Exam (elaborations)
Ethics in data science
- Institution
- PHI 101 Ethics OF DATA SCIENCE
Ethics in data science
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Ethics in data scienceWhat are the limitations of the chosen approach? - correct answer-Built-in
bias, e.g. voice recognition not handling many accents, medical datasets
skewed towards men
What is the recall regarding ethics in DS outputs? - correct
answer-Conclusions and automated systems can be used for good or ill,
professionals have responsibility for uses made of their work
What is an example of unethical behavior in DS? - correct answer-Volkswagen
detecting air-quality tests and switching to lower-polluting mechanisms only
during the test
What is the importance of professional ethics? - correct answer-Defines
expected behavior, required for membership in professional associations
Who are the stakeholders in data science? - correct
answer-Clients/employers, subjects described by data, workers whose jobs
might be displaced, end-users whose environment might be shaped
What are the principles of computing professional ethics? - correct
answer-Contribute to society, avoid harm, be fair, respect privacy, respect
others' work, work within competence, prioritize public good
What is data quality? - correct answer-Data quality is essential for useful
results.
What does 'garbage in, garbage out' mean? - correct answer-'Garbage in,
garbage out' means that if the input data is of poor quality, the output results
will also be of poor quality.
Why is it important to have good data sources? - correct answer-Good data
sources ensure that the whole provenance chain is trusted and that the data is
representative of the actual domain.
What is the process of cleaning data? - correct answer-Cleaning data involves
improving data quality as much as possible for specific uses.
, Why is it easier to automate analysis in Python than in Excel? - correct
answer-Python allows for easier automation and testing compared to Excel,
which often contains unnoticed errors in formulas and data.
Why is it important to know the limitations of the techniques used in data
analysis? - correct answer-Knowing the limitations helps in checking the
applicability of the techniques and ensures accurate results.
What is the significance of scatterplots in data analysis? - correct
answer-Scatterplots with all the data are helpful in spotting overall trends and
patterns between attributes.
Why should one be skeptical and ready to step away from initial findings in
data analysis? - correct answer-Being skeptical helps in avoiding biased or
incorrect conclusions and promotes objective analysis.
Why is it important to be open about limitations when communicating results?
- correct answer-Being transparent about limitations prevents overclaiming
and ensures accurate interpretation of the results.
What is asset management in data science? - correct answer-Asset
management involves effectively managing project assets (data and code) to
ensure quality outcomes, confidence in results, and privacy and confidentiality.
What impact does access control have on data management? - correct
answer-Access control, both in terms of policy and effective mechanisms, has
a significant impact on the client's business interests and the privacy of
individuals whose data is stored.
What rights are included in the concept of privacy? - correct answer-The
concept of privacy includes the legal and moral right to keep personal data,
such as contact information, medical records, and financial records, private.
What are some examples of personal data that people have the right to keep
private? - correct answer-Examples of personal data that people have the
right to keep private include location data, browsing history, and other
sensitive information.
What is the right to know what information about you is held by others? -
correct answer-Right to access personal information
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