When Machines Decide: The Promise and Peril of Living in a Data-Driven Society: Syllabus

Honors 3700-002, Fall, 2016-Spring 2017 Thursdays 2:00 pm-5:00 pm MHC 1205

Syllabus

Download the Syllabus and Course Schedule

KEY DATES FOR FALL SEMESTER

August 25, 2016 Student survey completed; selection/assignment of student class discussion leader teams.
September 1, 2016 Personal bios posted on Library Guide;
September 8, 2016 Selection of individual research topics
November 17, 2016 Student oral presentations on individual research projects
December 1, 2016 Student oral presentations on proposed Team Projects
December 8, 2016 Final selection and preliminary planning on Team Projects

 

Week 1: August 25---Introduction to the Course

Topics:
Introductions, review of syllabus and LibGuide, completion of student survey, selection of student research topics and discussion  leaders, ice-breaker exercise,other administrative information, etc.

Readings:
     None

 

Week 2: September 1---What is Big Data & Why is it Important?

Topics:
The characteristics of big data, the three “V’s”; how does big data differ from small data?; the life-cycle of big data; the growing importance of big data; how big data is and will be affecting our daily lives; some examples of high value big data uses.

Readings:

 

Week 3: September 8---The Collection, Consolidation, and Storage of Data

Topics:
The generators of data (e.g. social networks, mobile devices, geo-fencing, internet of things, businesses, governments, etc.); the aggregators of data (e.g. data brokers, businesses, government, etc.); data storage, data management & processing technologies (e.g. Hadoop, MapReduce, Spark, Pig, NoSQL, etc.); public and private databases.

Readings:

 

Week 4: September 15--- The Mining, Analysis and Use of Data

Topics:
The ABC’s of algorithms, machine learning and artificial intelligence; descriptive vs.
predictive analysis; de-identification and re-identification; reliability and limitations of big data analytics.

Readings:

 

Week 5: September 22---An Overview of the Potential Benefits & Dangers of Big Data

Topics:
The benefits of better decision-making, financial gain & advancing social good; the risks of bias, discrimination, exploitation, inequity and inequality; loss of privacy and surveillance and tracking by business and government;

Readings:

 

Week 6: September 29--- A Deeper Dive into Algorithms & Fairness Issues

Topics:
What are the different types of algorithms? How do they work? Are algorithms fair, discriminatory, racist, biased etc.? Can they substitute for human judgment? Transparency, accountability and ethical issues issues.

Readings:

 

Week 7: October 6---The Regulation/Governance of Big Data

Topics:
Existing laws, regulations, policies and best practices potentially applicable to the collection, management, use, analysis & privacy of data; ethical issues.

Readings:

 

Week 8: October 13---No Class- Fall Break

 

Week 9: October 20---Big Data and Law Enforcement

Topics:
The benefits and dangers associated with using big data for crime prevention, interdiction and in the criminal justice system; predictive policing, data consolidation and sharing, identifying crime patterns and using big data for realtime situational threat assessment; the specter of “big brother” and mass surveillance; the loss of the human element in crime interdiction; data and sentencing.

Readings:

 

Week 10: October 27--- Big Data and Education

Topics:
Use of big data for admissions, retention, identifying students at risk, predicting success, course scheduling, student advising and delivery of courses. University use of outside vendors or data analytics; privacy and data security issues

Readings:

Guest Presentation:

  • Mike Martineau, Director of Institutional Analysis, University of Utah

 

Week 11: November 3---Big Data and Business

Topics:
Understanding customer needs and how businesses are using machines to make decisions not only in marketing and retail sales, but also in making hiring and other human resources decisions; consent and privacy issues when businesses collect information about consumers.

Readings:

Guest Presenter: 

Trevor Dryer, Founder and CEO, Mirador

 

Week 12: November 10---Big Data and Healthcare

Topics:
Precision medicine, electronic health records, privacy of medical information, aggregation and sharing of records, transparency, medical device wearables, improved efficiency, patient outcomes and reduction of costs.

Readings:

Guest Presenter:

Willard H. Dere, MD, Director of the Program in Personalized Health and Co-Director of Center for Clinical and Translational Science at the University of Utah Health Care System.

Loren Larsen, Chief Technology Officer, HireVue

 

Week 13: November 17---Student Oral Presentations on Research Projects

Week 14: November 24---No Class - Thanksgiving Holiday

Week 15: December 1---Student Oral Presentation on Proposed Team Projects

Week 16: December 8---Final Selection and Preliminary Planning on Team Projects: Discuss detailed description of team project(s) and determin milestones and assignments over the semester break

 

 

 

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