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| Citation |
- Permanent Link:
- http://digital.auraria.edu/IR00000117/00001
Material Information
- Title:
- The Devil Wears Data
- Creator:
- Swauger, Shea
- Place of Publication:
- Denver, CO
- Publisher:
- ThinqStudio
- Publication Date:
- 02-21-2020
- Physical Description:
- Presentation
Notes
- Abstract:
- Predictive analytics, artificial intelligence, and facial recognition technology are just a few of the
things your data can be plugged into without consent. In this workshop, we’ll discuss data profiling technologies and techniques levied specifically at students; who, what, why, when, where and how data is mined; and to what end? We’ll explore notions of student data rights, data ethics, privacy, and trends in data legislation.
- Acquisition:
- Collected for Auraria Institutional Repository by the Self-Submittal tool. Submitted by Shea Swauger.
- Publication Status:
- Unpublished
Record Information
- Source Institution:
- Auraria Institutional Repository
- Holding Location:
- Auraria Library
- Rights Management:
- Copyright [name of copyright holder or Creator or Publisher as appropriate]. Permission granted to University of Colorado Denver to digitize and display this item for non-profit research and educational purposes. Any reuse of this item in excess of fair use or other copyright exemptions requires permission of the copyright holder.
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ERROR CAUGHT WHILE SAVING NEW DIGITAL RESOURCE TO SOLR INDEXES
2/28/2020 5:53:16 PM
Unable to connect to the remote server
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at SobekCM.Engine_Library.Solr.v5.v5_Solr_Controller.Update_Index(String SolrDocumentUrl, String SolrPageUrl, SobekCM_Item Resource, Boolean Include_Text) in C:\GitRepository\SobekCM-Web-Application\SobekCM_Engine_Library\Solr\v5\v5_Solr_Controller.cs:line 59
at SobekCM.Engine_Library.Solr.Solr_Controller.Update_Index(String SolrDocumentUrl, String SolrPageUrl, SobekCM_Item Resource, Boolean Include_Text) in C:\GitRepository\SobekCM-Web-Application\SobekCM_Engine_Library\Solr\Solr_Controller.cs:line 33
at SobekCM.Library.MySobekViewer.New_Group_And_Item_MySobekViewer.complete_item_submission(SobekCM_Item Item_To_Complete, Custom_Tracer Tracer) in C:\GitRepository\SobekCM-Web-Application\SobekCM_Library\MySobekViewer\New_Group_And_Item_MySobekViewer.cs:line 857
PAGE 1
THE DEVIL WEARS DATA
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Hi. I'm Shea.
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OUTLINE 1. Identifying bias 2. Three technologies to examine 3. Scenario exercise 4. Sticky exercise 5. Discussion and wrap up
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You already know more than you think.
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Technology and data are neutral and objective. MYTH:
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Technology and data are representations of power. REALITY:
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Intent is different from impact.
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TECHNOLOGIES TO EXAMINE 1. Artificial Intelligence/Machine Learning 2. Predictive Analytics 3. Facial Recognition
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A computer system that is feed large amounts of data which it uses to learn how to do a specific task. ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING
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HOW AI AND MACHINE LEARNING ARE BEING MARKETED TO HIGHER EDUCATION
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AI, MACHINE LEARNING, AND EQUITY
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RECENT DEVELOPMENTS WITH AI AND MACHINE LEARNING
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PREDICTIVE/LEARNING ANALYTICS The use of historical data and statistics to make predictions about something.
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HOW PREDICTIVE/LEARNING ANALYTICS ARE MARKETED TO HIGHER EDUCATION
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PREDICTIVE/ LEARNING ANALYTICS AND EQUITY
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RECENT DEVELOPMENTS WITH PREDICTIVE AND LEARNING ANALYTICS
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FACIAL RECOGNITION A technology used to identify a person based on their facial features and comparing them to a database of known people.
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HOW FACIAL RECOGNITION IS MARKETED TO HIGHER EDUCATION
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FACIAL RECOGNITION AND EQUITY
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RECENT DEVELOPMENTS WITH FACIAL RECOGNITION
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FALSE POSITIVES AND FALSE NEGATIVES When you design a technology, you make choices about how sensitive to make it. ! More sensitive = detecting all of what you want, some of what you don't ! Less sensitive = detecting some of what you want, none of what you don't
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Three scenarios 1. A.I. to detect cheating online 2. Predictive analytics for admissions 3. Facial recognition for campus building access APPLYING ETHICS IN TECHNOLOGY
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1. Form up in groups 2. Read over the scenario 3. Talk through the questions 4. Choose someone to share out SCENARIO EXERCISE 10 MINUTES
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1. What values do you want in your technology? 2. What values do you NOT want in your technology? 3. What rights do you want regarding your data? 4. What do you want to tell the leaders of the university about technology? STICKY EXERCISE 10 MINUTES
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OUTLINE 1. Identifying bias 2. Three technologies to examine 3. Scenario exercise 4. Sticky exercise 5. Discussion and wrap up
PAGE 29
CONTACT shea.swauger@ucdenver.edu Twitter @ SheaSwauger
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