MACHINE LEARNING AND FACIAL RECOGNITION
There is a lot of buzz, and controversy, surrounding the use of machine learning and facial recognition today. Facial recognition is being used more and more frequently, from automatically tagging photos on social media to unlocking your smart phone. While the potential value of facial recognition is immense, it also raises ethical questions and privacy concerns.
For this Discussion, you will examine two case studies which concern the utility of machine learning algorithms. You will also play a game called, Which Face is Real? which tests your skill in detecting AI-generated faces from the real thing.
RESOURCES
Be sure to review the Learning Resources before completing this activity.
Click the weekly resources link to access the resources.
WEEKLY RESOURCES
TO PREPARE
• Review the “Criminal Machine Learning” case study and the “Machine Learning About Sexual Orientation?” case study from the Calling Bullshit: Data Reasoning in a Digital World website in this week’s Learning Resources.
• Once you have read the above, review Which Face is Real? from the Calling Bullshit: Data Reasoning in a Digital World website in this week’s Learning Resources.
• Play Which Face is Real? multiple times until you feel you can successfully distinguish real faces from AI generated ones.
BY DAY 3
Post your responses to the following:
• What were the key points that Bergstrom & West make and how does it relate to the utility of the machine learning algorithms in either or both case studies?
• How did you perform on the Which Face is Real? game? How many times did you play? Did you improve? What did you discover about facial recognition?
Read a selection of your colleagues’ responses.
BY DAY 5
Respond to at least two of your colleagues’ posts, furthering the Discussion by comparing your experiences and responses with theirs and/or offering advice to help them better understand machine learning and facial recognition applications.
Note: For this Discussion, you are required to complete your initial post before you will be able to view and respond to your colleagues’ postings. Begin by clicking on the Post to Discussion Question link, and then select Create Thread to complete your initial post. Remember, once you click on Submit, you cannot delete or edit your own posts, and you cannot post anonymously. Please check your post carefully before clicking on Submit!
Return to this Discussion before the end of the week to read the responses to your initial posting. Note what you have learned and/or any insights that you have gained as a result of your colleagues’ comments.d
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