ผลต่างระหว่างรุ่นของ "Foundations of ethical algorithms"
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** เอกสารอ้างอิง | ** เอกสารอ้างอิง | ||
*** [https://dataprivacylab.org/projects/identifiability/paper1.pdf L. Sweeney, Simple Demographics Often Identify People Uniquely. Carnegie Mellon University, Data Privacy Working Paper 3. Pittsburgh 2000.] | *** [https://dataprivacylab.org/projects/identifiability/paper1.pdf L. Sweeney, Simple Demographics Often Identify People Uniquely. Carnegie Mellon University, Data Privacy Working Paper 3. Pittsburgh 2000.] | ||
| − | *** Netflix Prize. [https://www.cs.cornell.edu/~shmat/shmat_oak08netflix.pdf Arvind Narayanan and Vitaly Shmatikov, How To Break Anonymity of the Netflix Prize Dataset]; [https://www.cs.cornell.edu/~shmat/netflix-faq.html FAQ] | + | *** Netflix Prize. [https://www.cs.cornell.edu/~shmat/shmat_oak08netflix.pdf Arvind Narayanan and Vitaly Shmatikov, How To Break Anonymity of the Netflix Prize Dataset] | [https://www.cs.cornell.edu/~shmat/netflix-faq.html FAQ] |
*** GWAS privacy. [https://pubmed.ncbi.nlm.nih.gov/18769715/ Homer N, Szelinger S, Redman M, et al. Resolving individuals contributing trace amounts of DNA to highly complex mixtures using high-density SNP genotyping microarrays. PLoS Genet. 2008;4(8):e1000167. Published 2008 Aug 29. doi:10.1371/journal.pgen.1000167] | *** GWAS privacy. [https://pubmed.ncbi.nlm.nih.gov/18769715/ Homer N, Szelinger S, Redman M, et al. Resolving individuals contributing trace amounts of DNA to highly complex mixtures using high-density SNP genotyping microarrays. PLoS Genet. 2008;4(8):e1000167. Published 2008 Aug 29. doi:10.1371/journal.pgen.1000167] | ||
*** Word embedding. [https://arxiv.org/abs/1607.06520 Bolukbasi, Chang, Zou, Saligrama, Kalai. Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings.] | *** Word embedding. [https://arxiv.org/abs/1607.06520 Bolukbasi, Chang, Zou, Saligrama, Kalai. Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings.] | ||
| − | *** COMPAS. [https://www.propublica.org/article/machine-bias-risk-assessments-in-criminal-sentencing Machine Bias (ProPublica)] | + | *** COMPAS. [https://www.propublica.org/article/machine-bias-risk-assessments-in-criminal-sentencing Machine Bias (ProPublica)] | [https://www.propublica.org/article/how-we-analyzed-the-compas-recidivism-algorithm How We Analyzed the COMPAS Recidivism Algorithm (ProPublica) by Jeff Larson, Surya Mattu, Lauren Kirchner and Julia Angwin] |
== อ้างอิง == | == อ้างอิง == | ||
รุ่นแก้ไขเมื่อ 03:11, 15 สิงหาคม 2563
หน้านี้สำหรับรายวิชา Foundations of Ethical Algorithms
เนื้อหา
- Week 1: Introduction
- เอกสารอ้างอิง
- L. Sweeney, Simple Demographics Often Identify People Uniquely. Carnegie Mellon University, Data Privacy Working Paper 3. Pittsburgh 2000.
- Netflix Prize. Arvind Narayanan and Vitaly Shmatikov, How To Break Anonymity of the Netflix Prize Dataset | FAQ
- GWAS privacy. Homer N, Szelinger S, Redman M, et al. Resolving individuals contributing trace amounts of DNA to highly complex mixtures using high-density SNP genotyping microarrays. PLoS Genet. 2008;4(8):e1000167. Published 2008 Aug 29. doi:10.1371/journal.pgen.1000167
- Word embedding. Bolukbasi, Chang, Zou, Saligrama, Kalai. Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings.
- COMPAS. Machine Bias (ProPublica) | How We Analyzed the COMPAS Recidivism Algorithm (ProPublica) by Jeff Larson, Surya Mattu, Lauren Kirchner and Julia Angwin
- เอกสารอ้างอิง
อ้างอิง
รายวิชาจะอ้างอิงเนื้อหาจากหลายแหล่ง ดังนี้
- หนังสือ The Algorithmic Foundations of Differential Privacy โดย Cynthia Dwork และ Aaron Roth
- Science of Data Ethics - UPenn สอนโดย Michael Kearns และ Kristian Lum
- Ethics in Data Science - UTah สอนโดย Suresh Venkatasubramanian และ Katie Shelef
- Foundations of Fairness in Machine Learning - UW สอนโดย Jamie Morgenstern
- Explainable AI in Industry: Practical Challenges and Lessons Learned (ACM FAT* 2020 Tutorial)
