Better Get While the Gettin's Good

On December 11, 2013, Reuters reported that the two private equity companies that took human resources management software firm Kronos Inc. private in 2007 are looking to sell the company. Hellman & Friedman LLC and JMI Equity are exploring a sale of Kronos, which could be valued at more than $4 billion. Interested purchasers are reported to include TPG, KKR and Bain.

The Reuters article states that Hellman & Friedman and JMI have taken advantage of Kronos' strong cash flow to draw more than $1.5 billion in dividends from Kronos, and so have already earned twice the $752.9 million they committed as equity when they agreed to acquire the company in 2007. In November 2013, the two companies had Kronos borrow to pay themselves a $490 million dividend.

Who should be interested in a potential sale of Kronos by Hellman & Friedman and JMI, other than the sellers, potential buyers and Kronos employees? The hundreds of employers that are customers of the Kronos talent acquisition and employee assessment services.

Why should those employers be interested? The risks to those employers from the ongoing systemic investigation by the Equal Employment Opportunity Commission (EEOC) of several Kronos customers, an investigation focused on whether the Kronos assessment services violate the Americans with Disabilities Act (ADA) by illegally screening out persons with disabilities.

What are EEOC systemic investigations? Systemic investigations involves pattern or practice, policy, and/or class cases where the alleged discrimination has a broad impact on an industry, profession, company, or geographic area. In connection with systemic investigations, the EEOC’s enforcement tools include issuing broad information requests and subpoenas on employers that are named as respondents in EEOC charges, particularly when the EEOC suspects systemic discrimination, and filing pattern or practice class lawsuits in federal court.

What are the risks to employers? Systemic investigations by the EEOC and class action claims by job applicants for damages and injunctive relief. For some employers, the potential class size can be measured in the millions of plaintiffs. Employers have primary liability under the ADA, but Kronos has indemnified many of its employer customers. If Kronos does not have the financial resources, however, the indemnification is illusory.

What is Kronos?

Kronos is a U.S.-based workforce management software and services company. According to the company, tens of thousands of organizations in more than 100 countries - including more than half of the Fortune 1000 - use Kronos.

In August 2006, Kronos acquired Unicru, Inc., a company specializing in software used to assess and hire hourly workers. At the time of the acquisition by Kronos, Unicru had as customers for its assessment (the Unicru assessment) more than 140 leading companies and brands, including SuperValu, Kroger, Toys "R" Us, Best Buy, CVS, Borders, Lowe's, Caribou Coffee, and Marquis Healthcare.

The Unicru assessment consists of a number of statements, to which an applicant must answer “strongly disagree,” “disagree,” “agree,” or “strongly agree.” It includes statements such as: “You have confidence in yourself”; "You try to sense what others are thinking and feeling”; “You always say whatever is on your mind”; and “It is easy for you to feel what others are feeling.”

The systemic investigation of Kronos assessment customers, including Kroger, arose from a charge filed with the EEOC more than six years ago by a Kroger job applicant.  The charge led to an investigation that has been ongoing for more than six years and has generated a number of district court and appellate court decisions as Kronos has unsuccessfully sought to avoid disclosing information about the Unicru assessment and its impact on persons protected by the ADA.

Cloning Employees and Institutionalizing Biased Hiring Practices

According to Kronos, the Unicru assessment is an artificial intelligence test that uses neural networks to “learn” the characteristics of a customer’s “best” employees.  As stated by Kronos’ Chief Scientist and the developer of the Unicru assessment, Dr. David Scarborough, in chillingly Orwellian terms, "[o]ur system allows you to clone your best, most reliable people."

First used for engineering and industrial applications during the mid-1980s, neural networks evolved from early artificial intelligence research. Modeled on the function of the human brain, a neural network attempts to imitate human reasoning. Large amounts of data are fed into the network, which looks for relationships and reaches conclusions.


"There are a couple of dangers," states Jai Shekhawat, CEO of Chicago-based Fieldglass Inc., which develops software for managing workers. "Is something a correlation--a predictor--or merely a coincidence? At best, [these methods] are complementary to human judgment, not a substitute for it."

Notwithstanding such dangers, Kronos customers like Kroger are substituting this “coincidence” for human judgment. Based on the prospective employee's answers on the application, the Unicru assessment categorizes the applicant as red, green or yellow. In most cases, red is usually an automatic discard, or, as Dr. Scarborough stated “[m]anagers are strongly discouraged from hiring first quartile (“red”) applicants …”

There is no evidence that the Unicru assessment determines whether an employer’s hiring practices are biased or discriminatory. For example, if the Unicru assessment had been utilized fifty years ago, many companies’ “best” employees would have the personality traits of white males – persons of color, women and those with disabilities need not have applied.

The Unicru assessment embeds and industrializes existing stigma, bias and discrimination in the hiring process. As stated by Cynthia Dwork and Deirdre K. Mulligan in a recent Stanford Law Review article:

While automated decisionmaking systems “may reduce the impact of biased individuals, they may also normalize the far more massive impacts of system-level biases and blind spots.” Rooting out biases and blind spots in big data depends on our ability to constrain, understand, and test the systems that use such data to shape information, experiences, and opportunities.

As a “blind” tool that “learns” from the employer, the Unicru assessment replicates the existing bias of the employer and applies it on a massive scale. All applicants have their test responses fed through a discriminatory filter that is the Unicru assessment (a filter that is biased both on its own and in conjunction with its “learned” behavior). 

Illegal Medical Examination

The ADA prohibits the use of pre-employment medical examinations. At the pre-offer stage, an employer is only entitled to ask about an applicant's ability to perform the essential functions of the job. The ADA's prohibition against pre-employment examinations seeks to ensure that the applicant's disability is not considered prior to the assessment of the applicant's qualifications.

EEOC guidance provides a seven-factor test for analyzing whether a test or procedure qualifies as a “medical examination,” including:

• whether the test is designed to reveal an impairment of physical or mental health such as those listed in the Diagnostic and Statistical Manual of Mental Disorders (“DSM”); and
• whether the test is interpreted by a health care professional.

According to the guidance, the presence of any one of the seven factors is enough to support a finding that the test is a medical examination and the Unicru assessment meets the two factors listed above. 

Since the Unicru assessment is based on the five-factor model (FFM) of personality it meets the first factor listed above. As set out in previous posts -  ADA, FFM and DSM and Employment Assessments are Designed to Reveal an Impairment - assessments based on the FFM are designed to reveal an impairment of mental health, such as those listed in the DSM.

As to the second factor, whether the test is interpreted by a health care professional, the individuals who developed the Unicru assessment are psychologists, most of whom are members of the APA. In developing the Assessments, the psychologists establish the rules by which the assessments are to be interpreted (i.e., how the responses to the questions are to be scored, including whether the applicant receives a green, yellow or red rating).

According to the APA Model Act for State Licensure of Psychologists, “[t]he practice of psychology includes … (a) psychological testing and the evaluation or assessment of personal characteristics, such as intelligence; personality; cognitive, physical, and/or emotional abilities; … [and] (f) provision of direct services to … groups for the purpose of enhancing … organizational effectiveness, using psychological principles, methods, and/or procedures … for making decisions about the individual, such as selection …”

EEOC guidance states that psychologists are among the “variety of health professionals [that] may provide documentation regarding psychiatric disabilities” for ADA purposes. Accordingly, the psychologists who developed the Unicru assessment are "health care providers" for purposes of the ADA.

The CVS Example

In July 2011, CVS and the Rhode Island Civil Liberties Union (ACLU) entered into a voluntary settlement addressing the ACLU’s complaint challenging CVS’s use of a pre-hire questionnaire that the ACLU claimed could have a discriminatory impact on people with certain mental impairments or disorders. 

The CVS questionnaire contained statements to which applicants were required to respond, including: “You change from happy to sad without any reason,” “You get angry more often than nervous,” “Your moods are steady from day to day,” and “There’s no use having close friends; they always let you down.”

Responding to a complaint filed by the ACLU, the Rhode Island Commission for Human Rights had issued a finding in February 2011 that there was "probable cause" to believe that the questionnaire used by CVS violated state anti-discrimination laws that bar employers from eliciting information that pertain to job applicants' mental or physical disabilities.

Although employers may legally ask questions designed to help determine an applicant’s personality or aptitude for a job, the ACLU’s complaint argued that questions found in the CVS pre-offer assessment “could have the effect of discriminating against applicants with certain mental impairments or disorders, and go beyond merely measuring general personality traits.” 

Pursuant to the settlement agreement, CVS agreed to permanently remove the questions at issue from its online application.

Systemic Risk to Employers

The success of workforce science companies in developing employment personality and assessment tests over the past twenty years has created "systemic risk" for their employer customers. If one employer has violated the law and subjected itself to significant liability as a consequence of its use of an assessment provided by a workforce science company, then all customers of that company are similarly at risk. Workforce science companies provide their services to thousands of employers, including many of the largest employers in the U.S. 

The lack of diversity in the psychological model underlying many of the personality tests offered by workforce science companies (the five-factor model of personality or Big Five) also means that if one workforce science company's personality tests that use the Big Five is found to be an illegal medical examination under the Americans with Disabilities Act (ADA), all workforce science companies that use the Big Five (and, more importantly, their customers) are similarly at risk. 

There are multiple risks to employers arising from the use of personality tests and workforce assessments, including: 

1. Claims under the ADA and the Rehabilitation Act of 1973 that the personality tests are illegal medical examinations or that they illegally screen out persons with mental illness (as set out above); 
2. Claims under the ADA and the Rehabilitation Act of 1973 that the employer fails to select and administer the assessment in the most effective manner to ensure that the assessment results accurately reflect the skills, aptitude or whatever other factor that the assessment purports to measure, rather than reflecting an applicant’s impairment; 
3. Claims that employers and workforce assessment companies fail to properly safeguard confidential medical information obtained from the personality tests and illegally use that confidential medical information in violation of the ADA; and
4. Claims under Title VII of the Civil Rights Act that the workforce analytics cause there to be a disparate impact on the hiring of blacks and Hispanics.

As to the potential size of the plaintiff classes for the claims listed above, they range from a percentage of all applicants (in the case of claims that the tests illegally screen out persons with mental illness and claims of disparate impact under Title VII) to all applicants over the past 12 months (in the case of claims that the personality test is an illegal medical examination) to all applicants, employees and ex-employees over a longer period of time (in the case of claims that employers and workforce assessment companies failed to safeguard confidential medical information).

For some employers, the potential class size can be measured in the millions of plaintiffs. Consistent with the 2011 Supreme Court decision in Wal-Mart Stores, Inc. v. Dukes, plaintiffs in a class action suit predicated on the use of personality tests and workforce analytics will be challenging a uniform, company-wide practice. The uniform use of testing by an employer demonstrates that "there are questions of law or fact common to the class," or commonality, as required by the rules governing class actions.

Illusory Indemnification?

A key element in continuing to use Kronos assessment services is Kronos' ability to indemnify its employer customers. As noted above, the success of workforce assessment companies in marketing personality tests and workforce analytics over the past twenty years has created "systemic risk" for its customers. If one employer has violated the law and subjected itself to significant liability as a consequence of its use of a solution provided by a workforce assessment company, then all customers of that workforce assessment company are similarly at risk.

Even assuming workforce assessment companies are willing to provide indemnification to all customers, those employers need to independently assess whether the workforce assessment companies and their insurers have adequate resources to indemnify all customers. 

As Kenexa, an employment assessment company, consistently noted in its annual 10-K risk factor disclosures prior to its December 2012 acquisition by IBM:

The failure of our solutions to comply with employment laws may require us to indemnify our customers, which may harm our business. Some of our customer contracts contain indemnification provisions that require us to indemnify our customers against claims of non-compliance with employment laws related to hiring. To the extent these claims are successful and exceed our insurance coverages, these obligations would have a negative impact on our cash flow, results of operation and financial condition.

Similarly, customers of Kronos might be concerned about Kronos' ability to fulfill its indemnification obligations. As noted above, Kronos' current owners have paid themselves significant dividends during their ownership tenure, including causing the company to borrow to pay a $490 million dividend earlier this year.

The current owners of Kronos are also delaying substantive interaction with the EEOC in connection with its systemic investigation of Kronos customers, including the more than five years of litigation over the EEOC's information requests, while at the same time looking to sell Kronos. It may be possible that Hellman & Friedman LLC and JMI Equity end up with more than $5 billion from a $752 million investment, while leaving the new owner with the contingent indemnification liabilities. Kronos, under the new owner, may not have sufficient resources to cover the indemnification claims of its employer customers.

* * * * *

"Better Get While the Gettin's Good," the title of this post, is a lyric from Credence Clearwater Revival's song Up Around the Bend. The song's first verse reads:

There's a place up ahead and I'm goin'
Just as fast as my feet can fly
Come away, come away if you're goin',
Leave the sinkin' ship behind.

The question is whether the owners of Kronos Inc. are trying to get while the gettin's good by selling the company and leaving that sinking ship behind?

What Gets Lost? Risks of Translating Psychological Models and Legal Requirements to Computer Code

The genesis for this posting is the article "Technologies of Compliance: Risk and Regulation in a Digital Age" authored by Kenneth A. Bamberger and found at 88 Texas L. Rev. 669 (2010). This posting takes portions of the article, modified to address the issue of job applicant assessments, and intersperses information on elements of workforce analytics to provide examples of the risks and challenges raised in the Bamberger article.

Workforce analytic systems are powerful tools, but they pose real perils. They force computer programmers to attempt to interpret psychological models, legal requirements and managerial logic; they mask the uncertainty of the very hazards with which lawmakers and regulators are concerned; they skew decisionmaking through an “automation bias” as a substitute for sound judgment; and their lack of transparency thwarts oversight and accountability.

Lost In Translation

The hiring assessment functionality of workforce analytics contains three divergent logic systems, legal, psychological and managerial. The legal logic system derives, in part, from the Americans with Disabilities Act (ADA) and its accompanying regulations and related caselaw. The psychological logic system derives primarily from the five-factor model of personality, or Big Five, as it has evolved over the past 20-25 years. The managerial logic derives from the implementation of the human resource function of the employer. Technology in the form of workforce analytics then attempts to tie these three logic systems together in order to create an automated assessment program that attempts to determine applicant "suitability" or "fit."

Information technology is not value-neutral, but embodies bias inherent in both its social and organizational context and its form. It is not infinitely plastic, but, through its systematization, trends towards inflexibility. It is not merely a transparent tool of intentional organizational control, but in turn shapes organizational definitions, perceptions, and decision structures. In addition to controlling the primary risks it seeks to address, then, it can raise—and then mask—different sorts of risk in its implementation.

For example, many workforce analytic companies utilize the Big Five model in creating their personality assessments. As its name implies, the Big Five looks at five traits: openness, conscientiousness, extraversion, agreeableness, and neuroticism, with each trait conceptualized on an axis from low to high (e.g., low neuroticism, high neuroticism). The Big Five, operating under various names, existed for a number of decades prior to its "rebirth" in the early 1990s, where it was embraced by organizational psychologists.

Since the late 1990s workforce analytics companies like Unicru (now owned by Kronos) have adopted the Big Five for use in their job applicant assessment program. The workforce analytic companies have created "model" psychological profiles and tested applicants against those profiles. In general, applicants receive either green, yellow or red scores on the basis of a 50/25/25 cutoff. Applicants scoring red are generally not interviewed, let alone hired.

The use of technology systems to hardwire workforce analytics raises a number of fundamental issues regarding the translation of legal mandates, psychological models and business practices into computer code and the resulting distortions. These translation distortions arise from the organizational and social context in which translation occurs; choices “embody biases that exist independently, and usually prior to the creation of the system.” And they arise as well from the nature of the technology itself “and the attempt to make human constructs amenable to computers.”

These distortions are compounded when psychological models, legal standards and managerial processes are turned over to programmers for translation into predictive algorithms and computer code. These programmers may know nothing of the psychological models, legal standards and management processes. Some are employees of separate IT divisions within firms; many are employees of third-party systems vendors. Wherever they work, their translation efforts are colored by their own disciplinary assumptions, the technical constraints of requirements engineering, and limits arising from the cost and capacity of computing.

Managerial processes may be poor vehicles for capturing nuance in legal policy and psychological models, especially in a context like employment discrimination where regulators have eschewed rules for standards and where the interpretation of those standards by regulators and psychological professionals may change over time. For example, the ADA prohibits pre-employment medical examinations and psychological tests used by workforce analytic companies may be considered medical examinations (please see ADA, FFM and DSM). Employers and workforce analytic companies have interpreted the medical examination requirement as prohibiting the use of tests that are designed to diagnose mental illnesses. 

This interpretation creates two significant risks for employers and workforce analytic companies. First, the legal standard does not speak to "tests designed to diagnose mental illnesses;" rather, it is "whether the test is designed to reveal an impairment of physical or mental health such as those listed in the Diagnostic and Statistical Manual of Mental Disorders." "Designed to reveal" is semantically and substantively different from "designed to diagnose" and, as set out in Employment Tests are Designed to Reveal an Impairment, Big Five-based tests are designed to reveal impairments by their screening out process. As depicted in the graphic, tests designed to diagnose are a subset of the overall category of tests designed to reveal an impairment. Using the "designed to diagnose" category as the proxy for medical examinations puts employers and workforce analytic companies at significant risk of violating the ADA medical examination prohibition and the confidential medical information safeguards under the ADA. It may also result in other claims against the workforce analytic companies by job applicants, employers and insurers. The mistaken use of the "designed to diagnose" category as a proxy for medical examinations could be considered a design defect in the product liability arena or as negligent in a tort claim..

The second significant risk for employers and workforce analytic companies arises from their failure to account for the evolution of the Big Five model from non-clinical model to clinical model.  In her seminal review of the personality disorder literature published in 2007, Dr. Lee Anna Clark stated that “the five-factor model of personality is widely accepted as representing the higher-order structure of both normal and abnormal personality traits.” A clear sign of this evolution comes with the publication of the most current volume of the Diagnostic and Statistical Manual for Mental Disorders (DSM-5), published in May 2013, where the model used to diagnose many personality disorders is based on the Big Five. 

Consequently, even if the standard for defining a medical examination was focused solely on the use of a test that diagnosed a mental illness, the five-factor model has now evolved into a diagnostic tool used by the psychiatric community to define mental impairments, including personality disorders, of the kind set out in the DSM-5. The failure of employers and workforce analytic companies to account for the evolutionary development of the five-factor model puts them at significant risk due to their belief that the five-factor model is not a diagnostic tool - a belief that time and scientific advances have now overturned. 

Automation Bias

While computer code and predictive-analytic methods might be accessible to programmers, they remain opaque to users —for whom, often, only the outcomes remain visible. In the case of job applicants, even this information (assessment outcome) is not visible to them - results are not disclosed by employers or workforce analytic companies. Programmers “code[] layer after layer of policies and other types of rules” that managers and directors cannot hope to understand or unwind.

Human judgment is subject to an automation bias, which fosters a tendency to “disregard or not search for contradictory information insight of a computer-generated solution that is accepted as correct.” Such bias has been found to be most pronounced when computer technology fails to flag a problem.

In a recent study from the medical context, researchers compared the diagnostic accuracy of two groups of experienced mammogram readers (radiologists, radiographers, and breast clinicians)—one aided by a Computer Aided Detection (CAD) program and the other lacking access to the technology. The study revealed that the first group was almost twice as likely to miss signs of cancer if the CAD did not flag the concerning presentation than the second group that did not rely on the program.

Automation bias may be found in the algorithms created and used by workforce analytic companies to provide "insights" to their employer customers. For example, Kenexa, an IBM company, has determined that distance from work, commute time and frequency of household moves all have a correlation with attrition in call-center and fast-food jobs. Applicants who live more than five miles from work, have a lengthy commute or have moved more frequently are scored down by the algorithms, making them less desirable candidates.

Painting with the broad brush of distance from work, commute time and moving frequency may result in well-qualified applicants being excluded. The Kenexa insights are generalized correlations; they say nothing about any particular applicant.

What are the risks of employers slavishly adhering to the results of the algorithm? Part of the answer comes from identifying groups of people who have longer commutes and move more frequently than others, lower-income persons who, according to the U.S. Census, are disproportionately African-American and Hispanic.

Through the application of these “insights,” many low-income persons are electronically redlined, meaning employers will pass over qualified applicants because they live (or don’t live) in certain areas, or because they have moved. The reasons for moving do not matter — whether it is to find a better school for their children, to escape domestic violence, the elimination of mass transit in their community, or as a consequence of job loss due to a company shutdown (please see From What Distance is Discrimination Acceptable?)

An employer who does not look past the simple results of the assessment algorithms not only harms itself by failing to consider well-qualified employees, the employer puts itself at risk for employment discrimination claims by classes of persons (e.g., African-American, Hispanic) protected by federal and state employment laws.

Institutionalized (Mis)Understanding

Institutionalization of workforce management practices might permit evolutionary improvements in existing measurements, but it masks areas where risk types are ignored or analysis is insufficient and where more revolutionary, paradigm-shifting advances might be warranted.

These understandings (or misunderstandings) can be institutionalized across the field of workforce analytics. As workforce analytic practices are disseminated through the industry by professional groups, workforce analytic practitioners, management scholars, and third-party technology vendors and consultants, they standardize an approach that other firms adopt, seeking legitimacy.

Workforce analytic systems, designed in part to mitigate risks, have now become sources of risk themselves. They create the perception of stability through probabilistic reasoning and the experience of accuracy, reliability, and comprehensiveness through automation and presentation. But in so doing, technology systems draw organizational attention away from uncertainty and partiality. They can embed, and then justify, self-interested assumptions and hypotheses.

Moreover, they shroud opacity—and the challenges for oversight that opacity presents—in the guise of legitimacy, providing the allure of shortcuts and safe harbors for actors both challenged by resource constraints and desperate for acceptable means to demonstrate compliance with legal mandates and market expectations.

The technical language of workforce analytic systems obscures the accountability of the decisions they channel. Programming and mathematical idiom can shield layers of embedded assumptions from high-level firm decisionmakers charged with meaningful oversight and can mask important concerns with a veneer of transparency. This problem is compounded in the case of regulators outside the firm, who frequently lack the resources or vantage to peer inside buried decision processes and must instead rely on the resulting conclusions about risks and safeguards offered them by the parties they regulate.

Risks of a Technological Monoculture

Technology-based workforce analytic systems proliferate, in part, because policy makers have rejected rule-based mandates in favor of regulatory principles that rely on the exercise of context-specific judgment by regulated entities for their implementation . Yet workforce analytic technology can turn each of these regulatory choices on its head. The need to translate psychological, legal and managerial logic into a fourth distinct logic of computer code and quantitative analytics creates the possibility that legal choices will be skewed by the biases inherent in that process.

Such biases introduce several risks: that choices will be shaped both by assumptions divorced from sound management and incentives unrelated to public ends (e.g., hiring discrimination leading to larger income support payments - SSDI, SSI); that the rule-bound nature of code will substitute one-time technological “fixes” for ongoing human oversight and assessment (e.g., failure to recognize the evolution of the Big Five becoming a diagnostic tool); and that the standardization of risk-assessment approaches will eliminate variety—and therefore robustness in workforce analytic efforts, developing systemic risks of which individual actors may not be aware.

Systemic risks have developed because there is a technological "monoculture" in the workforce analytic industry. The problems are analogous to those of the biological domain. A deeply entrenched standard prevents the introduction of technological ideas that deviate too far for accepted norms. This means that the industry may languish with inefficient or non-optimal solutions to problems, even though efficient, optimal, and technically feasible solutions exist. The technical feasibility of these superior solutions is not important; they are excluded because they are incompatible with the status quo technology.

In a diverse population, any particular weakness or vulnerability is likely confined to only a small segment of the whole population, making population-wide catastrophes extremely unlikely. In a homogeneous population, any vulnerability is manifested by everyone, creating a risk of total extinction. In the case of workforce analytics, one successful challenge the Big Five-based model either being an illegal medical examination or screening out persons with disabilities introduces systemic risk to all customers of that workforce analytics company - one loss will lead to multiple challenges, along the lines of the asbestos litigation (please see The Next Asbestos? The Next FLSA?).Systemic risk is not limited to the ecosystem of the workforce analytic company being challenged, but extends to all companies that market or utilize Big Five-based assessments.

The potential costs are enormous. If the assessment is an illegal medical examination, then each applicant has a claim based on the use of an illegal medical examination. Some employers use the assessments to screen millions of applicants each year; each applicant is a potential plaintiff. Further, if the test is a medical examination, then each applicant has a claim for the misuse of confidential medical information (if the test is a medical examination, the applicant responses are confidential medical information). Not only does that lead to claims based on privacy violations, but all systems, solutions and databases that incorporate the information obtained from the assessments will need to be "sanitized." In a very real sense, the data may be the virus and the costs of "cleansing" those systems may well dwarf the very significant damages payable to applicants (please see When the First Domino Falls: Consequences to Employers of Embracing Workforce Assessment Solutions).

Kroger and Kronos: Chaos and Disorder

In classic Greek mythology, Kronos (also known as Cronus) was the leader of the first generation of Titans. Cronus was usually depicted with a sickle or scythe and the Greeks considered Cronus a cruel and tempestuous force of chaos and disorder.

Kronos, the company, is a U.S.-based workforce management software and services company. According to the company, tens of thousands of organizations in more than 100 countries - including more than half of the Fortune 1000 - use Kronos to control labor costs, minimize compliance risk, and improve workforce productivity.

In August 2006, Kronos acquired Unicru, Inc., a company specializing in software used to assess and hire hourly workers. At the time of the acquisition by Kronos, Unicru had as customers more than 140 leading companies and brands, including SuperValu, Kroger, Toys "R" Us, Best Buy, CVS, Borders, Lowe's, Caribou Coffee, and Marquis Healthcare.

The Unicru assessment consists of a number of statements, to which an applicant must answer “strongly disagree,” “disagree,” “agree,” or “strongly agree.” It includes statements such as the following: “You have confidence in yourself”; You are always cheerful”; “You try to sense what others are thinking and feeling”; “You always say whatever is on your mind”; and “It is easy for you to feel what others are feeling.”

Kroger, Kronos and the Unicru assessment are being investigated by the Equal Employment Opportunity Commission (EEOC) for compliance with labor and employment laws, including the Americans with Disabilities Act (ADA). The investigation has been ongoing for more than five years and has generated a number of district court and appellate court decisions as Kronos has sought to avoid disclosing information about the Unicru assessment and its impact on persons protected by the ADA.

Cloning Employees and Institutionalizing Biased Hiring Practices

According to Kronos, the Unicru assessment is an artificial intelligence test that uses neural networks to “learn” the characteristics of a customer’s “best” employees.  As stated by Kronos’ Chief Scientist and the developer of the Unicru assessment, Dr. David Scarborough, in chillingly Orwellian terms, "[o]ur system allows you to clone your best, most reliable people."

First used for engineering and industrial applications during the mid-1980s, neural networks evolved from early artificial intelligence research. Modeled on the function of the human brain, a neural network attempts to imitate human reasoning. Large amounts of data are fed into the network, which looks for relationships and reaches conclusions.

"There are a couple of dangers," states Jai Shekhawat, CEO of Chicago-based Fieldglass Inc., which develops software for managing workers. "Is something a correlation--a predictor--or merely a coincidence? At best, [these methods] are complementary to human judgment, not a substitute for it."

Notwithstanding such dangers, Kronos customers like Kroger are substituting this “coincidence” for human judgment. Based on the prospective employee's answers on the application, the Unicru assessment categorizes the applicant as red, green or yellow. In most cases, red is usually an automatic discard, or, as Dr. Scarborough stated “[m]anagers are strongly discouraged from hiring first quartile (“red”) applicants …”

There is no evidence that the Unicru assessment determines whether an employer’s hiring practices are biased or discriminatory. For example, if the Unicru assessment had been utilized fifty years ago, many companies’ “best” employees would have the personality traits of white males – persons of color, women and those with disabilities need not have applied.

The Unicru assessment embeds and industrializes existing stigma, bias and discrimination in the hiring process. As stated by Cynthia Dwork and Deirdre K. Mulligan in a recent Stanford Law Review article:

While automated decisionmaking systems “may reduce the impact of biased individuals, they may also normalize the far more massive impacts of system-level biases and blind spots.” Rooting out biases and blind spots in big data depends on our ability to constrain, understand, and test the systems that use such data to shape information, experiences, and opportunities.

As a “blind” tool that “learns” from the employer, the Unicru assessment replicates the existing bias of the employer and applies it on a massive scale. All applicants have their test responses fed through a discriminatory filter that is the Unicru assessment (a filter that is biased both on its own and in conjunction with its “learned” behavior). Hiring decisions are being made by Kroger and other Kronos customers based on this deeply flawed process.

Illegal Medical Examination

The ADA prohibits the use of pre-employment medical examinations. At the pre-offer stage, an employer, like Kroger, is only entitled to ask about an applicant's ability to perform the essential functions of the job. The ADA's prohibition against pre-employment examinations seeks to ensure that the applicant's disability is not considered prior to the assessment of the applicant's qualifications.

EEOC guidance provides a seven-factor test for analyzing whether a test or procedure qualifies as a “medical examination,” including:

• whether the test is designed to reveal an impairment of physical or mental health such as those listed in the Diagnostic and Statistical Manual of Mental Disorders (“DSM”); and
• whether the test is interpreted by a health care professional.

According to the guidance, the presence of any one of the seven factors is enough to support a finding that the test is a medical examination and the Unicru assessment meets the two factors listed above. 

Since the Unicru assessment is based on the five-factor model (FFM) of personality it meets the first factor listed above. As set out in previous posts -  ADA, FFM and DSM and Employment Assessments are Designed to Reveal an Impairment - assessments based on the FFM are designed to reveal an impairment of mental health, such as those listed in the DSM.

As to the second factor, whether the test is interpreted by a health care professional, the individuals who developed the Unicru assessment are psychologists, most of whom are members of the APA. In developing the Assessments, the psychologists establish the rules by which the assessments are to be interpreted (i.e., how the responses to the questions are to be scored, including whether the applicant receives a green, yellow or red rating).

According to the APA Model Act for State Licensure of Psychologists, “[t]he practice of psychology includes … (a) psychological testing and the evaluation or assessment of personal characteristics, such as intelligence; personality; cognitive, physical, and/or emotional abilities; … [and] (f) provision of direct services to … groups for the purpose of enhancing … organizational effectiveness, using psychological principles, methods, and/or procedures … for making decisions about the individual, such as selection …”

EEOC guidance states that psychologists are among the “variety of health professionals [that] may provide documentation regarding psychiatric disabilities” for ADA purposes. Accordingly, the psychologists who developed the Unicru assessment are "health care providers" for purposes of the ADA.

(Not) Walking the Talk

Kroger's Policy on Business Ethics states:

We are committed to a policy of equal opportunity for all associates without regard to race, color, religion, gender, national origin, age, disability or sexual orientation.

Kroger has six core values: Honesty; Integrity, Respect; Diversity; Safety; and, Inclusion. In a June 13, 2011 press release announcing the appointment of Kroger's chief diversity officer, Kroger's CEO is quoted as saying:

“Diversity is a core value at Kroger. We take our commitment to diversity seriously, both because it is right and because it makes us better at our business. When our decision-making is inclusive and reflects the diversity of our customers, we make better decisions.”

For job applicants with mental illness, there is no respect, no inclusion, no diversity, no honesty and no integrity. In the more than twenty years since passage of the ADA, there has been little positive movement in de-stigmatizing mental illness in the workplace (please see Mental Illness and Issues of Employment). People with mental illnesses identify employment discrimination as one of their most frequent stigma experiences. In its use of the Unicru assessment, Kroger, wittingly or not, continues the disturbing pattern of employment discrimination against citizens of the United States with mental illness.

Failing Customers and Shareowners

Kroger's Policy on Business Ethics also states:

As a retailer providing millions of Americans with their daily food and as a publicly owned company, The Kroger Co. has a special obligation to comply with the law and deal ethically with customers, suppliers, associates, and shareowners. 

Psychiatric medications are among the most widely prescribed and biggest-selling class of drugs in the U.S. In 2011, Americans spent $18.2 billion on antipsychotics to treat depression, bipolar disorder and schizophrenia, $11.0 billion on antidepressants and $7.9 billion on treatment for ADHD, according to IMS Health, which tracks prescription-drug sales. These three categories of prescription drug sales accounted for approximately 11.6% of all prescription drug sales in the U.S. for 2011

Kroger is the fifth-largest pharmacy operator in the United States, operating retail pharmacies in over 1,948 stores. During fiscal 2011, Kroger pharmacists filled over 146 million prescriptions at a retail value of approximately $7.3 billion. Assuming 11.6% of Kroger prescription drug sales were for antipsychotics, antidepressants and ADHD medications, prescription drugs for persons with mental illness accounted for approximately $847 million of Kroger prescription drug sales in 2011, some two-thirds of the amount of Kroger’s operating profit for that year.

Persons who have their prescriptions filled at Kroger, their family members and other loved ones also shop at Kroger for other products and services. Those persons, their family members and other loved ones provide a material percentage of Kroger’s overall revenue each year. How does Kroger repay this customer loyalty? By utilizing an unlawful pre-employment assessment to eliminate from consideration for employment persons with mental illness.

Why should persons with mental illness, their family members and other loved ones continue to shop at Kroger? Good question. 

Kroger's continuing use of the Unicru assessments calls into question Kroger's "special obligation to comply with the law and deal ethically" with its shareowners, As previously noted, Kroger and Kronos have been engaged in litigation with the EEOC for more than five years over legality of the Unicru assessment. To be precise, the five years of litigation have primarily addressed the unwillingness of Kroger and Kronos to provide information requested by the EEOC in order to conduct its investigation into the Unicru assessment. Two appellate courts, the latest in September 2012, have ruled decisively in favor of the EEOC and its right to investigate a broad set of nationwide and historical data from Kroger and Kronos.

At anytime over the past five years, Kroger could have ceased using the Unicru assessment, if only as a risk mitigation strategy for its shareowners. As noted in the Challenges to Pre-Employment Assessments posting, in July 2011, CVS and the Rhode Island Civil Liberties Union (ACLU) entered into a voluntary settlement addressing the ACLU’s complaint challenging CVS’s use of a pre-hire questionnaire that the ACLU claimed could have a discriminatory impact on people with certain mental impairments or disorders. Pursuant to the settlement agreement, CVS agreed to permanently remove the questions at issue from its online application.

Each day Kroger continues to use the Unicru assessment, there are thousands more potential plaintiffs with claims against Kroger. By now, the aggregate number of potential plaintiffs numbers in the millions - with each job applicant over the past 5+ years having a number of claims against Kroger.

Under the ADA, Kroger may use a third party like Kronos to undertake the assessment of Kroger job applicants. The use of a third party, however, does not insulate Kroger from any claims arising from the assessment usage. Under the ADA, Kroger is responsible (and liable) for any failures on the part of Kronos and the Unicru assessment to comply with the provisions of the ADA.

Any comfort Kroger or its shareowners take in the indemnification provided by Kronos should be tempered by the recognition that such indemnification may prove illusory. Kronos and its insurers may not have the capital necessary to indemnify Kroger and its shareowners for all claims arising from Kroger's continuing use of the Unicru assessment. Please see Damages and Indemnification Challenges for Employers.