1940: The Science of Making Work Fair

Summary

Podcast Summary: So Money with Farnoosh Torabi – Episode 1940

The Science of Making Work Fair
Guest: Siri Chalazi, Senior Researcher at Harvard Kennedy School
Date: February 4, 2026

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Episode Overview

In this episode, host Farnoosh Torabi sits down with Siri Chalazi, a renowned researcher on gender equity in organizations, to explore her new bestselling book, Make Work Fair (co-authored with Iris Bohnet). The conversation pivots around shifting the focus from “fixing” biased individuals to redesigning workplace systems, policies, and daily practices to foster fairness, equity, and inclusion. The episode delivers evidence-based, practical strategies for making workplaces more equitable, discusses the failings of traditional DEI (Diversity, Equity, and Inclusion) approaches, and offers both leaders and everyday employees tools for change – often surprisingly simple ones.

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Key Discussion Points & Insights

What Does Fairness at Work Really Mean?

• LEVELING THE PLAYING FIELD:
  • Siri uses the analogy of an Olympic sprint to define fairness: everyone starts at the same line with the same resources and conditions; only then can outcomes reflect true merit (05:45).
  • “A workplace in which everyone gets an equal opportunity to show up at the starting line... and the same resources and support to actually show their full talents.” — Siri Chalazi [06:14]
• DIFFERENCE BETWEEN EQUITY & EQUALITY:
  • Fairness is deeper than equality; it requires removing systemic barriers so everyone can maximize their potential.

How Do Biased Systems Cause Unfairness?

• Bias isn’t just individual prejudice—it’s reflected in job requirements, promotion criteria, evaluation processes, and expectations (like international mobility), often disadvantaging caregivers or those with nonlinear career paths (08:04).
• Real-world Examples:
  • Gaps in resumes unfairly penalized in hiring.
  • Women and minorities less rewarded even for equal performance.
  • Promotion criteria (like “international rotation”) exclude people with complex life circumstances (08:04–09:21).

The Flaws of Traditional DEI Initiatives

• Token Programs vs. Daily Practices:
  • Many DEI efforts are isolated—training programs, special events—rather than integrated into the daily business of running teams, evaluating performance, or hiring (13:42–15:49).
  • “People are still spending 99% of their time doing work the same way they had already done it.” — Siri Chalazi [13:45]
• Programs are easy to cut; it’s the everyday processes that truly drive fairness.

Redesigning Systems: The Three-Part Framework

• SIMPLE, HIGH-IMPACT TWEAKS:
  • Small changes in meetings, evaluations, and communications can make a huge impact (16:52).
  • Everyone (not just leaders) can make a difference; fairness isn’t just an “HR/leadership” issue.
• Examples:
  • Meetings: Ensure everyone’s voice is heard—use round robins, agendas sent in advance, or anonymous voting to empower quieter team members (17:50–18:22, 23:52).
  • Evaluations & Hiring: Predetermine what you’re evaluating to avoid “gut decisions” (18:25). Focus on actual skills, not proxies like resume gaps or who’s the loudest advocate (31:15).
  • Counting Representation: BBC journalist Ross Atkins started counting on air guests by gender to self-check representation, something “anyone can start counting.” (18:25)
• Quote:
  • “All of us have to and can make small tweaks in our everyday work to help make sure that we collectively are operating in a fair organization.” — Siri Chalazi [16:52]

The Role & Risks of AI in Fairness

• Amplifying Old Biases:
  • AI systems often encode and perpetuate biases already in data and human society, e.g., giving different negotiation advice based on perceived gender (10:13–11:11).
  • “When AI thinks it’s giving negotiation advice for a woman as compared to a man, it instructs that woman to negotiate less assertively...” — Siri Chalazi [11:08]
• Potential: AI can be a giant force for good—one algorithm is easier to fix than millions of minds—but only if fairness and reduction of bias is prioritized in development (12:05).
• Challenge: Tech companies are currently more focused on speed and scale than on fairness.

Making Compensation & Hiring Fairer

• Transparency is Key:
  • Posting pay ranges on jobs closes gender/racial wage gaps (24:51–27:12).
  • Employees should benchmark pay with all colleagues (not just those comfortable discussing) and advocate collectively for new benefits (menopause leave, flexible work, etc.) (27:12).
• Hiring:
  • Use actual skills-based exercises and scenarios in hiring, not just resumes (31:15–31:42). This is especially important as AI-generated or embellished resumes become more common.
  • “Evaluating people’s direct skills is by far the most predictive way of hiring.” — Siri Chalazi [31:42]

The Value of Fairness as a Business Priority

• Fairness isn’t just about being nice—it’s a business imperative. The number one thing CEOs cite for their company’s success? “People.” Fair systems ensure the best talent is found and put into the right roles (29:29–31:15).

Legal Dimensions and Optimizing for Fairness

• Farnoosh asks about when unfairness becomes a legal issue. Siri recommends treating fairness systems with the same rigor and experimentation as product or marketing processes: measure, track, adjust, and take calculated risks (35:06–36:40).
• “The riskiest thing is to keep the status quo.” — Siri Chalazi [36:40]

You Can’t (Easily) Change People—But You Can Change Systems

• Try to “de-bias” environments rather than individuals. A classic example: blind auditions for orchestras drastically increased the hiring of women, not because people became less sexist, but because irrelevant information (gender) was removed from the process (38:15–39:52).
• “You can’t change people, but you can change systems.” — Siri Chalazi [37:59]
• Simple changes can be profoundly effective: e.g., an Australian company boosted women’s promotion reapplications just by emailing rejected candidates a line saying they were “in the top 20%” (41:10).

Trends in Women’s Workforce Participation

• After pandemic declines, women’s workforce participation hit an all-time high in late 2024, but then dropped in 2025, especially for Black women, often due to sector-specific government and DEI cutbacks (41:53–43:18).
• Flexible work arrangements have been shown to drive both fairness and performance, but RTO (return-to-office) mandates are causing talented women and seasoned employees to leave (43:51–45:46).
• “When people do different roles, they should get paid differently... how come if someone works fully on a computer, we don’t recognize that it makes sense for them to have the flexibility to do it from wherever they want to?” — Siri Chalazi [45:46]

Personal Motivation

• Siri describes how seeing career advancement inequities firsthand as a management consultant galvanized her research path (46:45–48:22).

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Notable Quotes & Memorable Moments

• On why tackle fairness systemically:
  • “You can’t change people, but you can change systems.” — Siri Chalazi [37:59]
• On blind auditions & outcomes:
  • “When musicians auditioned behind a curtain, the share of women hired rocketed up—not because directors went through bias training, but because we removed irrelevant information.” — Siri Chalazi [39:52]
• On the myth of risk in changing practices:
  • “The riskiest thing is to keep the status quo.” — Siri Chalazi [36:40]
• On transparency’s role in closing gaps:
  • “Just having those salary ranges posted transparently... helps to close gender and racial gaps in salary.” — Siri Chalazi [24:51]
• On DEI programs:
  • “People were still spending 99% of their time doing work the same way...” — Siri Chalazi [13:45]

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Timestamps for Key Segments

• Defining Fairness with the Olympic Race Analogy: 05:40–07:55
• Concrete Examples of Systemic Bias: 08:04–09:21
• AI, Hiring & Gendered Bias: 10:13–12:14
• Problems with Traditional DEI Programs: 13:34–15:49
• Small Tweaks Anyone Can Make: 16:52–18:25
• AI in Negotiation, Amplifying Bias: 11:08–12:05
• Compensation, Transparency, & Advocacy: 24:51–27:12
• Hiring for Skills, Not Just Resumes: 31:15–31:57
• Legal vs. Practical Approaches: 35:06–36:40
• Blind Orchestra Auditions & Evidence: 39:52
• Empowering Rejected Candidates (Australian Company Example): 41:10
• Women’s Workforce Trends in 2024–2025: 41:47–43:18
• Flexible Work & Fairness: 43:51–45:46
• Personal Story—Why This Work?: 46:45–48:22

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Final Takeaways

• Workplace fairness is not just about eradicating individual bias but about systematically building processes that prevent it.
• Evidence-based, often cost-free, and extremely simple changes—like clearer communications, collecting representation data, or changing evaluation methods—can transform workplace equity.
• AI can entrench old biases or become a force for fairness, but only if designed thoughtfully.
• Fair practices are not only ethical but essential for long-term business performance.
• Collective action—by employees as well as leaders—powers meaningful, lasting change.

“All of us have to and can make small tweaks in our everyday work to help make sure that we collectively are operating in a fair organization.” — Siri Chalazi [16:52]

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Guest: Siri Chalazi
Book: Make Work Fair
Host: Farnoosh Torabi
Listen: So Money Podcast

Transcript

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[Siri Chalazi]

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So money.

[Narrator/Host]

Episode 1940 the Science of making work more fair.

[Iris Bonet]

You're listening to SO Money with award winning money guru Farnoosh Torabi. Each day get a 30 minute dose of financial inspiration from the world's top business minds, authors, influencers, and from Farnoosh yourself. Looking for ways to save on gas or double your double coupons. Sorry, you're in the wrong place. Seeking profound ways to live a richer, happier life. Welcome to SO money.

[Siri Chalazi]

One of the largest employees in Australia. They noticed that internally when women and men had applied to a leadership position, obviously one person gets a job. Most candidates are rejected. Among those rejected candidates, men were twice as likely as women to reapply for another leadership opening. And the organization said, we want to keep all these competent people in the pool. Do we want to close this gap? And they did something super simple. They were already emailed the rejected candidates saying thanks for applying. Sorry I didn't get the job. Please reapply. There's many different similar openings available. They added one sentence into the email that accurately informed candidates that they were in the top 20%. If you're in the top 20%, please reapply. And going back to our conversation earlier about the importance of transparency and reducing ambiguity by being more transparent with folks about, hey, you're at or close to the top, you actually have a realistic chance of getting another job if you reapply. And that close to gender gap in applications.

[Farnoosh Torabi]

Welcome to so Money everybody. I'm Farnoosh Tarabi. You know, sometimes making work more fair doesn't require a sweeping policy change or a million billion dollar program.

[Narrator/Host]

Sometimes it's as simple as one sentence, the right information delivered at the right moment and that can change who stays in the game and who quietly opts out. That idea sits at the heart of.

[Farnoosh Torabi]

Our conversation today with Siri Chalazi. She's a senior researcher at the Women in Public Policy Program at Harvard Kennedy School International recognized expert in advancing women and promoting gender equity in organizations. Together with her co author Iris Bonet.

[Narrator/Host]

A behavioral economist, they've written the bestselling.

[Farnoosh Torabi]

Book Make Work Fair. And it challenges one of the most.

[Narrator/Host]

Common assumptions we make about inequality at.

[Farnoosh Torabi]

Work, that the problem is just biased people who need to be fixed. Instead, their research shows that unfairness is actually baked into systems, processes and everyday practices. How we hire, how we evaluate, promote.

[Narrator/Host]

Pay, and even run meetings.

[Farnoosh Torabi]

And the good news is that these.

[Narrator/Host]

Systems can be redesigned.

[Farnoosh Torabi]

So we talk about what fairness actually means in the context of work, why traditional DEI programs are falling short, the small evidence based changes that make huge differences, and why transparency and clarity are.

[Narrator/Host]

Among the most powerful tools leaders and employees can have. Let's get into it.

[Farnoosh Torabi]

Siri Chalazi, welcome to so Money.

[Tara Davis Woodhull]

Thank you Farnooch. It's so great to be here.

[Farnoosh Torabi]

We are just a year post book launch for you. You and Iris Bonet wrote Make Work Fair. It's a very, very successful book that's making the rounds in both Corporate America leadership roundtables and here on so many, you know, our audience is largely individuals looking to have more pleasurable experiences at work, more meaningful experiences at work. Of course, we are all leaders as well, listening and so we're grateful to have you on the show to share with us not just your thoughts but your data mining around what actually makes work fair. And maybe we could start with your definition of fair because as I was pouring through a lot of the articles about your book and the pages of your book, I was curious to learn. Is it equity? Is it equality? What's fair? You often hear from my friends of color, I don't want a fair deal. I want what's equitable. And so I want to give you the stage to share your mindset behind fairness first, before we get into the.

[Siri Chalazi]

How to of it, it's the perfect place to start. So I want you to imagine the.

[Tara Davis Woodhull]

Olympics are coming up, that you are.

[Siri Chalazi]

A sprinter at the starting line of the 100 meter dash, right at the Olympics. How can we use this race to determine who the fastest sprinter is? We make sure that all the sprinters are wearing the same outfits, the same sneakers. They start at the same starting line, they finish at the same finish line 100 meters later, and in between, they all run the race on the same track. They encounter the same conditions. So whoever crosses the finish line first.

[Tara Davis Woodhull]

Is legitimately the fastest runner.

[Siri Chalazi]

But imagine a version of this race where I randomly come to one of the participants and ask them to remove their shoes or put one of the competitors to run on the grass next to the track instead of the fast, high performance track. Or in an analogy that's even more akin to what's happening in the real world, imagine I pull some of the participants 20 meters back so that instead of running 100 meters, they now have to run a distance of 120 meters. Those competitors are always going to finish later, but not because they're slower, less talented, less talented or slower, but because they're not encountering an equal or level playing field. They don't get the same conditions, the same supports to perform at their highest level. So for Iris and me, that's what fairness is. A workplace in which everyone gets an equal opportunity to show up at the starting line, the same starting line as everybody else. And then a workplace where everyone gets the same resources and support to actually show their full talents so that we're genuinely able to promote the best people, pay the most deserving people the highest salaries, and the research, unfortunately, is overwhelmingly convincing that this is not the world in which we live in today. There's actually a lot of bias and subjectivity in whom we choose to hire, how we choose to staff people on projects, who gets promoted, who gets the highest performance evaluation scores, who gets access to the executive coach or the leadership training program, or who gets to present on that high profile project in front of senior leadership. And so not everybody is getting an equal opportunity to succeed. And that's what fairness is all about.

[Farnoosh Torabi]

Wonderful. Can you run through some of those biases. Maybe just really quick, who are these people that are getting the promotions and the opportunities and the hires?

[Siri Chalazi]

Yeah, a couple concrete examples. If you have a non continuous work history on your resume, right. So there's a gap where your past job ended in 2002 and the next job started in 2005, there's a three year gap there. You're going to be penalized by employers and less likely to get hired or promoted. Not because you're any less capable, but because we have this bias against folks with career gaps. That's one example. We of course know that women and people of color are not only less likely to get hired, but even when they have the same performance evaluation scores, that translates into fewer promotions and less rewards for them. So smaller raises or bonuses. We know that a lot of the criteria that we use to evaluate people for promotions have baked in assumptions or prerequisites. Like you need to have had an international rotation that advantage certain types of people, people who have the flexibility to pick up and move. Right. Either someone who's maybe single with no caregiving responsibilities, or even if you have kids, someone who has a spouse that can help to relocate the kids and.

[Tara Davis Woodhull]

Take care of the home front while.

[Siri Chalazi]

You'Re traveling the world. So those are just a couple quick examples. But it really runs so deep into how we've chosen to structure our workplaces.

[Farnoosh Torabi]

I want to get into more of that structure and what can work better. I usually reserve the AI question for the end, but it's moving, working through our system so quickly. I have to ask, and I'm sure you have looked at this very closely and continue to the role of AI and whether it hinders or advances fairness at work. Just looking at the beginning of the journey, the hiring, the application process, we've already heard about biases there that because again, who is making these machines? It's humans with biases. And the information that AI is gathering from the Internet and all the available resources, again, at the source, it's humans who have biases. And what are you finding in terms of AI use cases, good and bad, when it comes to promoting fairness at work?

[Siri Chalazi]

From a researcher's standpoint, the biggest challenge with AI is precisely what you said at the beginning is it's moving so fast, it's evolving so quickly day to day that it's really hard to even study and test. It's like a child's brain. Right. If you ask a child to do the same task today and one week from today, they've already learned and grown so much in that week that you can't really compare the outputs. The same with AI. But we are seeing concerning evidence already that AI is amplifying and encoding a lot of the biases that exist in the sort of old world. So for example, when AI thinks it's giving negotiation advice for a woman as compared to a man, it instructs that woman to negotiate less assertively, to aim for a smaller raise, and it also directs the woman to negotiate more things like work arrangements or vacation time rather than pure salary. Whereas if it thinks it's advising a man, it says go for a super.

[Tara Davis Woodhull]

High salary, negotiate for this.

[Siri Chalazi]

We also have a study that shows that when people are told that a colleague used AI to complete an assignment, if that colleague was a woman, they're deemed to be less competent as a result. Whereas if that colleague who used AI was a man, we deemed them to be more competent because we think, oh, that man is so smart and strategic, he's leveraging the latest technology. Whereas we look at the woman and say, oh, she can hack it on her own, so she had to use AI to help. So again, 2026 manifestations of age old, gender biases. So the upside, the good potential of AI is of course a single algorithm is much easier to debias than thousands or millions of individual minds. So if we build these tools correctly, they can actually be a giant force for good. The reason I'm concerned is I don't see a lot of focus from the companies developing these new technologies on ensuring that indeed they get it, that they.

[Tara Davis Woodhull]

Are unbiased, that they are objective and fair.

[Siri Chalazi]

I see much more of a focus on speed and scale. And that's where some of this damage can happen.

[Farnoosh Torabi]

It requires so much reinforcing, as you mentioned, the human brains. We are, it's eons of kind of conditioning, not to excuse it, but it is what it is. It's. That's the kind of the hill we're up against in terms of D E and I. Your book came out in 2025 at the beginning of a year when a lot of the work that companies had done to uplift diversity, equity, inclusion within their companies seem to be made vulnerable. That the administration that we currently have was like ready to penalize institutions, companies for these sorts of proactive practices. So take us back to 2025 and maybe even before. I'm sure you saw this coming down the pipeline, this sort of pendulum swinging to the opposite direction. And, and let's focus on De and I. How are companies dealing right now with it. And I know in 2020 there was a big rush to, in many companies to create these structures. And I know you write with your co author that it was just, it was a rush. So there. It wasn't maybe very thoughtful. And so it didn't always work. How is De and I factoring into all of what you're talking about? Should we still have these departments? How should they be different?

[Siri Chalazi]

Yeah, the book came out at a very interesting time because my co author, Iris and I, of course, had started working on it years earlier and had.

[Tara Davis Woodhull]

Even finished writing it 9ish months earlier.

[Siri Chalazi]

Before it came out. Well before the election of the current administration. And what we had already been seeing as we worked with companies and studied them is that one of the biggest problems with the corporate dei, the way it was practiced was that it was very programmatic and divorced from the day to day of actual work. Host a special training program. You start a special recruitment program for quote, unquote, minorities. You'd celebrate International Women's Day or Pride Month or Black Heritage Month, either for a day or for a month, a year. But then aside from that, people were still spending 99% of their time doing work the same way they had already done it. Without tackling some of those biases and unfairness that's baked into our everyday processes of how we do work. Think about things like how you run meetings, how you staff your teams, whom you hire, whom you fire, how you decide who should get a promotion or a pay raise, how you set policies around flexible work or parental leave at your firm. Right? It's those types of everyday processes that actually impact your daily life at work. 99% of the time, going to that once a quarter networking event has much less impact on how you experience everyday work. But of course, those networking events or annual celebrations are much easier to throw money at and organize rather than actually trying to change how we work on a daily basis. And so that's really the foundation of Make Work Fair is trying to guide people to this paradigm shift of saying, let's forget those programs that don't actually change what happens at work. Let's instead make small, simple, often costless tweaks into how we work every day. That's how we're going to make work better. And that's actually the approach that works best regardless of what administration is in power, regardless of whether you're in an economic upturn or downturn. Because programs are easy to cut when money gets tight.

[Tara Davis Woodhull]

Right.

[Siri Chalazi]

Or when support from the leadership of the Organization vanishes. But every organization is evaluating performance. They need to staff people on teams. They're holding meetings every day, people are writing emails every day and speaking to colleagues. So that's the work that's happening no matter what. If we can change that, we can make organizations fairer in a lasting and resilient way.

[Farnoosh Torabi]

Let's get into some of the framework your book offers a three part framework. And without giving it all away, I know that one of the things that you really emphasize is simplicity. One, high impact behavior can be a great place to start. Where do you recommend employees and employers start? I noticed the word employees used quite a bit in the narrative. Whereas often we leave this to the leaders, to the employers to figure out. But you really want to empower everyday workers as well. And maybe that's a second question, a follow up. But first, what is a very simple tweak or action step that we can take in our workplaces?

[Siri Chalazi]

Yeah, this is like corporate communications, right? Your organization might have a PR department and they're in charge of the highest profile communications, like the CEO speeches or the annual report. But at the same time, every single employee, all day long, you're speaking up in meetings, you're writing emails, you're preparing presentations. In other words, for the organization to function, everyone needs to have a base level of communication skills. We can't rely just on the PR department. And fairness is the same way. All of us have to and can make small tweaks in our everyday work to help make sure that we collectively are operating in a fair organization. So this could be something as simple as how you conduct your meetings. Are you making sure that everyone has an opportunity to contribute? Are you actually going around the room and asking people, hey, I haven't heard from you. Or let's do a round robin, two minutes for each person to offer their thoughts on this. Hey, before we make a final decision, let's take an anonymous vote. Everybody take a post it, write down.

[Tara Davis Woodhull]

Yes or no, what's your preferred solution? And then we collect that information before.

[Siri Chalazi]

We finalize the decision. That's a simple example of leveling the playing field. If you're in charge of any kind of evaluation, whether that's hiring new employees, you're a manager, you have team members and you evaluate their performance. Are you using the same criteria to judge everybody and have you predetermined the criter before you start evaluating? Because if you just start interviewing candidates, you're much more prone to liking someone based not on their competence, but maybe.

[Tara Davis Woodhull]

Because they remind you of your younger self.

[Siri Chalazi]

And then that's gonna guide you to a more gut based decision making that's not as objective as if you had actually sat down beforehand and determined what do we need? What are the skills that we're looking for? And now let's use that to guide our evaluation. I'll also share with you briefly the example of a British journalist at the BBC, Ross Atkins, who was very passionate about, sure, that his journalism was representative of the world that it covers, but he had no data on hand to actually know whom he was featuring in his journalism and whether that was representative or not. So instead of asking HR to pull together some data sets, he just started counting with his own team. They were producing a nightly primetime news show at the time. So they'd spend two minutes at the end of each night's show, pen, post it, note counting. How many people did we we put on air during our 60 minutes? How many of those people were women? How many of them were men? And are we actually at 50? 50? Anyone can start counting.

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[Siri Chalazi]

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[Farnoosh Torabi]

I love that I've done that in my own work, I think going back many years because it's very easy to just interview the same three people for all your articles. And I'll say that I've done that. I've done that. You know your go tos you have, you're doing an article on credit or budgets and there's always like the same two people. And for many years it was mostly the men who were the loudest in the room and were they say the squeaky wheel. Was it the squeaky wheel Gets the grease. Gets the grease.

[Tara Davis Woodhull]

That's right.

[Farnoosh Torabi]

And men had some pretty greasy wheels or whatever, the squeaky wheels, they had a lot of grease. And then of course we saw. And I'm just speaking about my own domain, more and more women, people of color, people with different identities coming into the space and stepping in and say, I have some thoughts, I have expertise. And you know these folks because they've always been marginalized. Chances are they're not going to be the loudest, they're not going to be the ones to self promote as much. And so I love what the journalist did, but I also love your first tip about going around a meeting and calling on people because there is. Some people are just shyer, some people are maybe not as they're not public speakers or not as comfortable. Should they then not have a voice? Of course not. We've all been in those meetings where it just seems like it gets co opted by the same people. Great tips, great tips.

[Siri Chalazi]

Introversion. Extroversion is one dimension of diversity, right? Some people think by talking, some people think first and then talk. Another tip is send out agendas for your meetings in advance so everybody knows what will be discussed, what topics they're expected to have thoughts on so that they can actually prepare and be ready in the moment to offer their best contribution. Otherwise you're really just wasting talent in the room. You have these brilliant people in the room, but you're not giving them the playing field for them to be able to make their best contribution.

[Farnoosh Torabi]

Does your book also go into compensation and from both sides, right? From the employer and the employee. How to advocate for yourself in a way that involves this idea of fairness, that you know that what you're doing is rooted in fairness. And as an employer, how do you make sure you don't let those biases interfere with who you promote and who gets what paycheck?

[Siri Chalazi]

This is such a big topic and there's actually a ton of research on this and more coming out all the time, which is fantastic. Iris and I would argue that since the employer is the one who's making compensation decisions at the end of the day, it's really their responsibility to ensure that they're making those decisions fairly. Now, that's it. Of course, we all know that today the playing field is not level. So there's definitely things that you can do as an individual to help advocate for yourself. Transparency and lack of ambiguity is one of our best levers. So here in the U.S. for example, many states have laws that require employers to post pay ranges on their job advertisements. Elsewhere in the world, there's rules that companies have to state explicitly whether things like salary and benefits are negotiable or not. And we see that just having those salary ranges posted transparently, those statements about what's negotiable and what's not, helps to close gender and racial gaps in the salary that people actually, actually get when they come in. And of course, the more equal you are in the beginning, the more that helps over time. Because if you start with a huge chasm already from day one when you enter an organization, that's only going to get worse. This point about transparency also applies on the individual side. So try to get as much information as you can about what your pay is relative to other people's. If you're a woman, don't only benchmark yourself against other women who you might know and feel comfortable asking because they might be underpaid. Just like you rely on public sources, websites that do this aggregation. But also try as much as possible to talk to your colleagues, women and men, to figure out what other people are paid and then ask. Also negotiate, of course, if you can, if it's possible, once you're first starting the job and negotiate not just your numerical salary, but think about the benefits, the location of work, flexible work time, all those other ancillary benefits. Research shows that women tend to negotiate those a little bit more than men. So there's an opportunity here for men to also push for better benefits for themselves. And by asking to also shift what employers think is reasonable to offer, because we all know this is a two way marketplace, Companies are also responding to the signals that they're getting from job seekers and employees about what's desirable.

[Farnoosh Torabi]

Yeah, I think that in recent years has been a big paradigm shift where employees are saying, hey boss, I would love in really with, in collected, in collective numbers. Right. That's really where the power is to find other people at work to come together and say, hey, we think we should look into, I heard this recently, menopause benefits as we are aging and we need to take more time off for health reasons. This is not obviously universal yet, but anecdotally we're seeing these things because employees are bringing it to the attention of their employers. And I think that that is a great thing. What about hiring? This is again where AI is really taking over too much. I think the hiring process and really right now it's so hard to find a job and it can be so demoralizing because you may get to, you might even get an interview get to the fifth, sixth round. And then employers don't they ghost you?

[Siri Chalazi]

Yeah.

[Farnoosh Torabi]

Do you talk about that in your book? Because I think that is not fair. And I think everyone deserves a fair rejection. A fair rejection. Let me know what happened and so I can best prepare for my next job. Or at least I don't have to think it was something that I did. Maybe there was actually something that I couldn't control. And then it just affects your mental health. It affects your ability to get back out there and actually find a job. So I think the hiring process can be really where employers can do better. Do better.

[Siri Chalazi]

Yeah. Yeah. Huge area of opportunity. And it goes back to a question that you asked earlier, which I realized I didn't address, which is, what about DEI today? How are companies moving forward in this current climate? And it goes back to, why do we need fairness in the first place? Right. What's the point of fairness? It's not just to be nice or to do good for the sake of doing good. It's actually to enable business success. Because I talk to CEOs all the time and I say, if you had to pin your success down to one factor only, what would it be? And around the world, across industries, every leader gives me the same answer. Can you guess what it is? Varnush?

[Farnoosh Torabi]

You see me, I'm going like this. Money. They want to do better than the previous quarter.

[Siri Chalazi]

That's so true. But what enables them to do that? Their answer is always people.

[Farnoosh Torabi]

Oh, sure, people.

[Siri Chalazi]

And hopefully does make the world go around too.

[Farnoosh Torabi]

But yes, people, that's true.

[Siri Chalazi]

That's true. Money is a part of it. But basically what they need is they need to hire the best people, and they need to put those people into the right role at the right time and enable that person to do their best work for the company to succeed. If they're able to do that for every single role, for every single person, that organization is firing on all cylinders. And this is a need that never goes away. Because you asked me about hiring. Right? It's how do we identify the best people out there and how do we put them in the right roles at the right time? That's a critical need, and that's not possible without fairness. Because we need to be able to actually see talent in all the shapes and sizes that it comes in. And we need to be able to, through our hiring processes, through our evaluation processes, identify that talent and then make the optimal match between the talent and the roles that we have available. So AI is making it harder because it's flooding us with more and more information. Right? More and more resumes. Everybody can have ChatGPT write up a resume for them in two seconds, but the information is, is becoming lower and lower quality. It's actually less connected, related to truly what people's skills are. So how do we get around this? We get around it by shifting from things like resume reviews and looking at words on a page to actually assessing people's skills through scenarios, exercises, tasks that mimic the job that we're needing people to do as closely as possible. So if you're hiring for a customer service role, instead of asking people about, okay, so how years of experience do.

[Tara Davis Woodhull]

You have in customer service and where have you worked previously?

[Siri Chalazi]

Have them role play a real customer service scenario that might occur in your business. And this is where we can leverage technology smartly because we can have them role play that scenario with a bot and then we can assess the output. Or if you're hiring someone for a role that involves a lot of writing, instead of asking them about what they've written in the past, just design a 30 minute writing exercise and have them complete that and evaluate the quality of the actual writing.

[Farnoosh Torabi]

Brilliant.

[Siri Chalazi]

This is by far, research shows, even before the age of AI, but it's become more important now. Evaluating people's direct skills is by far the most predictive way of hiring. So how people do on that task has the highest correlation to how they'll actually perform in the job.

[Farnoosh Torabi]

If you're a huge company though, I fear that. And they're already doing this, they're leaning on AI because they want speed in the process, they want to make it more efficient, they want to make it more cost efficient, maybe means less people in the HR department. And that's what we're running up against. That is a true headwind. How do you convince companies that it's worth it to take this investment and this time investment and this money investment and this resource investment? It's not rocket science. Hiring is so important, it's so take your time. They're already taking their time. At least throw in a test or two to actually, that's the irony. Yeah.

[Siri Chalazi]

Companies say this is so important, our people are our most critical resource. And yet we're not willing to spend any time redesigning our hiring to make it actually better so that we get better people who stay longer and perform better. So here's how I convince companies to do it. I invite them to run an experiment, to do a pilot test and say, let's keep your current process, let's run all your candidates, your applicants through the current process. But in parallel, let's also design a new process where, for example, we might not ask them to submit resumes at. Or we might come up with three questions that elicit the skills that are required in the job that we're hiring for. And then we ask candidates to respond to those questions either on video or in written format. And then that's the first screen that we use to pick applicants who advance to the next round, which might be an in person interview for an exercise. So let's put the same candidates through both processes and then let's see whom we would have hired under each process and how they compare and what the differences are. And then let's actually track not just how quickly we fill a role, but let's track how well people perform in year one and two and five and let's track how long they stay.

[Farnoosh Torabi]

Right.

[Siri Chalazi]

These are often factors that are actually critical for the business, but they're not baked into the incentives around hiring because all the incentives are around fast, fast.

[Tara Davis Woodhull]

Speed, speed, speed, get somebody butts in seats as quickly as possible.

[Siri Chalazi]

And that's also a huge miss because our incentives there are not properly aligned. So it's just a matter of tweaking our processes along little bit.

[Farnoosh Torabi]

I'm wondering how this may or may not dovetail with the work that employment attorneys do. Because fairness is sometimes a legal requirement, depending on the type of fairness we're talking about, whether it's your treatment at work, obviously your firing can sometimes be cause for debate. Lawsuit. And how do you want your book to be ultimately leveraged?

[Narrator/Host]

Not.

[Farnoosh Torabi]

And we've talked so much already about like how it can be leveraged in the workplace, employers, employees, but also in the context of like when you feel you're not being treated fairly and it is creating a huge consequence cost for you. At what point is there a case for you and everything that we've talked about right now these are like things that are recommendations, but at some point they shouldn't be, they should be law, they should be required. It should be required.

[Siri Chalazi]

Yeah, I totally agree. No, I listen, I wish we lived in that world. Right. And I have to caveat. I'm not a lawyer, so I can't provide legal advice.

[Tara Davis Woodhull]

My number one advice to everybody is always consult your counsel, whether you're an.

[Siri Chalazi]

Individual or a company. But I think this comes down to one of the core messages of make work fair, which you asked earlier about the framework. One of the core messages is approach fairness in exactly the same way you Approach your core business. Right. Companies are optimizing their processes in terms of marketing or product development or engineering all the time. But somehow we never think to optimize an experiment in talent management or our HR policies around parental leave. Why not though? Because those are the tools that work to manage our business. We manage our business in a very data driven way. We collect metrics on the things we care about, we set goals. Some people might even have sales quotas or targets. Then there's incentives in place. If you meet the goals, good things happen.

[Tara Davis Woodhull]

If you miss the quotas, bad things happen.

[Siri Chalazi]

And then we track data and actually use it to create accountability so that if we're moving in the right direction, everybody benefits. If we're not, we adjust our approach. So if this is how we manage our core business and it's working, isn't this exactly how we should manage fairness? And this applies even to risk tolerance. We take calculated risks in our core business all the time and we consult with lawyers and we, we make educated decisions. There's. But we don't operate without risk. And so I think in the realm.

[Tara Davis Woodhull]

Realm is in the realm of fairness. Excuse me.

[Siri Chalazi]

It's the same thing. Yes, there's always some risk involved. People could sue you, and they do sometimes. But when you know you're on the right track, doing the right thing, actually working to level the playing field even more, equal opportunity, then you can feel pretty good that you're on the right path. I find it to be ironic. Again, I'm not a lawyer, but in the law there's this assumption that whatever you're doing today, the status quo is risk free and that if you change it, that's the risk. I would argue that in light of this mountain of evidence that shows that there's actually a lot of unfairness and discrimination and bias going on today, the riskiest thing is to keep the status quo. And the best thing to do is actually to show that you're taking active steps to ensure that you take out all the unfair fairness that is baked into your processes. That's how I would frame it.

[Farnoosh Torabi]

Brilliant. In the beginning of your book, you tackle some myths that we need to get acquainted with when it comes to just fairness and biases. And one of the myths that you write about is that we need. It's a myth that we need to. Debias, individuals and I, we talked about this a little bit earlier and we have all these kind of assumptions, but how does that work? You can't change people. People. What are the workarounds then?

[Siri Chalazi]

Yeah, you can't change people, but you can change systems. And to me, this is actually one of the most groundbreaking insights from behavioral science that's emerged from research in economics.

[Tara Davis Woodhull]

Neuroscience, psychology, organizational psychology, so forth over the decades.

[Siri Chalazi]

Which is that even though we humans, all of us are biased, it's just how our brains are wired. When we're put into a decision making circumstances, circumstance into an environment that is unbiased, our brains can make more objective decisions. So if we surround ourselves with smart systems that build science into how the system is designed, build our kind of best understandings of how to work around biases, we can actually make better decisions. The great classic example is hiring for orchestras. When in orchestra auditions, musicians were invited to audition behind a couple curtain so that the evaluators could hear the music but not see who was playing. The share of women hired rocketed up. Not because the orchestra directors went through unconscious bias training or not because they had goals or targets in place, simply because we removed irrelevant information, the gender and the looks of the person from factoring into the decision. And we liberated the orchestra directors minds to focus on the thing that actually mattered, which was the quality of the sound. And there are so many ways we can do this in our workplaces today. So to go back to the bias I mentioned against people with non continuous work histories, one way we could get around that is by redesigning the formatting of our resumes so that instead of listing a past work experience with the specific dates attached 2000 to 2005, we would just say the specific work experience with the total amount of time or years that we did that job. Five years as a manager, 10 years as a senior manager.

[Farnoosh Torabi]

Brilliant.

[Siri Chalazi]

And we don't lose any information that's relevant to assessing a person's competence. But we do obscure the gaps that skew hiring managers for no reason. Another example, which I love, relates to career progression. One of the largest employers in Australia, they noticed that internally when women and men had applied to a leadership position, obviously one person gets a job. Most candidates are rejected. Among those rejected candidates, candidates men were twice as likely as women to reapply for another leadership opening. The organization said, we want to keep all these competent people in the pool. Do we want to close this gap? And they did something super simple. They were already emailing the rejected candidates saying thanks for applying, sorry I didn't get the job, please reapply. There's many different similar openings available. They added one sentence into the email that accurately informed candidates that they were in the top 20 position. You're in the top 20%, please reapply. And going back to our conversation earlier about the importance of transparency and reducing ambiguity, by being more transparent with folks about, hey, you're at or close to the top, you actually have a realistic chance of getting another job if you reapply that close to gender gap in applications. And it didn't cost them a cent to just add a sentence into the email. So these are the types of concrete, simple redesigns that we packed into the book, scouring all the evidence that exists to date, because it is actually so much easier than we realize to redesign work to make it more fair.

[Farnoosh Torabi]

On a sort of related note, Siri, your work is so embedded in gender equity in the workplace at Harvard, and I'm sure you're seeing the data around more women leaving the workforce. It started obviously during the pandemic. I thought we were back to normal. And then we were right.

[Siri Chalazi]

We reached the highest level of women's workforce participation in the United States ever at the end of 2024, at I believe, 78 point something percent. Yeah.

[Farnoosh Torabi]

So what's going on? Last year was not, not great for women in the workplace. What happened?

[Siri Chalazi]

Yeah, 2025, we saw a downtick in women's workforce participation, particularly big losses among black women in the workplace. I think part of that is connected to the types of jobs that saw the most significant downsizing in 2025. The federal government fired a ton of people and women of color were disproportionate. They had above a sort of higher representation, higher than proportional representation in those jobs. We of course know that inside many organizations and in the private sector, DEI related roles, culture and people, related roles took a disproportionate hit. And again, those roles were disproportionately populated by women and people of color. So that's part of the story. I'm always cautious to try to understand a trend while it's actively unfolding, unfolding, because sometimes the passage of time causes you to see things differently. So in the early days of the pandemic, this is a great example, in the spring and summer of 2020, everyone was panicking about women leaving the workforce en masse, which it did look like, right? The numbers didn't lie in the moment. But then a few years later, because of the increased availability of flexible working, remote working, as I mentioned, women's workforce participation rates bounced back and went up to their highest levels ever. So what's happening right now is real and it's cause for concern, but it could turn out to be A blip. Just like the pandemic era dips did.

[Farnoosh Torabi]

Another thing we saw during the pandemic which has gone away is this flexible work working from home. We had to during the pandemic and then companies who it was working, they stuck with it. But now there's also this push to go back to work in the office five days a week. And I'm wondering how that plays into the context of fairness. Because if you are an employee who can be more productive working at home instead of commuting, like how does that, how should employers think about that? And is it fair to ask everyone to come five days a week? Everybody? Yeah.

[Siri Chalazi]

This question of flexible work is one where I see so many decisions being driven by ideology and leaders gut instincts rather than the data and the evidence. And we actually have so much evidence from around the world world for decades already, not just in the last five years. That shows that if you do it right and design it well, remote work and the availability of flexible working assign arrangements can be the big one of the biggest drivers of fairness and also one of the biggest drivers of your organizational performance because you actually retain your best talent and you allow people, when we allow people to self select into the working arrangements that work best for them. Those people who are more productive at home work mostly from home. And those people who know that they're.

[Tara Davis Woodhull]

More productive in the office, it turns.

[Farnoosh Torabi]

Out they go to the office.

[Siri Chalazi]

So everybody wins. And on the flip side, we have some brand new data from the tech and finance sectors in the US just in the last few years that shows that when big tech and finance employers implemented these return to office mandates forcing everybody to come back, they saw huge talent drainage and who was most likely to leave it was disproportionately women, disproportionately more senior employees and employees with more skills and more other options because they said, oh, if you're not going to allow me to work the way I want to, I know that I'll find another employer who will. So these companies were really just shooting themselves in the foot. And I know what you mean about fairness because I saw this in many workplaces during the pandemic where when we started to come back, the kind of argument from employers was it's not fair that someone gets to work from home and someone else doesn't. So we have to make all of you come back and sit in front of your computers in the office. But then I said, how come you pay the janitor and the CEO different salaries? Because they do different jobs, right?

[Tara Davis Woodhull]

Their Roles, what they actually do on a daily basis are very different.

[Siri Chalazi]

We have no trouble understanding that when people do different roles, they should get paid differently. So how come if someone works fully on a computer, we don't recognize that.

[Tara Davis Woodhull]

It makes sense for them to have.

[Siri Chalazi]

The flexibility to do it from wherever they want to. Whereas, of course, someone like a janitor or food service worker has to come in because they can't clean remotely. So it's just faulty logic or missing logic. And those were the questions that I was asking leaders is, wait a second, how come it's okay for you to pay people differently but then not give them different work arrangements depending on the role and the task that they're doing?

[Farnoosh Torabi]

Yeah, fair point. See what I did there?

[Siri Chalazi]

Nice.

[Farnoosh Torabi]

How did you get into this work? And I would love a personal story maybe that drew you to this. Such important work that you do. An example of feeling the unfairness, witnessing it, or seeing the bias even in yourself, to say, you know what, I want to really dive into the data and research this and help people.

[Siri Chalazi]

It was really my own real world experience, actually. I would say that even though the educational system is not perfect, it does a better job than the workplace of insulating people from the worst manifestations of unfairness. So for me, elementary, middle, high school, college, I honestly never felt like there was any gender bias in the world. But it hit me in the face as soon as I graduated and got my first job in management consulting. I'd look at my peers at the entry level, 50, 50 women and men, tons of diversity. And then I'd look to the top, to the part, partnership. And at most, 10% of partners were women.

[Farnoosh Torabi]

Right?

[Tara Davis Woodhull]

There was a very typical mold of.

[Siri Chalazi]

Person who was a partner at that firm. Like in all consulting firms, I would see women who I personally worked with, who were super capable, not advancing as fast as men who I also work with, who I deemed to be pretty.

[Tara Davis Woodhull]

Mediocre based on my firsthand experience with them. I saw senior leaders in the firm who were brain makers behaving very badly.

[Siri Chalazi]

And that bad behavior was overlooked because they were the point person for the biggest account. So we just have to live with it, right? So I started, started experiencing all these things firsthand and realized, oh my gosh, it's the 21st century and this is still happening. I cannot believe that these problems haven't been fixed by now. So it was really living that reality firsthand that galvanized for me that I wanted to make my lives work, helping companies be better, be more fair, actually create workplaces that offer everyone an opportunity to find the job that they love and then do their best work and be fairly rewarded for it.

[Farnoosh Torabi]

Siri Chalazi, thank you so much. This is such an important conversation. I hope you'll come back. I know you have.

[Siri Chalazi]

Thank you for a lot of lives.

[Farnoosh Torabi]

To change with this book.

[Tara Davis Woodhull]

Truly we're trying right? The work won't be done anytime soon, but I hope that everyone listening will.

[Siri Chalazi]

Have gotten some small idea from this conversation of something small that you can do in your own own work today without requiring any budget or anybody else's buy in. But just start creating a better workplace for you and your team.

[Farnoosh Torabi]

I love that. Oh my gosh. Make Work Fair. Thank you so much.

[Tara Davis Woodhull]

Thank you Farnuj.

[Farnoosh Torabi]

Thanks so much to Siri Chalazi for joining me.

[Narrator/Host]

Her book again is called Make Work Fair.

[Farnoosh Torabi]

I'll link to it in our show notes and I'll see you back here for a fresh episode of Ask Farnie this Friday. I hope your day is so money.

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[Siri Chalazi]

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[Siri Chalazi]

Now.