Zeynep Tufekci, techno-sociologist, 2016, 17:32
I. Pre-watching task
Comment on the title of the talk
II. Comprehension questions
1) Why have ethical questions come to the fore in computer science?
2) What are the positive and negative aspects of machine learning as a method?
3) How can predictive algorithms affect hiring? What safeguards did the company
mentioned in the talk use to ensure the transparency of their hiring algorithms?
4) What are computer algorithms compared to? Why?
5) How could computer systems amplify bias? What examples does the speaker mention?
How do algorithms affect parole and sentencing decisions? Why?
6) What stories did Facebook algorithms favour? What was the effect?
7) How else can machine intelligence fail?
8) How should people deal with algorithms?
III.Identify the topic and the thesis of the talk.
IV.Paraphrase and explain the following
churn through the data
digital crumbs
predictive power
smother a very important but difficult conversation
math-washing
algorithm suspicion
value-laden human affairs
to abdicate and outsource our responsibilities
V. Give the gist/summary of the talk.
VI.Expand on the statement you find most interesting, explain your choice:
We cannot outsource our responsibilities to machines.
The complexity of human affairs invades the algorithms.
We need to cultivate algorithm suspicion, scrutiny and investigation. We need to make sure we have
algorithmic accountability, auditing and meaningful transparency.
We need to audit our black boxes and not have them have this kind of unchecked power.