Ethics of Big Data is about finding alignment between an organization's core values and their day-to-day actions in a way that balances risk and innovation. As Big Data brings business operations and practices deeper and more fully into individual lives, it is creating a forcing function that raises ethical questions about our values around concepts like identity, privacy, ownership, and reputation. How we understand those values and align them with our actions when innovating products and services using Big Data technologies benefits from a framework that provides a common vocabulary and encourages explicit discussion. The material will address the intersection of ethics and Big Data; what it is and what it isn't. Specifically, how to approach and generate dialog about an abstract subject with direct, real-world implications. A general framework for talking about ethics in the context of Big Data will be introduced. Aspects include: 1. Direct relevance to your data handling practices 2. How Big Data is influencing important concepts including identity, privacy, ownership, and reputation 3. Ethical Decision Points 4. Value Personas as a tool for encouraging discussion and generating agreement and alignment between values and actions 5. Balancing the benefits of Big Data innovation and the risks of harm The webcast will present key concepts from the forthcoming book Ethics of Big Data

1. An Introduction to
Ethics of Big Data
§ Webcast by Kord Davis"

2. Preamble
§ Deeply passionate about more productive discussion"
§ Academic background in philosophy"
§ Experiences with Big Data "
§ Topic site to launch with book release"
§ #ethicsofbigdata "
www.ethicsofbigdata.com" Twi$er:
@kordindex
#ethicso4igdata

3. Current State
§ A data architect and a product
manager (or two) walk into a
meeting… "
§ Creepy? Yes, it is. No, it isnʼt."
§ In the absence of a common
vocabulary and framework for
discussion, individuals revert to
their own moral codes"
www.ethicsofbigdata.com" Twi$er:
@kordindex
#ethicso4igdata

4. Future State
§ Creating a common vocabulary and
framework for productive discussion
(ethical inquiry)"
§ Ethics of Big Data is about
understanding the influence of our
values on our actions. "
§ Seeking a set of common values"
§ Action in alignment with those values"
www.ethicsofbigdata.com" Twi$er:
@kordindex
#ethicso4igdata

5. Path Forward
§ Review key concepts in the book"
§ Raise awareness and engagement"
§ Intentional ethical inquiry"
§ Explore a framework"
"» Four Aspects of Big Data Ethics"
"» Ethical Decision Points"
"» Values & Actions Alignment"
"» Value Personas"
"
"
"
www.ethicsofbigdata.com" Twi$er:
@kordindex
#ethicso4igdata

6. What Is This Big Data Thing?
§ Assuming familiarity"
§ Some characteristics"
§ Familiar examples"
§ Volume, variety, velocity creates a “forcing function”"
www.ethicsofbigdata.com" Twi$er:
@kordindex
#ethicso4igdata

7. What Is This Ethics Thing?
§ Big Data is ethically neutral"
§ Use of Big Data is not"
§ Ethics is only one aspect"
§ Abstract concepts, real implications"
§ Ethical inquiry informs ethical action"
§ Ethical principles informed by values"
§ Aligning action with those values"
www.ethicsofbigdata.com" Twi$er:
@kordindex
#ethicso4igdata

8. Big Data’s Forcing Function
§ Pushing business operations
deeper into our lives"
§ Changing common meanings"
§ Value implications"

9. Big Data’s Forcing Function
§ Volume, Variety, Velocity "
§ The Supreme Court and Netflix"
§ Data Exhaust/Ecosystem/Life stream"
§ Meta-data"
"
www.ethicsofbigdata.com" Twi$er:
@kordindex
#ethicso4igdata

10. Anatomy of a Tweet
§ Place type"
§ Verified Badge status"
§ Number of favorites"
§ Number of followers"
§ Protected status"
§ Country"
§ Application used to Tweet"
§ Authorʼs screen name"
§ Authorʼs biography"
www.ethicsofbigdata.com" Twi$er:
@kordindex
#ethicso4igdata

11. Big Data’s Forcing Function
§ Imagine if Hemingway blogged, JFK tweeted, or Rosa
Parks was on Facebook"
§ What will our grandchildren know about us that we didnʼt
know about our grandparents?"
§ Library of Congress"
§ Political change (Egypt, SOPA)"
§ Social change (location, interaction, communication)"
§ Education, Healthcare, Weather"
"
www.ethicsofbigdata.com" Twi$er:
@kordindex
#ethicso4igdata

12. Big Data’s Forcing Function
§ Risk"
!» Security!
!» Privacy!
!» Legal compliance!
!» Customer Engagement!
§ Opportunity"
!» Innovation!
!» Deeper insights!
!» Broader outlooks!
!» Customer Engagement!
!
!
"
www.ethicsofbigdata.com" Twi$er:
@kordindex
#ethicso4igdata

13. Balancing Risk and Innovation
§ Use the Force"
!» Acknowledge!
!» Frame!
!» Differentiate!
!» Engage!
§ Frame Key Aspects"
!!
"
www.ethicsofbigdata.com" Twi$er:
@kordindex
#ethicso4igdata

14. Four Aspects of Big Data Ethics
§ Identity"
§ Privacy"
§ Ownership"
§ Reputation"

15. Four Aspects of Big Data Ethics
Iden8ty
Privacy
Ownership
Reputa8on
www.ethicsofbigdata.com" Twi$er:
@kordindex
#ethicso4igdata

16. Four Aspects of Big Data Ethics
§ Identity"
» Is offline existence identical to online existence?!
§ Privacy"
» Who should control access to data about you?!
§ Ownership"
» What does it mean to own data about ourselves?!
§ Reputation"
» How can we determine what is trust-worthy?!
"
www.ethicsofbigdata.com" Twi$er:
@kordindex
#ethicso4igdata

17. Iden8ty
Privacy
Identity Ownership
Reputa8on
§ “Identity is prismatic”, Chris Poole"
§ “Having two identities for yourself is an example of a
lack of integrity”, Mark Zuckerberg"
§ Fred Wilson proposes “lightweight” online identity"
§ New products and services launch"
§ US Government proposes National Strategy for
Trusted Identities in Cyberspace!
§ Google+ policy changes on pseudonyms"
"
www.ethicsofbigdata.com" Twi$er:
@kordindex
#ethicso4igdata

18. Iden8ty
Privacy
Privacy Ownership
Reputa8on
§ “Data can be either useful or perfectly anonymous but
never both.” (Paul Ohm)"
§ 87% of Americans can be identified by three data points:
gender, birthdate, ZIP code"
§ In last 12 months:"
» Supreme Court ruled warrantless GPS tracking is unconstitutional"
» Homeland Security tests crime prediction technology"
» Zuckerberg declares “age of privacy” to be over"
» New product and services launch based on privacy control"
» OʼReilly publishes “Privacy and Big Data”"
» Google streamlines 60+ privacy policies into one—generating
industry debate and Congressional inquiry"
"
"
www.ethicsofbigdata.com" Twi$er:
@kordindex
#ethicso4igdata

19. Iden8ty
Privacy
Ownership Ownership
Reputa8on
§ Google website devoted to “liberating your data”"
§ UK government proposes “personal identity data”
marketplace (a DC company does the same)"
§ Doc Searls calls for an end to collecting customer data"
§ World Economic Forum (WEF) describes personal data
as a “new economic asset class” (data as currency)"
§ The Sierra Club sues Orange County for access to GIS
data"
"
www.ethicsofbigdata.com" Twi$er:
@kordindex
#ethicso4igdata

20. Iden8ty
Privacy
Reputation Ownership
Reputa8on
§ Google+ policy changes on pseudonyms"
§ “The Future of Reputation” (2007)"
§ New products and services launch"
§ “Reputation management” "
§ Ongoing debate about reputation"
"» Itʼs alive: h$p://www.avc.com/a_vc/2010/03/how-­‐to-­‐defend-­‐your-­‐reputa8on.html"
"» Itʼs dead: h$p://techcrunch.com/2010/03/28/reputa8on-­‐is-­‐dead-­‐its-­‐8me-­‐to-­‐overlook-­‐our-­‐indiscre8ons/
"
"
"
"
www.ethicsofbigdata.com" Twi$er:
@kordindex
#ethicso4igdata

21. Current Practices: Alignment?
§ What is the current state of affairs?"
§ Fortune 50 public-facing policy
statements"

22. Current Practices: Buying & Selling
§ On the one hand…34 out of Fortune 50 companies
would NOT SELL personal data without consent"
§ No policy stated they would sell personal data"
§ On the other hand…11 out of Fortune 50 stated they
would BUY (or “obtain”) data from third parties"
§ 0 out of Fortune 50 stated they would NOT BUY
personal data"
www.ethicsofbigdata.com" Twi$er:
@kordindex
#ethicso4igdata

23. Ethical Decision Points
§ If itʼs not okay to sell something,
how is it okay to buy it?"

24. Ethical Decision Points
§ Ethical incoherence"
§ Values and actions can be in conflict"
§ “Donʼt know what we donʼt know”"
§ Opportunity to align values and
actions to increase collaborative
innovation"
§ Reduce value conflicts in Big Data
innovations"
§ Comfort factor (reduced creepy)"
www.ethicsofbigdata.com" Twi$er:
@kordindex
#ethicso4igdata

25. Ethical Decision Points
§ Some real-world examples include:"
"» adding a new product feature"
"» policy development"
"» security breach"
"» designing new products/services"
"» opportunity to use or combine data in a new way"
www.ethicsofbigdata.com" Twi$er:
@kordindex
#ethicso4igdata

26. Ethical Decision Points
§ " Continuous cycle:"
"» Inquiry" Inquiry
"» Understanding"
"» Articulation"
Ac8on
Understanding
"» Action"
Ar8cula8on
www.ethicsofbigdata.com" Twi$er:
@kordindex
#ethicso4igdata

27. Values & Actions
§ Alignment"
§ Benefits of alignment"
§ Risks of misalignment"
§ Value Personas"
"
"
www.ethicsofbigdata.com" Twi$er:
@kordindex
#ethicso4igdata

28. Values & Actions
§ You already know how to do this"
§ Our values inform our actions all the time"
§ We value lots of things"
§ Ethical practice is an outcome of ethical inquiry"
§ Ethical inquiry is an exploration of values"
§ Values can be personified"
"
"
www.ethicsofbigdata.com" Twi$er:
@kordindex
#ethicso4igdata

29. Value Personas
§ Evolution of “user persona”"
§ Articulate how specific values inform
specific actions in specific context"
§ Aligns operational perspectives on
values & actions: executives,
managers, line staff"
§ Designed in collaborative workshops
with cross-functional team"
www.ethicsofbigdata.com" Twi$er:
@kordindex
#ethicso4igdata

30. Value Personas
§ Considerations include:"
"» Intention"
"» Security"
"» Likelihood"
"» Aggregation"
"» Responsibility"
"» Benefit"
"» Harm"
"» Organizational roles"
"» Timeline"
"
"
"
www.ethicsofbigdata.com" Twi$er:
@kordindex
#ethicso4igdata

31. Common Themes
§ Big Data is:"
"» Ubiquitous"
"» Permanent"
"» Explicit"
"» Aggregated"
www.ethicsofbigdata.com" Twi$er:
@kordindex
#ethicso4igdata

32. Transparent Collaboration
§ Acknowledge the complexity at Ethical Decision Points"
§ Be explicit with ethical discussions"
§ Engage the nuance"
§ Encourage “value talk”"
§ Use Value Personas to help create a common
understanding & facilitate dialog"
§ Seek alignment of values and actions"
§ See Exact Target best practices"
"» http://subscribersrule.com/"
"» http://www.exacttarget.com/company/orange-culture.aspx "
www.ethicsofbigdata.com" Twi$er:
@kordindex
#ethicso4igdata

33. Transparency
§ If your data handling actions
were known today … would
they align with your values?
Your customerʼs values?"

34. Thank You!
§ Topic site: "www.ethicsofbigdata.com"
§ Blog: " "www.kordindex.com"
§ Email: " "kord@28burnside.com"
§ Twitter:" "http://twitter.com/kordindex "
§ LinkedIn: "http://www.linkedin.com/in/korddavis "
§ Ethics of Big Data (OʼReilly, March 2012):"
" "http://shop.oreilly.com/product/0636920021872.do"
"
"
"
"
"
All references will be provided in archived presentation."
www.ethicsofbigdata.com" Twi$er:
@kordindex
#ethicso4igdata