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Ethics of Algorithms
Dominique Shelton Leipzig
Partner, Privacy & Security, Co-Chair Global Ad Tech & Data Management
Perkins Coie
Artificial Intelligence and Privacy What do new privacy laws mean for your AI business?
Part 1: How Did We Get Here?
Part 2: CCPA and AI
Part 3: AI in a Pandemic
2
INTRODUCTION
CCPA: HOW DID WE GET HERE?
DOMINIQUE SHELTON LEIPZIG
3
Global Privacy Trends
India may be next...
4
The GDPR: Rights & Obligations
1 2
3
4 5
6
7
8
Right to Access (can be made irrespective
of lawful basis of processing (Art.15)
Correction Request Right
(Art. 16)
Erasure Requests (Art. 17) -
only valid under six
circumstances)
Restriction Request
(Art. 18)
Right of Portability
(Art. 20; only for consent or
contractual necessity)
Objection Rights
(Art. 21)
Objection to Automated
Processing (Art. 22)
Transparency Obligation
(Art. 13)
5
AI and GDPR
• Valid Legal Basis for
Processing Art. 6
• Human review of
contested automated
decision-making Art. 22
• Deletion
• Correction
• Access
6
New State Proposed Laws and Two New Federal Bills
1. Colorado
2. Connecticut
3. Hawaii
4. Illinois
5. Maryland
6. Massachusetts
7. Mississippi
8. New Jersey
9. New York
10. New Mexico
11. North Dakota
12. Pennsylvania
13. Rhode Island
14. Texas
15. Vermont
16. Virginia
17. Washington No federal preemption in place.
7
2018 and 2019 Ballot Initiatives
• June 2018
Ballot Initiative
Qualifies
• Compromise
Legislation
• CCPA 2.0
11/13/2019
• Federal
Privacy Law
8
On the Horizon in California 2020
• Proposed Regs 10/10/2019; AG says minimal changes expected
• Final CPRA version submitted on 11/13/2019; currently out for signature
9
The CCPA: Rights & Obligations
1 2
3
4 5
6
7
8
Abbreviated Right to
Know Re PI Collection
Expanded Right to Know
RE PI Collection
Detailed Right to Know PI
Sales and/or Disclosures for
a Business Purpose
Right to Opt Out of PI
Sales for Adults
Right to Opt-In to PI Sales
for Kids
Right to Access
and Portability
Right to Deletion
Right Not to Be
Discriminated Against for
Asserting Rights 1-7
10
Three Independent Business Obligations
Targeted
Training
Create Designated Methods
for Asserting Rights
Obtain Immunity by
Making Contract Meet
Specific Criteria
11
CCPA – Artificial Intelligence
12
AI and the CCPA
• Consumer Right Nos. 1-3 Require transparency about
– Specific pieces of PI
– Purposes of Collection
– Sharing
– Sale
• Deletion Rights
• Access Rights
13
AI vs. Privacy to fight the Pandemic
14
Legislative Concerns re: Covid-19 and Privacy
15
CCPA Definition of PI Is Broad
• Identifiers
• Geolocation
• Professional or
employment
information
• Education
information
• Protected
Characteristics
• Commercial
Information
• Internet or Other
Electronic Network
Activity
Information
• Inferences
• Biometric
Information (e.g.,
facial recognition,
fingerprint, voice
recordings,
iris/retina images)
• Audio, electronic,
visual, thermal,
olfactory, or similar
information
16
Perkins Coie Comments to the CA AG on Behalf of
California Chamber of Commerce
CAL CHAMBER COMMENTS
REGARDING REGULATIONS
17
CCPA in the Press
18
Coordinate Responses For Consumer Requests
19
Implementing the CCPA:
A Guide for Global Business
https://iapp.org/store/books/a191P000003QmX3QAK/
20
Speaker Info
DOMINIQUE SHELTON LEIPZIG
Partner and Co-Chair, Ad Tech Privacy & Data Management Practice, Perkins Coie [email protected]
21
Algorithms, Ethics and recruiting
Loren Larsen
CTO
HireVue
RESUME
ANALYTICS
TOP CANDIDATE DISTRIBUTION
WITHOUT ASSESSMENTS TOP CANDIDATE DISTRIBUTION
WITH ASSESSMENTS
Simple Candidate Prioritization
ADVERSE IMPACT (4/5THS RULE) ILLUSTRATION
MALE
FEMALE
KEY: Adverse Impact Ratio Calculations
Before Mitigation (33% cutoff score):
Male Passing Rate (MPR): 80% Female
Passing Rate (FPR): 53%
Female Adverse Impact Ratio:
.67 (FPR / MPR)
33%
R VALUE = .42
66%
The Dilemma of Ethics and Algorithms:
Transparency, Secrecy, Innovation, and
Consumer Rights
Samir Mehta
Partner
Stinson, LLP
The Dilemma
• Consumers want:
– To know what data is used
– To know how that data is used
• Businesses want:
– To create new tools that use data in new ways
– To protect their new tools from disclosure
Why Keep Algorithms Secret?
• Short windows to capitalize
– Upfront R&D costs
– Technology gains will erode
• Keeping the edge is crucial
– Secrecy
– Intellectual Property
Concerns of Keeping Algorithms Secret
• Consumer impact is unclear
• Data models are unclear
• Technology platforms
– A common approach can
spread rapidly
• Latency of spotting issues
Solving the Dilemma
• Regulation and legislation
• Industry standards
• Engineering ethics
• Standards
• Watchdogs
• Litigation
• Consumer activism
Each tool is valuable, but each tool is limited
Seeing Past the Dilemma
• Algorithms can provide ethical gains
• Algorithms present opportunity for all parties
– Disrupt problematic past practices
– Reduced cost for solutions
– Free customers to work on more interesting problems
– More insight and accountability
– Speed
– Efficiency
– Government accountability
– Better industry standards
THANK YOU!
35