Ethics & Governance of Artificial Intelligence (EGAI)

5 Intellectual Debt 5 Intellectual Debt

5.1. “The Hidden Costs of Automated Thinking” by Jonathan Zittrain (The New Yorker, 2019)

“The Hidden Costs of Automated Thinking” by Jonathan Zittrain (The New Yorker, 2019)

5.2. “Artificial Intelligence’s ‘Black Box’ Is Nothing to Fear” by Vijay Pande (The New York Times, 2018)

“Artificial Intelligence’s ‘Black Box’ Is Nothing to Fear” by Vijay Pande (The New York Times, 2018)

5.3. “Hidden Technical Debt in Machine Learning Systems” by D. Sculley et al., (NIPS, 2015)

“Hidden Technical Debt in Machine Learning Systems” by D. Sculley et al., (NIPS, 2015)

5.4. “Stop Explaining Black Box Machine Learning Models for High Stakes Decisions and Use Interpretable Models Instead” by Cynthia Rudin (Nature, 2019) - Read until “Algorithmic Challenges in interpretable ML” on page 211 + Conclusion.

Read until “Algorithmic Challenges in interpretable ML” on page 211, as well as Conclusion.

“Stop Explaining Black Box Machine Learning Models for High Stakes Decisions and Use Interpretable Models Instead” by Cynthia Rudin (Nature, 2019) - Read until “Algorithmic Challenges in interpretable ML” on page 211 + Conclusion.

5.5. "Please Stop Doing 'Explainable' ML" by Cynthia Rudin (VIDEO)

"Please Stop Doing 'Explainable' ML" by Cynthia Rudin (VIDEO)

5.6. “Law and Adversarial Machine Learning” by Ram Shankar Siva Kumar et al. (ArXiv, 2018)

“Law and Adversarial Machine Learning” by Ram Shankar Siva Kumar et al. (ArXiv, 2018)