There has been very little analysis of big data ethics from an Ignatian or Catholic Social Thought point of view.  The Jesuit tradition, with its focus on persons and community, as well as the CST tradition, certainly provides some direction for navigating these difficult Big Data questions.

1. An Ignatian
Approach to Big
Data Ethics
Andy Gustafson – Creighton University
Celeste Harvey – College of St. Mary (Omaha)

2. Big Data
Big Data refers to the extremely large data sets that may be analyzed to
reveal and predict patterns, trends and associations, especially with regard
to human behavior and interactions. We know facebook, google, amazon,
apple and others gain data from us which can then be either used by them,
or sold to others. More and more IT investment is going into getting,
managing and maintaining big data (and many of our schools now offer
finance/data analytics classes and degrees).
But with big data come big ethical questions.

3. Some Ethical Issues
• Ethical precepts for data science and codes of conduct,
• Privacy and confidentiality
• Consent and Choice
• Ownership
• Fairness (asymmetric info expansion)
• Responsible conduct of research
• Reasonable use of data
• Substantiated conclusions from data
• Ability to detect algorithmic bias
• Societal Effects of AI decision-making
• Personal moral effects of AI decision-making
• Social Responsibility concerns for data analysts and AI coders
• Loss of Serendipity

4. • There has been very little
analysis of big data ethics from
an Ignatian or Catholic Social
Thought point of view. The
Jesuit tradition, with its focus
on persons and community, as
well as the CST tradition,
certainly provides some
direction for navigating these
difficult Big Data questions.

5. Not Good or Bad:
Good, Bad and Ugly.
• Big Data Analysis and AI is with us to
stay. There are a myriad of wonderful
possibilities which can come from data
analysis and AI, but we must give a
great deal of thought to the
unintended consequences, as well as
the rightness or wrongness of some
applications of Big Data Analysis.

6. Example 1: Apple Face-Recognition and
Ousmane Bah
• Ousmane Bah, who was arrested on charges of stealing from an
Apple store in Boston (a town which he had never been to) on the
very night that he was at his prom in Manhattan. NYC police
arrested him at 4am at his home, with an arrest warrant obtained
based on Apple’s allegations which were based on face recognition
technology.
• “When a name is mismatched to a particular face,” the suit states, "the
security benefits the Face ID software become a criminal’s weapon.

7. “What your Face May Tell Lenders
About Whether You’re Creditworthy”(WSJ 6/10/19)
• China’s huge insurer, Ping An, uses facial recognition technology to
verify identities as well as to examine expressions for clues about
their truthfulness, and to assess risk of the insured (but also to keep
agents from skipping meetings).
• Biometric companies (Aware, Ping An, etc) are doing very well and
payment providers are using the biometric identity verification more and
more.

8. China’s Social Credit System
• China’s Social Credit System, rates a person’s reputation using in
part China’s mass surveillance systems to potentially ban some
citizens from flying or using the train, throttling your internet speeds,
banning your kids from the best schools, keeping you from getting
the best jobs or rooms at the best hotels, and potentially even taking
away your dog.
• “China's social credit system has been compared to Black Mirror, Big
Brother and every other dystopian future sci-fi writers can think up. The
reality is more complicated — and in some ways, worse.” (WIRED 2019)

9. Social Credit System Continued
• Of course Uber, Ebay, Yelp, and Experian already rate aspects of our lives.
• But the SCS judges a wide swath of personal behavior (and that of your
online friends) and then punishes or rewards you accordingly. "It's both
unique (to China) and part of a global trend.“
• There is no singular SCS, but a hodgepodge of local social record systems at
this point.
• The target, eventually, is that the government system will be country wide,
with businesses given a "unified social credit code" and citizens an identity
number, all linked to permanent record. "If you go to a credit China
website, and you have an entity's credit code, you can type that in and pull
up credit records," explains Hoffman. "Individuals will have ID-linked
codes." It's less a score, she says, and more of a record.

10. • “If their score reaches 600, they can take out a Just Spend loan of up to
5,000 yuan (around £565) to use to shop online, as long as it's on an
Alibaba site. Reach 650 points, they may rent a car without leaving a
deposit. They are also entitled to faster check-in at hotels and use of the
VIP check-in at Beijing Capital International Airport. Those with more than
666 points can get a cash loan of up to 50,000 yuan (£5,700), obviously
from Ant Financial Services. Get above 700 and they can apply for
Singapore travel without supporting documents such as an employee
letter. And at 750, they get fast-tracked application to a coveted pan-
European Schengen visa. "I think the best way to understand the system is
as a sort of bastard love child of a loyalty scheme," says Creemers.
• “Higher scores have already become a status symbol, with almost 100,000
people bragging about their scores on Weibo (the Chinese equivalent of
Twitter) within months of launch. A citizen's score can even affect their
odds of getting a date, or a marriage partner, because the higher their
Sesame rating, the more prominent their dating profile is on Baihe.”
(Wired, 2017)

11. Problems with
SCS approach
• It is an externalist approach, relying entirely
on consequent punishments, not on
transformation of the person’s desires.
• It undermines individual freedom and
choice by eliminating true privacy. Without
privacy there is no chance to do right
without reward.
• It has a superficial (fascist) ‘common good’
aim without protection of dignity of the
person or difference– which is not common
good at all.

12. AI Ethics Source: Data via Moral Machine
• MIT Moral Machine

13. Is Ethics Democratic/Determined by Majority?
• Traditionally, ethics are ideals, not derived from empirical
observation.
• Ethical norms tell us what OUGHT to be, not what IS happening.
• We frequently observe that the ethical action is heroic, because it is
so uncommon among us.
• So deriving ethics from mass polling is probably not a solid basis for
ethics.

14. Basic Problem: Elimination of the Human
• “From the start, the Spiritual Exercises encourage purposeful
reflection on the relationship between one's everyday activities and
the end or set of ends associated with those activities. However, the
Exercises do not just encourage reflection upon an abstract final end.
Rather, they have the person purposefully contemplate the way he or
she directs his or her life toward "the good" of the deity. As spiritual
exercises, the Exercises encourage individual reflection upon the
movements of the soul by the divine spirit and its ungodly opposite -
God and the evil spirit.” Dennis Moberg, 2001, JBE

15. Jesuit Values vs Big Data Practices:
• Cura Personalis… Create Profile to guess (Minority Report, Pre-crime)
• Discernment.... Decisions made for us (SDVs)
• Finding God in all things... Yes and no– amazing technology
• Magis . ... More can be done…
• Reflection Automated decisions
• Service rooted in justice... Possible helps…?
• Solidarity and kinship. Lockstep

16. CST Principles & Big Data Analytic practices
• Common Good Does it include the individual?
• Dignity of Human Person Am I data, or a person? Mob/masses rule?
• // Rights&Responsibilities No Privacy, no full responsibility
• Solidarity Not by choice though…
• Pref. Option for the Poor and Vulnerable Wasted Lives (Zygmunt Bauman)
• Stewardship and Care for Creation Possibly?
• Subsidiarity:Local/least centralized auth? CSC = Government gone wild

17. MBA Class
Week 1
Watch: Katina Michaela on the Dangers of Over-Quantifying
yourself
and Watch:
The Dangers of Big Data
Read:
Big Data: New Opportunities and New Challenges
Ethics for Big Data and Analytics
Introduction to: Weapons of Math Destruction
“Big Data Ethics” Andrej Zwitter in Big Data and Society July-
December 2014:1-6
Week 2
Weapons of Math Destruction (Ch1-3)
A defense of ad blocking and consumer inattention Ethics and
Information Technology Sept 2018 20:3 143-155.
"AI can help us live more Deliberately" by Julian Friedland, MIT
Sloan Management Review 6/2019
Watch: The Social Dilemma
Week 3
Weapons of Math Destruction (Ch4-7)
“From Individual to Group Privacy in
Big Data Analytics” Mittelstadt, Brent
In Philosophy & Technology, 30(4), 475-494. 20 p. DEC 2017.
“Big Data Ethics” Richads & King, Wake Forest Law
Review 49 (2014) 393-432.
Week 4
Weapons of Math Destruction (Ch 8-10)
"From Dignity to Security Protocols: A Scientometric Analysis of
Digital Ethics" René Mahieu, Nees Jan van Eck, David van
Putten & Jeroen van den Hoven
Ethics and Information Technology volume 20, pages175–
187(2018)
IS Democracy Safe in the Age of Big Data?
Watch: The Creepy Line

18. Bibliography
• Bauman, Zygmunt (2003) Wasted Lives
• Moberg, Dennis and Martin Calkins (2001) “Reflection in Business Ethics:
Insights from St. Ignatius ‘ ‘Spiritual Exercises’” Journal of
Business Ethics, 33:3 257-270.
• “Ethics for Big Data and Analytics” O’Leary, IEEE 31:4 2016.
• “Student Sues Apple for $1 Billion, Blames Face-recognition Tech for False
Arrest”
• “The complicated truth about China’s social Credit System” Wired, 2019
• “Big Data Meets Big Brother” Rachel Botsman, Wired 10/21/17.
• “What your Face May Tell Lenders About Whether You’re Creditworthy”
Wall Street Journal
• “China Has Started Ranking Citizens with a Creepy ‘Social Credit’ System—
Here’s What You Can Do Wrong, and the Embarassing, Demeaning Ways
they Can Punish You” Business Insider (India) 4/8/18.
• The Creepy Line
• The Social Dilemma

19. andrewgustafson@creighton.edu
• Creighton University, Omaha Nebraska, USA