Merge branch 'master' of https://github.com/jphall663/GWU_rml

README.md

@@ -20,10 +20,12 @@ Corrections or suggestions? Please file a [GitHub issue](https://github.com/jpha
 
 ### Lecture 1 Class Materials
 
-* [Syllabus](rml_syllabus_summer_2020.pdf)
+* [Syllabus](https://github.com/jphall663/GWU_rml/blob/master/Syllabus%20-%20PH%20-%20Responsible%20Machine%20Learning%20-%20MSBA%20-%20v3.pdf)
 * [Lecture Notes](tex/lecture_1.pdf)
 * Lecture Video - please email instructor: [email protected].
-* Software Example: [Building from Penalized GLM to Monotonic GBM](https://nbviewer.jupyter.org/github/jphall663/GWU_rml/blob/master/lecture_1.ipynb)
+* Software Example:
+  * [Building from Penalized GLM to Monotonic GBM](https://nbviewer.jupyter.org/github/jphall663/GWU_rml/blob/master/lecture_1.ipynb)
+  * [Simple Explainable Boosting Machine Example](https://nbviewer.jupyter.org/github/jphall663/GWU_rml/blob/master/lecture_1_ebm_example.ipynb)
 
 ### Lecture 1 Suggested Software
 
@@ -46,10 +48,8 @@ Corrections or suggestions? Please file a [GitHub issue](https://github.com/jpha
   * [*This Looks Like That: Deep Learning for Interpretable Image Recognition*](https://arxiv.org/pdf/1806.10574.pdf)
 
 * **Links from Lecture 1**:
-  * [Tay (bot)](https://en.wikipedia.org/wiki/Tay_(bot))
-  * [New York Regulator Probes UnitedHealth Algorithm for Racial Bias](https://www.wsj.com/articles/new-york-regulator-probes-unitedhealth-algorithm-for-racial-bias-11572087601)
-  * [When a Computer Program Keeps You in Jail](https://www.nytimes.com/2017/06/13/opinion/how-computers-are-harming-criminal-justice.html)
-  * [When an Algorithm Helps Send You to Prison](https://www.nytimes.com/2017/10/26/opinion/algorithm-compas-sentencing-bias.html)
+  * [EU AI Regulation Proposal](https://digital-strategy.ec.europa.eu/en/library/proposal-regulation-laying-down-harmonised-rules-artificial-intelligence)
+  * [FTC Guidance (2021)](https://www.ftc.gov/news-events/blogs/business-blog/2021/04/aiming-truth-fairness-equity-your-companys-use-ai)
 
 ***
 
@@ -87,13 +87,7 @@ Corrections or suggestions? Please file a [GitHub issue](https://github.com/jpha
   * [*Towards Better Understanding of Gradient-based Attribution Methods for Deep Neural Networks*](https://arxiv.org/pdf/1711.06104.pdf)
 
 * **Links from Lecture 2**:
-  * [On the Art and Science of Explainable Machine Learning](https://arxiv.org/pdf/1810.02909.pdf)
-  * [Access Denied: Faulty Automated Background Checks Freeze Out Renters](https://themarkup.org/locked-out/2020/05/28/access-denied-faulty-automated-background-checks-freeze-out-renters)
-  * [ML Attack Cheatsheet](https://github.com/jphall663/secure_ML_ideas/blob/master/img/cheatsheet.png)
-  * [Debugging Machine Learning Via Model Assertions](https://cs.stanford.edu/~matei/papers/2019/debugml_model_assertions.pdf)
-  * [Machine Bias](https://www.propublica.org/article/machine-bias-risk-assessments-in-criminal-sentencing)
-  * [Gender Shades](http://gendershades.org/)
-  * [Explainable Neural Networks based on Additive Index Models](https://arxiv.org/pdf/1806.01933.pdf)
+
 
 ***
 
@@ -172,8 +166,6 @@ Python:
   * [*Hacking Smart Machines with Smarter Ones: How to Extract Meaningful Data from Machine Learning Classifiers*](https://arxiv.org/pdf/1306.4447.pdf)
 
 * **Links from Lecture 4**:
-  * [*A Plea for Simplicity*](https://www.schneier.com/essays/archives/1999/11/a_plea_for_simplicit.html)
-  * [*Privacy Risks of Explaining Machine Learning Models*](https://arxiv.org/pdf/1907.00164.pdf)
 
 ***   
 
@@ -206,18 +198,6 @@ Python:
 
 * **Links from Lecture 5**:
 
-  * [Testing and Debugging in Machine Learning (Google)](https://developers.google.com/machine-learning/testing-debugging)
-  * AI Incidents (not already linked above):
-    * [Self-Driving Uber Car Kills Pedestrian in Arizona, Where Robots Roam](https://www.nytimes.com/2018/03/19/technology/uber-driverless-fatality.html)
-    * [The Woz tweets on Apple and Goldman Sachs](https://twitter.com/stevewoz/status/1193424787248279552)
-    * [Suckers List: How Allstate’s Secret Auto Insurance Algorithm Squeezes Big Spenders](https://themarkup.org/allstates-algorithm/2020/02/25/car-insurance-suckers-list)
-    * [A.C.L.U. Accuses Clearview AI of Privacy ‘Nightmare Scenario’](https://www.nytimes.com/2020/05/28/technology/clearview-ai-privacy-lawsuit.html)
-    * [Government’s Use of Algorithm Serves Up False Fraud Charges](https://undark.org/2020/06/01/michigan-unemployment-fraud-algorithm/)
-    * [Microsoft's robot editor confuses mixed-race Little Mix singers](https://www.theguardian.com/technology/2020/jun/09/microsofts-robot-journalist-confused-by-mixed-race-little-mix-singers)
-    * [Welfare surveillance system violates human rights, Dutch court rules](https://www.theguardian.com/technology/2020/feb/05/welfare-surveillance-system-violates-human-rights-dutch-court-rules)
-  * [*Intelligible Models for HealthCare: Predicting Pneumonia Risk and Hospital 30-day Readmission*](http://people.dbmi.columbia.edu/noemie/papers/15kdd.pdf)
-  ![Excerpt from *Intelligible Models for HealthCare: Predicting Pneumonia Risk and Hospital 30-day Readmission*](img/asthama_pneumonia.png)
-
 ***   
 
 ## Lecture 6: Responsible Machine Learning Best Practices 
@@ -245,12 +225,6 @@ Python:
 
 * **Links from Lecture 6**:
 
-  * [Example Model Card](https://modelcards.withgoogle.com/object-detection)
-  * [Network Graph Example](https://github.com/jphall663/corr_graph)
-  * Autoencoder Visualizations:
-    * [*Reducing the Dimensionality of Data with Neural Networks*](https://www.cs.toronto.edu/~hinton/science.pdf)
-    * [DNSC 6279 Autoencoder Example](https://nbviewer.jupyter.org/github/jphall663/GWU_data_mining/blob/master/05_neural_networks/src/py_part_5_MNIST_autoencoder.ipynb)
-
 
 ***