Informações sobre o curso
4.6
53 classificações
24 avaliações
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Redefinir os prazos de acordo com sua programação.
Nível iniciante

Nível iniciante

Horas para completar

Aprox. 15 horas para completar

Sugerido: 4 weeks, 3-4 hours/week...
Idiomas disponíveis

Inglês

Legendas: Inglês...
100% online

100% online

Comece imediatamente e aprenda em seu próprio cronograma.
Prazos flexíveis

Prazos flexíveis

Redefinir os prazos de acordo com sua programação.
Nível iniciante

Nível iniciante

Horas para completar

Aprox. 15 horas para completar

Sugerido: 4 weeks, 3-4 hours/week...
Idiomas disponíveis

Inglês

Legendas: Inglês...

Programa - O que você aprenderá com este curso

Semana
1
Horas para completar
1 hora para concluir

What are Ethics?

Module 1 of this course establishes a basic foundation in the notion of simple utilitarian ethics we use for this course. The lecture material and the quiz questions are designed to get most people to come to an agreement about right and wrong, using the utilitarian framework taught here. If you bring your own moral sense to bear, or think hard about possible counter-arguments, it is likely that you can arrive at a different conclusion. But that discussion is not what this course is about. So resist that temptation, so that we can jointly lay a common foundation for the rest of this course....
Reading
4 vídeos (Total de 21 min), 4 leituras, 1 teste
Video4 videos
What are Ethics?9min
Data Science Needs Ethics3min
Case Study: Spam (not the meat)4min
Reading4 leituras
Course Syllabus10min
Welcome Announcement10min
Help us learn more about you!10min
What are Ethics? - Introduction10min
Quiz1 exercício prático
Module 1 Quiz20min
Horas para completar
1 hora para concluir

History, Concept of Informed Consent

Early experiments on human subjects were by scientists intent on advancing medicine, to the benefit of all humanity, disregard for welfare of individual human subjects. Often these were performed by white scientists, on black subject. In this module we will talk about the laws that govern the Principle of Informed Consent. We will also discuss why informed consent doesn’t work well for retrospective studies, or for the customers of electronic businesses....
Reading
4 vídeos (Total de 33 min), 1 teste
Video4 videos
Human Subjects Research and Informed Consent: Part 28min
Limitations of Informed Consent9min
Case Study: It's Not OKCupid6min
Quiz1 exercício prático
Module 2 Quiz20min
Horas para completar
1 hora para concluir

Data Ownership

Who owns data about you? We'll explore that question in this module. A few examples of personal data include copyrights for biographies; ownership of photos posted online, Yelp, Trip Advisor, public data capture, and data sale. We'll also explore the limits on recording and use of data. ...
Reading
5 vídeos (Total de 28 min), 1 teste
Video5 videos
Limits on Recording and Use7min
Data Ownership Finale3min
Case Study: Rate My Professor3min
Case Study: Privacy After Bankruptcy2min
Quiz1 exercício prático
Module 3 Quiz20min
Semana
2
Horas para completar
2 horas para concluir

Privacy

Privacy is a basic human need. Privacy means the ability to control information about yourself, not necessarily the ability to hide things. We have seen the rise different value systems with regards to privacy. Kids today are more likely to share personal information on social media, for example. So while values are changing, this doesn’t remove the fundamental need to be able to control personal information. In this module we'll examine the relationship between the services we are provided and the data we provide in exchange: for example, the location for a cell phone. We'll also compare and contrast "data" against "metadata"....
Reading
7 vídeos (Total de 53 min), 2 leituras, 1 teste
Video7 videos
History of Privacy15min
Degrees of Privacy10min
Modern Privacy Risks12min
Case Study: Targeted Ads3min
Case Study: The Naked Mile2min
Case Study: Sneaky Mobile Apps5min
Reading2 leituras
Privacy - Introduction10min
Module 4 Discussion Prompt References10min
Quiz1 exercício prático
Module 4 Quiz20min
Horas para completar
1 hora para concluir

Anonymity

Certain transactions can be performed anonymously. But many cannot, including where there is physical delivery of product. Two examples related to anonymous transactions we'll look at are "block chains" and "bitcoin". We'll also look at some of the drawbacks that come with anonymity....
Reading
4 vídeos (Total de 26 min), 1 teste
Video4 videos
De-identification Has Limited Value: Part 17min
De-identification Has Limited Value: Part 210min
Case Study: Credit Card Statements2min
Quiz1 exercício prático
Module 5 Quiz20min
Semana
3
Horas para completar
2 horas para concluir

Data Validity

Data validity is not a new concern. All too often, we see the inappropriate use of Data Science methods leading to erroneous conclusions. This module points out common errors, in language suited for a student with limited exposure to statistics. We'll focus on the notion of representative sample: opinionated customers, for example, are not necessarily representative of all customers....
Reading
10 vídeos (Total de 60 min), 1 leitura, 1 teste
Video10 videos
Choice of Attributes and Measures6min
Errors in Data Processing8min
Errors in Model Design8min
Managing Change5min
Case Study: Three Blind Mice4min
Case Study: Algorithms and Race3min
Case Study: Algorithms in the Office3min
Case Study: GermanWings Crash5min
Case Study: Google Flu5min
Reading1 leituras
Data Validity - Introduction10min
Quiz1 exercício prático
Module 6 Quiz20min
Horas para completar
1 hora para concluir

Algorithmic Fairness

What could be fairer than a data-driven analysis? Surely the dumb computer cannot harbor prejudice or stereotypes. While indeed the analysis technique may be completely neutral, given the assumptions, the model, the training data, and so forth, all of these boundary conditions are set by humans, who may reflect their biases in the analysis result, possibly without even intending to do so. Only recently have people begun to think about how algorithmic decisions can be unfair. Consider this article, published in the New York Times. This module discusses this cutting edge issue....
Reading
6 vídeos (Total de 50 min), 1 leitura, 1 teste
Video6 videos
Correct But Misleading Results12min
P Hacking10min
Case Study: High Throughput Biology3min
Case Study: Geopricing2min
Case Study: Your Safety Is My Lost Income10min
Reading1 leituras
Algorithmic Fairness - Introduction10min
Quiz1 exercício prático
Module 7 Quiz20min
Semana
4
Horas para completar
1 hora para concluir

Societal Consequences

In Module 8, we consider societal consequences of Data Science that we should be concerned about even if there are no issues with fairness, validity, anonymity, privacy, ownership or human subjects research. These “systemic” concerns are often the hardest to address, yet just as important as other issues discussed before. For example, we consider ossification, or the tendency of algorithmic methods to learn and codify the current state of the world and thereby make it harder to change. Information asymmetry has long been exploited for the advantage of some, to the disadvantage of others. Information technology makes spread of information easier, and hence generally decreases asymmetry. However, Big Data sets and sophisticated analyses increase asymmetry in favor of those with ability to acquire/access. ...
Reading
5 vídeos (Total de 46 min), 1 leitura, 1 teste
Video5 videos
Ossification7min
Surveillance4min
Case Study: Social Credit Scores7min
Case Study: Predictive Policing8min
Reading1 leituras
Societal Consequences - Introduction10min
Quiz1 exercício prático
Module 8 Quiz20min
Horas para completar
3 horas para concluir

Code of Ethics

Finally, in Module 9, we tie all the issues we have considered together into a simple, two-point code of ethics for the practitioner....
Reading
3 vídeos (Total de 16 min), 1 leitura, 2 testes
Video3 videos
Wrap Up2min
Case Study: Algorithms and Facial Recognition4min
Reading1 leituras
Post-Course Survey10min
Quiz1 exercício prático
Module 9 Quiz10min
Horas para completar
1 hora para concluir

Attributions

This module contains lists of attributions for the external audio-visual resources used throughout the course....
Reading
4 leituras
Reading4 leituras
Week 1 Attributions10min
Week 2 Attributions10min
Week 3 Attributions10min
Week 4 Attributions10min
4.6
24 avaliaçõesChevron Right

Melhores avaliações

por JMJul 1st 2018

This course is short, slow, and easy, but I ranked it five stars because the content is important in today's growing reliance on data science.

por SMMay 15th 2018

Excellent Course. Gives interesting and detailed perspectives on ethical matters related to how data can be used and should be used.

Instrutores

Avatar

H.V. Jagadish

Bernard A Galler Collegiate Professor
Electrical Engineering and Computer Science

Sobre University of Michigan

The mission of the University of Michigan is to serve the people of Michigan and the world through preeminence in creating, communicating, preserving and applying knowledge, art, and academic values, and in developing leaders and citizens who will challenge the present and enrich the future....

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