HCDS (Fall 2017)/Day 2 plan: Difference between revisions

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== Overview ==
* Informed consent in the age of Data Science
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* Privacy
* Legalities
** Privacy expectations
* Privacy and ethics
** Inferred values
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** Merged datasets


The key word in data science is "data". As data scientists, we have access to a vast amount of information that relates to the public and private lives of our fellow human beings. As ''human centered'' data scientists, we want to make sure that the work we do with this data respects the people it relates to, adhering to both legal requirements and ethical best practices. That's what we'll be discussing in the second week of Human-Centered Data Science, discussing copyright, federal criminal law and the sociological definition of "creepy".
== Legalities ==
Despite it feeling, a lot of the time, like the internet in general and data science in particular are lawless, there are some (insufficient, outdated) laws that do in fact apply. Most of the time this relates to either copyright - either of what you produce or what you consume - or how your work adheres to the terms of service of a datastore or website it might draw information from.
There are specific areas in which more laws apply (for example, health data, which may or may not fall under the Health Insurance Portability and Accountability Act, or HIPAA) but if you end up wandering into those areas you'll hopefully have a lawyer to tell you all about that. In the meantime, we'll focus on copyright and TOS adherence.
=== Copyright and licensing ===
=== Terms of Service ===
== Privacy and ethics ==
=== Informed consent ===
=== Expectations of privacy ===
=== Harm ===


[[Category:HCDS (Fall 2017)]]
[[Category:HCDS (Fall 2017)]]

Revision as of 05:02, 2 October 2017

  • Informed consent in the age of Data Science
  • Privacy
    • Privacy expectations
    • Inferred values
    • Merged datasets