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DAN FREY: Hello, I'm Dan Frey.

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And I'm the faculty research
director at MIT's D lab.

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I'm also principal investigator
for the Comprehensive

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Initiative on Technology
Evaluation, which we

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refer to by the acronym CITE.

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The CITE program was
established in order

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to assess and evaluate
technologies and products

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so that we can better understand
which ones perform the best

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and also which ones provide the
best value given the context.

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And better information about
process and technologies

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also helps us to best
implement those technologies

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in an international
development setting.

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Now, this topic is especially
important in machine learning.

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We understand that these
exciting new technologies

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can sometimes cause or else
propagate certain inequities

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or biases.

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And there are a
number of techniques

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that are now emerging from
research community that

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can help us to mitigate
those problems by adjusting

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the algorithms or
else modifying data

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sets in order to provide better,
more equitable, and more fair

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outcomes.

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Now, we hope that you'll
engage with us very deeply

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in this course and that we'll be
able to provide knowledge that

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can help you to better
implement these techniques

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in your own
professional endeavors.

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Thanks for joining
us in this course.

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