Tag Archives: Epstein Becker & Green

NYC Job Postings Must Include Salary Ranges Effective May 15, 2022

NYC employers will soon be required to include a minimum and maximum salary on all job postings for positions performed within the City. As we previously reported, the City Council passed Int. 1208-B (Law) on December 15, 2021, and due to new NYC mayor Eric Adam’s inaction within the 30-day veto period, it became a law as of January 15, 2022. Beginning May 15, 2022, the Law requires employers with four or more employees to include a “good faith” minimum and maximum salary range on for all advertised NYC job, promotion and transfer opportunities. Additionally, the Law makes the failure to include salary range an unlawful discriminatory practice under the City’s Human Rights Law.

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Video: Biden Touts Employer-Mandated Vaccines, Booster Shot Questions, and EEO-1 Deadline Delayed – Employment Law This Week

As featured in #WorkforceWednesday:  This week, we look at the renewed focus on mandatory vaccination policies and how those policies may need to shift in light of COVID-19 booster shots.

President Biden Calls on Employers to Mandate Vaccines

Shortly after the U.S. Food and Drug Administration granted full approval of the Pfizer vaccine for those 16 and older, President Biden encouraged private employers to “step up” their vaccination requirements.

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AI-Based Compensation Management and Bias: Can AI Close the Pay Gap?

A critical component of a successful employer-employee relationship is the employer’s fair and equitable treatment of employees, often embodied in the employer’s employee engagement, retention, and compensation practices.  When it comes to compensation, U.S. employers must comply with federal and applicable state equal pay laws that prohibit discriminatory pay practices, and a myriad of state and local laws banning inquiries into, or the use of, prior salary history in setting pay.  Yet, compensation bias and discrimination still exist and continue to be the subject of government investigations, audits, and litigation.

With the growing use of artificial intelligence (AI) tools in every aspect of our lives, it is not surprising that companies are increasingly deploying AI and machine learning algorithms in various human resources functions, including compensation management and decision-making, as well as in the prediction of future employee performance.  Many argue that AI-based compensation tools can be used to close pay gaps and end discriminatory compensation practices.   The question arises, however, as to whether these tools can provide employers with a reliable method of providing objective, fair and precise compensation structures for their workforce, or whether they could intentionally (or unintentionally) cause an employer to violate applicable law and perpetuate bias in compensation structures.

Consider the following scenario:

A professional services firm has a large percentage of its employees working remotely, consequently, supervisors do not believe they have a good understanding of the contributions each employee makes.  So the firm collects metrics that are intended to reflect the value of each employee’s contribution to the company.  Because many metrics are subjective and hard to measure, the firm uses proxy metrics such as time spent in training, the type of training, and “electronic presence,” which is a measurement of time each employee spends electronically active working at the computer.  The firm uses an algorithm that is trained on all the data collected for all workers, and that algorithm makes a compensation recommendation based on its analyses of the collected data points and its predictions of future performance.  The employee’s supervisor makes the ultimate compensation decision, informed by the algorithm’s recommendation as well as qualitative and subjective assessments of the employee’s contributions (such as quality of work product, timely completion of projects, responsiveness, enhancement of skills, innovation).  The firm also collects market data to reflect, for each function at the company, the going market rate of pay as well as trends in compensation for certain skill sets, and uses the algorithm to assist supervisors in making salary recommendations for new hires and for purposes of promotions.  The supervisors are increasingly relying on the algorithms, especially when they do not have time to review each employee or candidate’s file completely.  The company believes the system is fair, but hasn’t done any special testing to identify any particular biases.  The question arises: to what legal risks, if any, is the employer exposed?

In this scenario, the AI-based compensation tool is being used for multiple purposes, from setting pay for new hires, to determining promotions, and to assessing remote worker performance.  Despite these well-intended uses, there are potential legal risks depending on the nature and source of the data used to train the algorithm.

Datasets used to train the algorithms may be comprised of an employer’s existing internal data, data from external sources, or a combination of both.   Employers should evaluate the quality of the initial data collected, and monitor any evolution of the data, for discriminatory factors.  These datasets may include employee data for particular positions requiring a certain educational, skill or experience level with varying compensation levels.  The appropriate grouping of employees performing the same job functions or job types is also critical to the assessment. AI tools should be carefully calibrated to compare the proper categories of employees. Any errors in these datasets could skew the results produced by the AI tool in a manner that could adversely affect the employer’s compensation practices.

In general, with these datasets, we must consider whether use of the AI tool can lead to compensation decisions that have a disparate impact on employees.  Further, could use of the AI tool potentially violate applicable laws that prohibit inquiries into prior salary histories?  Should the results from these AI tools be used by employers to make compensation decisions without additional input from supervisors?

These are among the questions that we’ll explore in our upcoming Labor & Employment-Recruiting and Compensation workshop.

To learn more about the legal risks of and solutions to bias in AI, please join us at Epstein Becker Green’s virtual briefing on Bias in Artificial Intelligence: Legal Risks and Solutions on March 23 from 1:00 – 4:00 p.m. (ET). To register, please click here.

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The European Data Protection Board Issues Guidance on Cross-Border Data Transfers

On November 11, 2020, the European Data Protection Board (EDPB) issued eagerly awaited guidance for complying with the requirements of the General Data Protection Regulation (GDPR) for protecting the privacy rights of individuals in their personal data subject to potential transfer from the European Union (EU) to the United States and other countries. The guidance comes in the wake of the uncertainly following the Court of Justice’s July 16, 2020 decision in Schrems II invalidating the EU-US Privacy Shield and upholding the use of standard contractual clauses as a permissible vehicle to transfer personal data to countries outside of the European Union provided there are “effective mechanisms” in place to ensure a level of protection for the data that is “essentially equivalent” to that existing within the European Union. The Court recognized that additional safeguards may be needed to provide an adequate level of protection because the standard contractual clauses are between private parties, and do not bind governmental authorities.

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A Reflection on RBG’s Impact and Legacy

“My mother told me to be a lady. And for her, that meant be your own person, be independent.” – Ruth Bader Ginsburg

A couple days after Ruth Bader Ginsburg passed away, my eight year old daughter asked me, when I was her age, what I wanted to be when I grew up. I paused and swallowed hard. I had wanted to be a doctor, but despite how well I performed in school, the more conservative environment I grew up in did not support such dreams because it was “not something that moms did”.

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Deadline Looms for Responding to DEA’s Proposed Aggregate Production Quotas for 2021

On Tuesday, September 1, 2020, the Drug Enforcement Agency (“DEA”) proposed 2021 aggregate production quotas (APQs) for controlled substances in schedules I and II of the Controlled Substances Act (“CSA”) and an Assessment of Annual Needs (“AAN”) for the List I Chemicals pseudoephedrine, ephedrine, and phenylpropanolamine. This marks the second year that DEA has issued APQs pursuant to Congress’s changes to the CSA via the SUPPORT Act.  After assessing the diversion rates for the five covered controlled substances, DEA reduced the quotas for four: oxycodone, hydrocodone, hydromorphone and fentanyl.

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Australia’s High Court Rules on How to Count Personal Leave Entitlement Under the Fair Work Act

On August 13, 2020, 11 years after the enactment of the Fair Work Act 2009 (Cth) (the “FW Act”), Australian employers received guidance from the High Court regarding how to count the entitlement to “10 days” of personal leave per year of employment, as required under Section 96 of the FW Act.

The High Court determined that employees’ leave entitlement is equivalent to the average of employees’ “ordinary hours” of work over the course of a two-week period (i.e., 1/26th of the ordinary hours of work in a year) and not 10 “working days” of paid leave per year. This decision likely will have far-reaching implications for all Australian employers, particularly those with a workforce that works outside the parameters of the ordinary 9-to-5 workday, five days per week.

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COVID-19 Trend Watch: Employers Respond to Employees’ Voting Concerns with New PTO and Other Election-Related Policies

As has been true for so many issues arising from the COVID-19 pandemic, growing concerns about safely voting in the 2020 elections are beginning to permeate the workplace, prompting employers nationwide to create or revise policies to address employee apprehensions about voting amidst a pandemic. Time to Vote, a self-described “business-led, nonpartisan coalition that aims to increase voter participation in the U.S. elections,” founded by numerous major companies, reports that, as of August 27, 2020, more than 700 companies, representing about two million workers, have pledged to grant their employees unpaid or paid time off (“PTO”) to vote on Election Day and to promote initiatives such as early voting and vote-by-mail. In addition, some employers are also providing time off for employees to engage in election-related activities, such as serving as poll workers (in response to the anticipated shortage of such workers due to the pandemic).

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Missouri Court Rules in Favor of Business Owners in COVID-19 Coverage Lawsuit

Following up on our recent post about a business interruption insurance decision by a Washington D.C. court, a federal judge in Missouri ruled last month, in Studio 417, Inc., et al. v. The Cincinnati Ins. Comp., No. 20-cv-03127-SRB, that businesses can sue their insurance carrier for business interruption losses caused by COVID-19.

Plaintiffs, owners of a hair salon and various restaurants (the “Insureds”) purchased an all risks policy from Cincinnati Insurance Company (the “Insurer”). As a result of losses sustained due to COVID-19, the Insureds sought business income, civil authority, ingress and egress, dependent property and sue and loss coverages under their policies. The policies did not include a virus exclusion. After the Insurer denied their claims for losses related to COVID-19, the Insureds brought a putative class action against the Insurer for breach of contract and declaratory judgment.

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As Schools Reopen, U.S. Department of Labor Issues FAQs on Childcare Leave Under the FFCRA

The beginning of the school year has added to a mire of uncertainty of how to manage work and family in our current COVID-19 world. Some schools have reopened to full-time in-person classes, while others have adopted full-time remote learning; still others have opted a hybrid model that mixes the two, and some give parent the choice of whether to send their children to school or have them login. Added to this, decisions once made are subject to reversal, if new COVID-19 cases enter the picture.  So now, on top of everything else that the COVID-19 crisis has affected, working parents must try to figure out how to manage their children’s education, while trying to maintain their financial security. And, as always, employers need to remain mindful of their compliance obligations.

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