The best data scientists are those who think about the technical, social, ethical,
legal and business contexts of their work and question their data, the goals of
their work and their assumptions about their task.
These data scientists are critical data scientists. They reason about the
information presented to them and choose what to believe based on reflection and
independent consideration. This is known as ‘critical thinking’.
To become a critical data scientist, you must:
• Understand the connections between ideas.
• Identify inconsistencies and flaws in someone else’s reasoning.
• Prioritise ideas and facts in terms of relevance and magnitude.
• Reflect on your justifications, beliefs and values.
• Construct, assess and respond to other arguments.
In the following sections, you will find four different situational contexts
relating to what has been discussed in lectures and tutorials.
In each of these contexts are several provocations. Provocation is a
question or statement that prompts you to think critically about the
information in front of you so that you can draw from it and form your
opinion. You need to choosetwoof these contexts, critically assess and then
respond to the provocations they contain. These provocations mainly take
the form of questions.
Your answers for each context should be 750 words and should address the
provocations directly. The marks are allocated to the questions, and you
should base the amount you write about each on these weightings. There is
a leeway of 10% over or under the word count (75 words).
You should refer to all learning outcomes of this unit, as these will guide
your answers. In marking your submission, we are looking for evidence
that you have critically reflected on the information presented to you and
what information you have chosen, based on rational consideration, to
inform your opinion.
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