papers. Design rigorous and comprehensive evaluation criteria that recognize and reward the highest standards of integrity in scientific research. (shrink)

İslam hukuk doktrininde bir fiilin veya sözün hükmünü belirleme noktasında kasıt esas alınır. Kasıt; hukuki işlemlerden elde edilmek istenen neticedir. Bununla birlikte mükellefin söz veya fiillerinin kasıt sonucu meydana gelmesi halinde söz ve fiillerine hüküm bağlanır. Bu takdirde bir akdin esasını onunla elde edilmek istenen hukuki neticeye yöneltilmiş olan tarafların kastı teşkil eder. İslam dini mükelleflerden bir davranışı ortaya koyduğu zaman bunun bilinçli olarak yapılmasını ve o işe kalben yönelmesini istemiştir. Dini emir ve yasakların tamamı bir maksadı gerçekleştirmek için vazedilmiştir. (...) Şari’in emir ve yasaklardaki maksadı da ya kulların maslahatını temin etmek yada onlardan bir mefsedeti gidermektir. Mükelleften istenen de bu maksat doğrultusunda hareket etmesi ve Şari’in maksadından başka bir şeyi kastetmemesidir. Hukuki tasarrufların geçerli olması noktasında bütün mezheplerin kasta önem verdikleri görülmektedir. (shrink)