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DAN FREY: Hello, I'm Dan Frey.
And I'm the faculty research director at MIT's D lab.
I'm also principal investigator for the Comprehensive
Initiative on Technology Evaluation, which we
refer to by the acronym CITE.
The CITE program was established in order
to assess and evaluate technologies and products
so that we can better understand which ones perform the best
and also which ones provide the best value given the context.
And better information about process and technologies
also helps us to best implement those technologies
in an international development setting.
Now, this topic is especially important in machine learning.
We understand that these exciting new technologies
can sometimes cause or else propagate certain inequities
or biases.
And there are a number of techniques
that are now emerging from research community that
can help us to mitigate those problems by adjusting
the algorithms or else modifying data
sets in order to provide better, more equitable, and more fair
outcomes.
Now, we hope that you'll engage with us very deeply
in this course and that we'll be able to provide knowledge that
can help you to better implement these techniques
in your own professional endeavors.
Thanks for joining us in this course.
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