VIDCAST: Sourcing and Screening at a Time of Talent Scarcity

In the wake of the Great Resignation, the war for skilled workers rages on, with more open roles than there are job seekers to fill them. Candidates are willing to wait it out to find best-fit roles, demanding (and receiving) higher compensation, more flexibility, community, and an inclusive culture before accepting a full-time job at a traditional employer.

Meanwhile, an open role represents significant costs for an enterprise through both productivity and financial losses; numbers that only compound with each passing day. To avoid such pitfalls, a long-term strategy is needed to navigate today’s talent shortage. 


In the short term, there are immediate measures HR leaders can put in place to get the right people in the right places quickly. These include sourcing and attracting talent through creative recruitment, broadening the talent pool to include active and passive candidates, looking internally for employee mobility opportunities and focusing on skills-based hiring within all of these channels.

In this session, retrain.ai co-founder and COO Isabelle Bichler-Eliasaf and Chief Research Officer Ben Eubanks of Lighthouse Research discuss how AI can invigorate and expedite the sourcing and screening process to help HR leaders hone in on best-fit, diverse candidates faster. Their conversation covers:

  • The biggest hiring challenges today and how HRs are managing them
  • What factors have caused today’s talent shortage
  • The importance of career-pathing opportunities in attracting talent and keep employees engaged
  • How AI and skills-matching can build a talent marketplace to fuel internal mobility
  • How AI can enhance the human experience at work and strengthen DEI goals
  • What constitutes Responsible AI and how does HR tech balance automation and fairness
  • Ben’s 2023 predictions for HR

 

 

 

Update: Responsible AI and the NYC Audit Law Pushed to Q2

UPDATE: The Automated Employment Decision Tool (AEDT) Law (Local Law 144) slated to take effect in New York City, on April 15th will be delayed until May 6, 2023.

On Monday, December 12, 2022, the New York City’s Department of Consumer & Worker Protection (“DCWP”) announced the Automated Employment Decision Tool (AEDT) Law (Local Law 144) slated to take effect in New York City, on January 1st will be delayed until April 15, 2023.

Created to ensure organizations using automated / AI-based hiring tools proactively protect against potential or unintended bias in the processing of candidate information or hiring decisions, the law requires organizations using such tools to comply with mandatory independent audits of AI systems and transparency about their use with candidates. With only months to go, this means the time for enterprises to evaluate their systems for ethical, Responsible AI is now. 

Learn how this law impacts HR Leaders everywhere, not just in NYC >>

Despite its designation as a local law, HR leaders everywhere must remain engaged in tracking its evolution. New York City is the epicenter of the business world, if an enterprise operates and has employees or is hiring employees in NYC this regulation applies to them.

So why the delay? 

The New York City Department of Consumer and Worker Protection (DCWP) is overseeing the rollout of the law. They say the delay is due to the high volume of public comments generated by a public hearing held in November. A quick review of the department’s website shows well over 100 pages of feedback and inquiries stemming from that hearing, including comments submitted by retrain.ai. The DCWP aims to review all input before planning a second hearing.

What sort of questions came up? 

Numerous points were raised, ranging from what specifically defines an AEDT to how regulation can remain effective without stifling innovation. A few specifics included:

  • What sort of qualifications and certifications will be required to select and authorize an independent auditor? 
  • How will data size be figured into the equation, given that some businesses won’t possess the robust data set necessary to accurately determine bias?
  • What options are available to candidates who opt out of the AI-based systems, as is their choice? How will they be assured equal consideration in the hiring process?

A second public hearing will be planned for the first quarter of 2023. In the meantime, we’ll keep you updated in our Responsible AI Hub, where you can also learn what constitutes unbiased, Responsible AI, what to look for in an HR Tech vendor to ensure compliance, and how retrain.ai uses the five pillars of Responsible AI to support the growth of a skilled, diverse workforce.  

To experience a personalized walkthrough of how retrain.ai can help you reach your HR goals, visit us here.

Additional resources

  • Responsible AI and the NYC Audit Law: What You Need to Know Before 2023 – On-demand webinar
  • Responsible AI: Why It Matters and What HR Leaders Need to Know – On-demand webinar

Q&A: The NYC AI Audit Law

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

For organizations using AI in their hiring processes, prepping for 2023 means evaluating compliance with a new law that will take effect in New York City in January, but which will impact millions of HR leaders and job candidates everywhere

Local Law 144, or the NYC AI Audit Law, 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. To avoid introducing unintended bias into those actions, however, the AI must be responsible–meaning fully explainable machine learning systems structured to avoid biases that could skew results unfairly. 

With only weeks to go until the NYC AI Audit Law kicks in, there are still plenty of unanswered questions. In this vidcast, retrain.ai Co-founder and COO Isabelle Bichler-Eliasaf speaks with Rob Szyba, partner and employment attorney at Seyfarth Shaw about aspects of the law that aren’t quite clear yet, including:

  • What specifically defines an automated employment decision tool (AEDT)? How much weight is given to the AEDT as one part of a multi-level hiring process?  [Timestamp: 5:08]
  • Who is performing the mandatory AI bias audits required by the law?  [Timestamp: 10:01]
  • What accommodations are given to candidates who opt out of AEDT interview steps?  [Timestamp: 11:28]
  • How are candidates who opt out assured equal consideration?  [Timestamp: 12:38]
  • What happens to organizations in that are new to AI use in hiring and don’t necessarily have enough data to test their system by the time the law takes effect? Will they be considered in default?  [Timestamp 15:32]
  • The law applies in New York City, but what does that mean for businesses based outside of NYC who have offices or even remote workers based in the City?  [Timestamp 19:02]
  • How can those of us in the AI space convey the importance of ensuring that regulation helps the process without stifling innovation? That it protects AI’s ability to enhance the human workforce experience?  [Timestamp 25:06]

Additional Resources:

Not Headquartered in NYC? The New AI-based Hiring Regulations Will Likely Still Apply to You. Blog post

NYC AI Law Update – 4 Important Things You Need to Know Blog post

A New NYC Law Puts Pressure on Talent Intelligence: Will Your AI Solution Be Ready? Blog post

Responsible AI and the NYC Audit Law: What You Need to Know Before 2023 – On-demand webinar

Responsible AI: Why It Matters and What HR Leaders Need to Know – On-demand webinar

To experience a personalized walkthrough of how retrain.ai can help you reach your HR goals, visit us here.

Not Headquartered in NYC? The New AI-based Hiring Regulations Will Likely Still Apply to You

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

Beginning on January 1, 2023, companies using AI in their hiring practices in New York City must comply with Local Law #144, the Automated Employment Decision Tool Law (AEDT), which mandates independent audits of AI systems and transparency about their use with candidates, among other specifics. 

At its core, the NYC Law–and the larger EEOC statement that preceded it–aim to ensure that AI and other emerging tools used in hiring and employment decisions don’t introduce or augment bias that can create discriminatory barriers to jobs. You can read more about the details of the law in our earlier blog post

While some may believe the new regulation is just a niche city law that only applies to enterprises within the boundaries of New York City, impacting a relatively small pool of employers and job candidates, the reality is that its reach goes well beyond the NYC metro area and even the state as a whole.

Who needs to pay attention to the NYC Law?

Pretty much EVERYONE.

New York City is the epicenter of the business world, with many corporate roads running through it. If an enterprise operates any element of its business through NYC, and if they hire staff for that function, the law applies. 

Enterprises don’t need to be that expansive. Organizations using AI in hiring and promotions practices will need to ensure compliance with the new law if:

  • They have any sort of office or presence in NYC
  • They are based elsewhere but have open positions based in NYC
  • They have open remote positions that may attract candidates residing in NYC

But what if a company has only a single NYC employee, working remotely from their apartment in the City? Or if a global company has just one position to hire in Manhattan–which may be filled by a candidate living in New Jersey or Connecticut? 

It ALL counts. And reaches just about EVERYWHERE.

The geographic reach of the NYC law stretches far beyond the U.S. as well. New York City is a major hub for companies based all over the world and global companies who operate any part of their business–from a US Headquarters to a sales office, to a warehouse team and everything in between–fall under the requirements of the new legislation.

Strategize now for compliance next year.

Add up all the scenarios and you’ve got a massive number of companies that will be under the microscope come January. In today’s competitive landscape, stopping to retrofit HR systems for compliance presents a loss of momentum. Likewise accommodating multiple solutions across geographies or business functions. 

If you’re not sure whether your HR systems are using Responsible unbiased AI, now is the time to find a partner who can integrate with your HR tech stack, forming a unified system of intelligence that actively targets and eliminates unintended bias.

The retrain.ai Talent Intelligence Platform is built on the five pillars of Responsible AI to provide our customers with a transparent and bias-audited system. Our Talent Acquisition and Talent Management solutions help HR leaders hire faster and retain longer, while actively supporting a skilled and diverse workforce. 

To experience a personalized walkthrough of how retrain.ai can help you reach your HR goals, visit us here.

 

Additional resources

  • Responsible AI and the NYC Audit Law: What You Need to Know Before 2023 – On-demand webinar
  • Responsible AI: Why It Matters and What HR Leaders Need to Know – On-demand webinar

NYC AI Law Update – 4 Important Things You Need to Know

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

How AI Can Enhance the Human Experience at Work

Can’t AI be considered a threat to people’s jobs? How can we view it as a positive for HR?

By providing a skills view of an enterprise’s workforce, AI-powered talent intelligence can highlight best-fit positions and new opportunities for employees within the organization, as well as suggested development courses to help them get there. As a result, HR leaders can offer personalized career pathing at scale, investing meaningful effort into each and every employee. 

In this clip from our 3Sixty Insights vidcast, retrain.ai co-founder and COO Isabelle Bichler-Eliasaf discusses the power of personalized professional development to lower attrition and engage employees.


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.

Responsible AI and the Algorithms That Fuel DEI

How can HR leaders ensure their AI is supporting DEI efforts? 

To accelerate DEI goals, the ultimate aim of responsible AI is to solve potential unintended bias. As such, machine learning models must be specifically designed using fairness algorithms that focus on skills without incorporating demographic or other information that could skew unbias results.


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.

Employee Skills Data and the Future of Work: Insights Tell the Story

How can HR leaders successfully build a skills-based talent pipeline in an ever-changing world of work? 

Analyzing and forecasting in-demand skills enables us to see what job opportunities exist now and what learning and development opportunities could help enterprises and their employees prepare for the jobs of the future. 

In this clip from our 3Sixty Insights vidcast, retrain.ai co-founder and COO Isabelle Bichler-Eliasaf discusses the billions of data points that feed such predictive analytics, and what value the resulting insights hold for organizations preparing for the future of work. 

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.

Customer Chat: Maccabi Healthcare Services (part 2)

Welcome to part two of excerpts from our conversation with Yael Rotem-Sher, Organizational Development Manager, and Ifat Alfasi, Head of Learning and Development, Maccabi Healthcare Services. In this post, we’ll focus on skills development and career-pathing. If you’re not caught up on part one, you can read about the keywords approach in our previous post, and for a deeper dive check out our Skills Extraction whitepaper to learn how semantics, not keywords, are the ROI differentiators.

If you’re interested in viewing the vidcast in its entirety, you can do that here.

 

How do you view the recent focus on skills-based talent acquisition, talent management, and L&D? 

 

In the past, or in some cases still, most organizations look at career management in terms of jobs. You go from job to job to job to job. Nowadays, we look at this through a different lens–a skills lens. Which skills are required for multiple jobs, and can also be beneficial in other things? And for your specific job, which skills do you need to be able to continue doing it? We’re looking at everything from a 3D perspective. Not just, “here’s the job, and here’s the ladder” that we were used to. It’s a much more complex climbing wall. 

Building on the climbing wall idea, we wanted to give employees more tools to be in charge of their own career paths and to strengthen their employability. The first way we do that is by moving people within the organization, giving people different roles. The second is focusing on learning–personal and professional development. Maccabi has some amazing projects that enable employees to experiment with managing a project from start to finish, not as part of your job, but as a separate project. This gives them experience and skills that contribute to their value as an employee in our organization–and outside of it. Today it’s not a bad word to think of your value both in and out of your organization.

 

How does Maccabi build on that idea to help employees grow from skills development to career-pathing? 

 

When we look at learning & development for an employee, we first focus on specific skills: Which skills should be strengthened? Which skills should you invest time in as you build your career path? The process isn’t immediate gratification–it won’t give employees available positions immediately. Our aim is that it will help us with long-term planning. If as an employee I’m in point A, I’ll set point B and point C as my goals. Then I’ll plan my way there: These are the areas I should move forward to that match my skills. Which other skills do I need to upgrade and work on?

In practice, we want to create a visual marketplace; a website, or page on our website where our employees can go through retrain’s intake process, then click on jobs they find interesting, get to the landing page of our recruitment department and see available positions. If the position they fit into isn’t available now, maybe it will open up six months or a year from now. In the meantime, they can see which skills to work on and enter our online learning system to see L&D opportunities curated by retrain.ai’s system. It’s an image of the future. 

It’s a lot of work to create this but this is our goal– to give our employees and our managers the ability to plan their climbing wall strategically, based on skills. It’ll come into play in feedback and evaluation talks, employees will be more career-oriented and many parts of the organization will work with the recruitment department. And wow, the sky is the limit with this process.

 

How does the marketplace look from an employee perspective? From an organizational perspective?

  

At the end of the day, it’s like an employee’s navigation tool–like Waze for the career world. They are able to use the tool based on their skills, their wants and aspirations, combined with the current market demand and their company’s goals. They can enter the portal, see existing options, see whether–or when–they’re available and in essence take the wheel on steering their career. If they see a role they like, they can upskill for it by purchasing courses. For example, if you want to become a data analyst, you must learn python; here are relevant python courses. You don’t need to get confused by the variety. It’s a win-win for the organization and the employee.

From the business side, retrain.ai gives our organization the ability to generally map and detect the low-skill vulnerabilities to see where we need to develop. It can give sectorial maps, geographical and regional maps– it betters our organizational vision.

For example, ‘analyst’ is a growing profession all over the world including within Maccabi. We need more and more people skilled in this field. So if I plan to develop an analyst program, I’ll use this system and it will tell me who has the right skills and potential to become a data analyst. Then, I can very quickly pick them without a huge process of mapping out people. Based on that, I can also plan for the needs of the recruitment department. It opens a lot of opportunities and potential. 

retrain.ai is an AI-powered matching engine already prepped for the future. Structured first and foremost around Responsible AI, our talent intelligence platform 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

Customer Chat: Maccabi Healthcare Services (part 1 of 2)

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