EEOC's Next Step in Preserving Values

The recent White House report, “Big Data: Seizing Opportunities, Preserving Values," found that, "while big data can be used for great social good, it can also be used in ways that perpetrate social harms or render outcomes that have inequitable impacts, even when discrimination is not intended." The fact sheet accompanying the White House report warns:

As more decisions about our commercial and personal lives are determined by algorithms and automated processes, we must pay careful attention that big data does not systematically disadvantage certain groups, whether inadvertently or intentionally. We must prevent new modes of discrimination that some uses of big data may enable, particularly with regard to longstanding civil rights protections in housing, employment, and credit.

In order to address the potential for big data analytics to systematically disadvantage certain groups, the White House report contains the following policy recommendation:

The federal government’s lead civil rights and consumer protection agencies, including the Department of Justice, the Federal Trade Commission, the Consumer Financial Protection Bureau, and the Equal Employment Opportunity Commission, should expand their technical expertise to be able to identify practices and outcomes facilitated by big data analytics that have a discriminatory impact on protected classes, and develop a plan for investigating and resolving violations of law in such cases. In assessing the potential concerns to address, the agencies may consider the classes of data, contexts of collection, and segments of the population that warrant particular attention, including for example genomic information or information about people with disabilities. 

Examples of Discriminatory Big Data Practices and Outcomes

Examples of practices and outcomes facilitated by big data analytics that could have a discriminatory impact on protected classes include:

• Use of location-based data that discriminates against lower-income persons, who are disproportionately Black, Hispanic, women and people with disabilities. Please see  From What Distance is Discrimination Acceptable?

• Use of pre-employment personality tests that discriminate against people with mental disabilities. Please see What Are The Issues, ADA, FFM and DSM, and Employment Assessments Are Designed to Reveal an Impairment.

• Mental illness is no respecter of age, gender, geography, income, occupation, military status, race, religion or sexual orientation.  Please see Tests Discriminate Against Returning Veterans, Tests Discriminate Against New and Expectant Mothers and Employment Tests Discriminate Against LGBTs.

EEOC's Next Step?

The White House report recommends that the EEOC, as one of the federal government's lead civil rights agencies, expand its technical expertise to be able to identify practices and outcomes facilitated by big data analytics that have a discriminatory impact on protected classes. The EEOC's next step may be to call on some of the same resources used by the White House review group led by John Podesta at the three workshops held during the 90-day review period leading to the issuance of the White House report:

• Big Data Privacy: Advancing the State of the Art in Technology and Practice
• Organized and co-hosted by the MIT Big Data Initiative at CSAIL and the MIT Information Policy Project 
• The Social, Cultural & Ethical Dimensions of “Big Data”
• Organized and co-hosted by Data & Society Research Institute and the NYU Information Law Institute
• Big Data: Values and Governance
• Organized and co-hosted by the UC Berkeley School of Information and the Berkeley Center for Law and Technology

The suggestion is that some of the individuals and organizations that co-hosted, presented and supported those the three workshops be persuaded to take their shows on the road, assisting the EEOC and the other federal civil rights agencies (Department of Justice, Federal Trade Commission and Consumer Financial Protection Bureau)  in understanding and preventing new modes of discrimination that some uses of big data may enable, particularly with regard to housing, employment, and credit.