Author: Isabelle Bichler

UPDATE: Local Law 144 will now go into effect on May 6, 2023.

This is an update to our initial post on the upcoming NYC Law. 

With less than six months to go before a new AI audit law goes into effect in New York City, new details are emerging to give us a better understanding of how the legislation–and penalties for noncompliance–will be implemented. 

Local Law 144 of 2021, as it’s known, issues updated guidelines for employers using AI in hiring. Part of a quickly growing practice, AI tools are in high demand for companies looking to speed up preliminary candidate screening and enable efficiency in the hiring process. In order to avoid introducing unintended bias into those actions, however, the AI must be responsible. There are several key attributes of Responsible AI, the net result of which is fully explainable machine learning systems structured to avoid biases that could skew results unfairly. 

There are still many questions around the details of the NYC audit law, which says companies using “automated employment decision tools” must first submit them to an independent bias audit and notify candidates at least ten days before an AI tool is used to allow for accommodations. But now we know more about what happens to those who don’t comply.

 

The latest update:

 

• Each day an employer uses an automated employment decision tool in violation of the law counts as a separate violation. 
• An employer’s failure to provide notice to a candidate or employee constitutes an additional daily violation.
• Potential violations will be viewed quite broadly, setting forth penalties applicable to “all subdivisions, paragraphs, subparagraphs, clauses, items or any other provision.”
• Fines for first time violations start at $375 per infraction; second violations start at $1350.

Plenty of questions still remain around the logistics of the new law, including who will conduct the required impartial audits and what standard will be used to determine any disparate impact on job candidates. We’ll be watching for those updates in the coming weeks and months, and will be sharing them here. 

 

retrain.ai is a talent intelligence platform designed to help enterprises hire, retain, and develop their workforce, intelligently. Leveraging AI and real-time labor market data, enterprises unlock talent insights and optimize their workforce effectively to lower attrition, win the war for talent and the great resignation in one, data-driven solution. To learn more book a demo. 

More than two years since the start of the pandemic, hospitals around the world are still grappling with burnout, battling some of the worst staffing shortages in decades. Even before Covid-19, the U.S. public health system was under strain; a recent McKinsey report found that the public health workforce shrank by more than 15% over the past 10 years.

Maccabi Healthcare Services faced similar staffing and attrition challenges when they turned to retrain.ai. Together, we helped Maccabi create a harmonized view of their workforce, clarifying what deployable skills they already had in-house, the talent they could quickly upskill to fit their short- and long term needs, and the skills they would need to begin developing and hiring for going forward.

We sat down with Yael Rotem-Sher, Organizational Development Manager, and Ifat Alfasi, Head of Learning and Development, both from Maccabi, to talk about our collaboration. In the first of a two-part blog series, we’ll share excerpts from that conversation.

The full vidcast can be viewed here.

 

This is a journey into this very interesting project. Where did the need stem from? 

 

The first step was dreaming, visualizing what we wanted the future of Maccabi to look like. We looked at the current state, what problems we were facing, we looked at the world and asked ourselves which changes and adaptations were required. Then, we began building our dream of career management. 

Maccabi is a very large organization: 9,000 employees, 6,500 independent contractors; with subsidiaries, we’re over 120,000 people. At the end of the day, it’s a challenge because one can’t see the forest for the trees. 

Our second challenge was narrow pyramids in some roles. Most of our employees are caregivers; in that capacity, the pyramid you climb up is relatively narrow. Like everyone, we also began experiencing the trends in the labor market; although the percentage of people leaving Maccabi is relatively low compared to other organizations, it was still becoming a challenge. 

Thirdly, we looked at futuristic skills and understood we needed to develop our employees for the changes coming. In the past, an organization was in charge of its employees’ careers, but now, the power is in the hands of the employees. We asked ourselves,  how do we that shift? How do we make it accessible to them? How can we help them understand where and how they can develop? 

A big part of it also has to do with curatorship. Curatorship and accessibility were big challenges. Because everything is big in our organization, when we talk about personal and professional development, we’re talking about development in roles but also through learning and experimenting. And we wanted to make it all accessible. 

While we were starting to visualize this future, we mentioned our ideas to a vendor who put us in touch with retrain.ai.  When retrain.ai presented their concept to us, I felt like my dream was coming true. It was like… Where did you come from? With every word, we looked at one another in awe. They talked about everything we visualized in our future.

 

How was your collaboration as a fast-paced startup alongside a huge and perhaps a bit traditional organization? 

 

Maccabi may be defined as a very large, traditionally bureaucratic healthcare organization, but in terms of Learning & Development, when we look ahead, we think, where do we want to bring our organization? The ambitious goals we set ourselves are based on the organization’s strategic goals. We want to be a more agile, fast-paced, adaptable organization. We don’t want every process to take two years. This is what we have in common with retrain.ai, and that’s how we make it happen. Our partnership means we have backup. This doesn’t mean it will happen instandly across the whole organization, but it’s starting to sink in in many areas, enabling us to move forward quickly.

We also try to be as innovative as possible, which is why it’s no surprise that we met retrain.ai. We’re currently building training plans based on the fundamentals of where we want to go, and we progress by listening to the needs of our clients–in this case, participants in the program or even their managers. We always remain agile to modify and adapt.  and we build it as we go while listening to our clients’ needs. In this case,  the participant in the program or even their managers. We always remain agile enough to modify and adapt things.

 

How was the process of incorporating retrain.ai’s platform?  

 

We had always understood these to be long, time-consuming processes; by the time our database was updated, we’d have to do it again, as it will be outdated and irrelevant. Working in a very large organization, such processes aren’t easy; they take time and are impacted by bureaucracy and acquisitions. 

With retrain.ai, we brought them into our department’s management meetings because not only did their solution meet our needs as an organizational learning & development department, it also related to mobilization, recruitment, employee retention, employer branding–all fields of HR. From that, we were able to recruit quite quickly and see the benefits. In terms of learning & development, we had already been offering a multitude of opportunities but didn’t have the accessibility and curatorship we needed. These two elements come into play in retrain.ai’s solution, and our need was met. It was amazing. 

In our second in this two-part series, we’ll find out how retrain.ai supported Maccabi’s efforts around skills-based development and employee career pathing. 

retrain.ai is an AI-powered matching engine already prepped for the future. Structured first and foremost around Responsible AI, our solution connects the right talent to your open roles and career pathways by tapping into their skills, capabilities, and aspirations, making sure you reduce attrition and retain the right talent. To see it in action, request a demo. 

Update: The New York City Council has now voted to push back the implementation of the pay transparency law to November 1, 2022.

Beginning in May, employers hiring in New York City will be required to give a minimum and maximum salary range within every job posting. The legislation, enacted by the NY City Council, is meant to course-correct pay inequities within organizations by keeping salary information out in the open. Beyond New York City, the trend has already been moving steadily forward. In 2020, a Pay Transparency Study from Mercer found that 67% of organizations viewed the practice as increasingly important. 

Continue reading “We (Literally) Need to Talk Money in NYC. Salary Transparency is Here.”

UPDATE: Local Law 144 will now go into effect on April 15, 2023. Learn more about the change here.

On January 1, 2023, a new law will take effect in New York City, aimed to more heavily regulate the use of AI in screening job candidates or employees up for promotion. The news follows an October 2021 statement from the U.S. Equal Employment Opportunity Commission, announcing updated guidelines for employers using AI in hiring.

Continue reading “A New NYC Law Puts Pressure on Talent Intelligence: Will Your AI Solution Be Ready?”

Gartner’s latest survey of HR professionals shows DEI is among the top priorities for 2022, along with change management and the future of work. In response, a whopping 79% of companies across industries are increasing budget investments for DEI.

Continue reading “Expanding the Role of DEI”