Big Data and Employment Discrimination Aaron Konopasky, J.D., Ph.D.
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Transcript of Big Data and Employment Discrimination Aaron Konopasky, J.D., Ph.D.
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A PuzzleAs an employment lawyer I am
interested in some of the ethical issues raised by Big Data
Although the background reading provided on the conference website is exceptional, I was surprised to find that most of it seemed relatively unconcerning (in my role as an employment discrimination lawyer)
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ExplanationMost people here are interested
in potentially negative effects of Big Data research on study participants, and/or
Believe that the negative effects of Big Data are best avoided through greater privacy protections, but...
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I Don’t Care About Study Participants or Privacy...in my role as an employment
discrimination lawyer◦(This is not quite true. If a research
participant is also a job candidate or employee, then perhaps I might be interested in the possibility that his or her personally identifiable data is obtained by the employer, contrary to the wishes of the subject. But I don’t have anything to add to that conversation, so I will ignore it.)
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What I am Concerned AboutThat Big Data researchers will create
products (e.g., algorithms that rate or categorize job applicants) that unfairly exclude people with certain protected characteristics from employment
Query: Should the possibility that research findings will be misused affect how or whether the research should be done?
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What I Will DiscussFederal employment
antidiscrimination laws◦Goals◦How they are designed to
accomplish those goalsHow Big Data could threaten
those goalsWhether/the extent to which
current law protects us
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EEO Laws
There are certain characteristics that generally shouldn’t get in the way of a job, but often do – “protected characteristics”
Federal EEO laws are meant to take these characteristics out of the equation
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Protected Characteristics
Race, color, national origin, sex (including pregnancy), religion (including atheism)◦ Title VII of the Civil Rights Act of 1964 (“Title VII”)
◦ Equal Pay Act (“EPA”) (sex only)
Medical condition/disability ◦ Americans with Disabilities Act (“ADA”)
Being “too old” (minimum 40)◦ Age Discrimination in Employment Act of 1967 (“ADEA”)
Genetic information (including family medical history)◦ Genetic Information Nondiscrimination Act of 2008
(“GINA”)
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Protection #1: Disparate Treatment
Adverse actions cannot be motivated by protected characteristics◦E.g., terminating someone because of
a disability, or refusing to hire someone based on race
◦Severe & pervasive harassment based on protected characteristics is also prohibited
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Protection #2: Disparate Impact
A policy or practice that disadvantages people with a certain protected characteristic, as a group, is prohibited unless it can be justified from a business standpoint
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Protection #3: Reasonable Accommodation
Employers may be required to make certain accommodations for people who need them because of a disability, or for religious reasons◦E.g., a permanent shift assignment for
someone who needs to work around a treatment schedule, or an exception to the dress code for someone who wears a hijab for religious reasons
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Protection #4: Privacy Access to genetic and medical
information is restricted Information that the employer
does have must be kept confidential
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A Related Law: Fair Credit Reporting Act (FCRA)
Employer needs written permission to purchase background reports (including credit and criminal history reports)◦ Only if purchased from a background
reporting company
Must promise to not use the information in violation of EEO laws
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Disparate Treatment? Under current law, some problematic
uses of Big Data would constitute disparate treatment, e.g.--◦Employer uses algorithm that predicts health
status in order to screen out people with disabilities
◦Employer uses an algorithm that is known to use protected characteristics as predictors
But what if --◦Neither the employer nor the programmer
knows that the product takes a protected characteristic into account, or
◦The product disadvantages a protected group by using proxies for protected status?
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Disparate Impact? If an Big Data product
disproportionately disadvantages a protected group, it is illegal unless it can be justified from a business point of view
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Justification
There may be reason to questions whether some troubling uses of Big Data could be justified◦Products that measure the wrong
thing Repurposed research Stereotypes and assumptions
◦Products that measure similarity to the status quo Actual success may be partly a result of
discrimination
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StrategiesSuppress or forego researchAttach strong privacy rights to all
informationKeep research results a privateCreate even more rigorous
standards for justifying employment practices
... ?
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Aaron Konopasky, J.D., Ph.D.Senior Attorney-Advisor ADA/GINA Policy DivisionOffice of Legal CounselEqual Employment Opportunity Commission131 M Street NEWashington, DC 20507
Phone: (202) 663-4127email: [email protected]