Citation
Sex, Lies, and Data

Material Information

Title:
Sex, Lies, and Data
Creator:
Colorado Learning and Teaching with Technology ( Conference )
Swauger, Shea ( Author, Primary )
Place of Publication:
Denver
Publisher:
University of Colorado Denver
Publication Date:
Physical Description:
Conference Papers

Notes

Abstract:
Data has promised fabulous new insights to higher education and research over last ten years, with libraries actively supporting data-related research through new services and infrastructure. However, these new data-intensive methods come with some unintended ethical consequences. This session will consider how libraries are uniquely situated to respond such dilemmas. Participants will be divided into teams to consider short, real-life examples of published research (studies from Ashley Madison, OkCupid, Facebook) and share how each violated fundamental principles of ethics, research, or librarianship. We will then discuss how libraries and other research institutions can proactively shape data ethics in teaching and research. The session leader will support the conversation with critical data theory and practical examples from a university setting.
Acquisition:
Collected for Auraria Institutional Repository by the Self-Submittal tool. Submitted by Shea Swauger.
Publication Status:
Unpublished

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Auraria Institutional Repository
Holding Location:
Auraria Library
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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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s ex, lies, a nd data

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agenda 1. d iscuss 3 examples of applied data ethics 2. b rief history of ethical regulation in academia 3. explore 1 new research area with potential ethical problems 4. b reak! 5. s et some rules for ethical research 6. d iscuss a new tool and its ethical implications

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instructions 1. f orm groups of 2 3 people 2. r ead one of the case studies, then as a group discuss (~10 minutes): 1. What happened? 2. How did it make you feel? 3. Were there any moral/ethical violations? Why? 4. Would you do anything differently? If so, what? 3. s hare with the larger group what you talked about

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group number one

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group number two

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! !"#$%&'() '*+*,

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group number three

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how did they make you feel?

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STRUCTURES for PROTECTION

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INSTITUTIONAL REVIEW BOARD

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TUSKEGEE SYPHILIS EXPERIMENTS

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1974

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1991

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2006

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2017

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2031 16

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ALGORITHMIC DISCRIMINATION

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SOMETIMES, THE WRONG THING TO DO MAY BE ALLOWED

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SOMETIMES, THE RIGHT THING TO DO MAY BE AGAINST THE RULES

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POLICY VIGILANTISM

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POLICY REFORM

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SOME GROUND RULES

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1. SILENCE DOES NOT EQUAL CONSENT

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2. ONLINE AVAILABILITY DOES NOT MAKE SOMETHING PUBLIC

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3 TOOLS ARE NOT NEUTRAL

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4. DATA ARE NOT NEUTRAL

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5 ETHICS ARE COMPLEX & INTERSECTIONAL

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6 CHECK YOURSELF (BEFORE YOU WRECK YOURSELF) Ice Cube

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7. OUR ONTOLOGIES & EPISTEMOLOGIES ARE SUSPECT

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ONTOLOGY

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ONTOLOGY

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EPISTEMOLOGIES

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EPISTEMOLOGY

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EPISTEMOLOGY

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n ormalizing bodies

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TSA BODY SCANNERS

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a pplying the concepts: Proctorio

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Proctorio records : video through your webcam audio through your microphone your desktop your web traffic facial movement body movement

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Proctorio flags the student for review if you: have unusual' body or facial movement get up and leave from the test t alk, or others talk around you look at another website look at another device take the exam from an unusual' location

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THINK, PAIR, SHARE (~10 minutes) What are some potential abuses of this product? Can those abuses be mitigated? How? What are some assumptions this product takes for granted? Can/should those assumptions be challenged? If so, how? Is the potential risk of abuse worth the potential benefit of the product? Defend you answer.

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v alues & assumptions are built into all tools and research

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build something into all tools & research that interrogates values & assumptions

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