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Chief in Tech S1E24 - Lori Nishiura Mackenzie : The Power of Our Collective – Reimagining Inclusion · Chief in Tech Deep Dive Shortcast

• 0:00
  What if the smoothest, most agreeable meeting
• 0:03
  you had today was actually a complete failure?
• 0:07
  I mean, that's a wild thought, right? Because
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  we usually love those meetings. Right. Think
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  about it. Everyone just nodded. No one stepped
• 0:12
  on any toes. And you reached consensus in what,
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  10 minutes flat? And you walk out feeling like,
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  wow. We are incredibly efficient. Exactly. It
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  feels great. But according to the research we're
• 0:25
  digging into today, that exact lack of friction
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  might actually be blinding your team to critical
• 0:31
  missing information. Yeah, it completely flips
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  the script on what we consider a successful dynamic.
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  It really does. So welcome to the deep dive.
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  Our mission today is to unpack this really thought
• 0:44
  -provoking talk by Laurie Nashirah Mackenzie.
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  It's called The Power of Our Collective, Reimagining
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  Inclusion. And for anyone who, you know, wants
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  to be well informed on team dynamics and organizational
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  behavior, But maybe without drowning in academic
• 0:59
  papers, this is perfect. Yeah, we're going to
• 1:01
  look closely at her arguments because she systematically
• 1:03
  challenges all this conventional wisdom about
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  what a highly functioning group actually looks
• 1:07
  like. It is a fascinating analysis because it
• 1:10
  forces us to examine the foundational metrics
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  of success. I mean, we are trained to view harmony
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  as the ultimate indicator of a healthy environment.
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  Right. Like if everyone's smiling, we're doing
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  it right. Exactly. But Laurie's perspective proposes
• 1:25
  that true inclusion is not about comfort at all.
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  In fact, she argues it's inherently designed
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  to be, well, somewhat difficult. And to understand
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  why she makes that argument, we kind of need
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  to look at the personal story she uses to ground
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  her whole thesis. Yeah, it's a really powerful
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  starting point. It is. So she describes being
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  just six years old, walking to the local library
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  with her mother, and it's just this perfectly
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  normal happy day. Right. Nothing out of the ordinary.
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  Yeah, but then this car drives by and it slows
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  down and the men inside lean out the window and
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  start making these like mocking fake Chinese
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  noises at her. It's a jarring illustration of
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  how certainly the external world can impose this
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  this narrative on you. Exactly. And the reaction
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  from her mother, who, by the way, Laurie describes
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  as a very gentle person, her reaction was immediate.
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  What did she do? Without missing a beat, her
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  mother gave those men the bird. Oh, wow. Yeah.
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  just flick them off right there on the street.
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  And for a six -year -old Lori, this crystallized
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  two huge things. Which were? First, that simply
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  based on physical appearance, you know, some
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  people just flat out refuse to see you for who
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  you are. And second, you always have the agency
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  to stand up against that discrimination. What's
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  fascinating here is how this childhood realization
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  scales into broader societal patterns. Yeah,
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  how so? Well, Lori points out that while she
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  learned this at six, many individuals, particularly
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  in the black community, encounter this reality
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  at a much younger age. Right. It's not always
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  a dramatic street encounter either. Exactly.
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  Or for others, the realization might happen in
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  a classroom, you know, like when a student enthusiastically
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  raises their hand and the teacher just systematically
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  ignores them in favor of other kids. Yeah, that
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  feeling of just being invisible. Right. And Laurie
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  uses these lived experiences of being unseen
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  or underestimated as a starting point for debunking
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  three specific myths about corporate inclusion.
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  OK, let's unpack this, because if the starting
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  point is acknowledging that these biases exist,
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  then Laurie's framework requires us to totally
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  rethink the end goal of bringing people together.
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  Which leads directly into the first major myth
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  she tackles, this idea that Inclusion equals
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  ease. Yeah, because we assume the goal is a room
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  full of people getting along perfectly. Right.
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  We think smooth sailing means we're doing great.
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  But to dismantle that myth... Laurie turns to
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  this landmark study by the late researcher Catherine
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  Phillips, who investigated jury deliberations.
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  Oh, juries. That's a super high stakes environment.
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  Highly pressured, very consequential decisions.
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  The setting is crucial here. And in the U .S.
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  legal system, the attorneys are the ones selecting
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  the jury, which means you can end up with vastly
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  different compositions. Exactly. Sometimes you
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  get a highly homogeneous jury where everyone
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  shares a similar background, and sometimes you
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  get a highly diverse jury. OK, so what did the
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  researchers actually do? Well, They wanted to
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  observe if the composition of the jury fundamentally
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  changed the mechanics of how they deliberated.
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  And what did they find? The initial data point
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  they found seems on the surface like an argument
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  against diversity. The diverse juries actually
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  took significantly longer to deliberate than
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  the homogenous ones. Wait, really? Because if
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  an organization is purely optimizing for speed
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  and efficiency, taking longer sounds like a structural
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  flaw. It does. But taking longer isn't a flaw
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  if the output is better. Ah. So what did they
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  find when they looked at the actual quality of
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  the decisions? They found that taking longer
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  was actually a feature of the diverse group,
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  not a bug. They evaluated whether the juries
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  made factual errors when reviewing the evidence.
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  And the data showed that the diverse juries made
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  significantly fewer mistakes. But, and this is
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  the key part, the underlying mechanism is what
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  makes this study so important. What were they
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  doing differently? The diverse juries were uniquely
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  capable of noticing missing information. For
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  example, they'd examine the records and realize,
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  hey, the documentation states there were three
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  eyewitnesses to this event. But we've only been
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  provided testimony from two of them. Where is
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  the third? Oh, wow. And the homogenous juries
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  just missed that. Routinely. They were moving
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  quickly and comfortably, so they routinely failed
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  to catch that missing data. I have to push back
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  on the mechanics of that, though. Like, is it
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  possible the diverse jury just happened to possess
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  different external knowledge. What do you mean?
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  Like, did they just know the neighborhood better
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  or understand a specific cultural context that
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  gave them, you know, inside information about
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  the crime? No, and that is the most critical
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  takeaway from Catherine Phillips's research.
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  The diverse juries did not possess secret inside
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  knowledge about the case. Then why were they
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  so much sharper? The underlying mechanism that
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  improved their performance was simply the presence
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  of dissent. Dissent. Just disagreeing. Yeah.
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  Think about it. When you're sitting in a room
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  with people who share your background, your brain
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  relies on cognitive shorthand. You assume a baseline
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  consensus which allows you to coast. Right. You
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  just sort of nod along. Exactly. But when you're
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  in a room with people who are demonstrably different
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  from you and they start asking questions, it
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  introduces cognitive friction. It wakes you up.
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  Literally. Hearing dissent from someone with
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  a different perspective forces your brain to
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  wake up and reevaluate the evidence more rigorously.
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  It makes me think about physical training. Like,
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  if you go to the gym and lift a weight that offers
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  absolutely zero resistance, your muscles aren't
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  actually getting stronger. Right. You're just
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  panting and going through the motions. Yeah.
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  You're just wasting time. Laurie's argument suggests
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  that inclusion isn't about creating a smooth
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  ride. It's about introducing constructive friction.
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  The resistance is what builds the intellectual
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  muscle of the group. That is a highly accurate
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  way to conceptualize the cognitive science behind
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  it. Growth and rigorous analysis happen in the
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  space of discomfort. So, according to the framework
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  presented in the talk, how do organizations mechanically
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  apply this? Laurie suggests two actionable shifts.
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  The first is altering meeting norms. You know,
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  norms are just the habitual unspoken rules of
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  engagement. Like letting a meeting just naturally
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  rush toward a comfortable consensus. Exactly.
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  Instead of doing that, Leaders must explicitly
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  design a norm that mandates dissent. Meaning
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  you literally have to ask for the friction. Yes.
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  Before finalizing any major decision, the person
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  running the meeting should ask, can anyone provide
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  one solid, evidence -based reason why we should
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  not move forward with this? Oh, that's smart.
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  By formalizing the question, you completely remove
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  the social penalty for disagreeing. You make
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  it part of the job. And the second shift involves
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  mindful listening. What does the data say about
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  that? Well, Laurie cites organizational research
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  demonstrating that in a standard group of eight
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  people, just three of those individuals will
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  dominate 67 % of the speaking time. Which honestly
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  isn't surprising to anyone who has ever worked
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  in a corporate environment, right? The loudest
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  voices naturally expand to fill the available
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  space. Absolutely. But the question is how to
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  mechanically dismantle that dynamic. According
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  to Laurie, inclusion means fundamentally redefining
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  how we measure participation. It's not about
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  rewarding the people who are simply the quickest
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  to speak. Because quick doesn't always mean correct.
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  Right. It requires the meeting facilitator to
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  actively manage the airtime, deliberately making
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  space for the quieter voices. Because those are
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  often the voices holding the positive dissent
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  that will ultimately make the final decision
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  more robust. Okay, so if we accept the premise
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  that cognitive friction and dissenting voices
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  make a team demonstrably smarter. If they're
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  the key to finding that missing third eyewitness,
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  why are those specific voices so frequently filtered
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  out before they even get a seat at the table?
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  That is the big question. And it leads us straight
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  into Laurie's second myth. This widespread belief
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  that professionalism is a purely empirical objective
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  standard. Oh, this is a deeply entrenched concept
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  in corporate culture. Organizations operate on
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  the assumption that their standards for evaluating
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  talent and work product are completely neutral
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  and merit based. Right. And Laurie shares this
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  fascinating study about evaluating legal briefs
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  that completely dismantles that assumption. Oh,
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  the legal brief study is incredible. It really
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  is. So the researchers created a single standardized
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  legal brief. allegedly written by a third -year
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  law associate. Crucially, they intentionally
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  seeded this document with a specific number of
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  errors. Like what kind of errors? Typographical
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  mistakes, factual inaccuracies, and logical flaws.
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  Just a real mix. They then sent this exact same
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  brief to multiple law partners for evaluation.
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  The methodology here is brilliant because they
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  isolated a single variable. Exactly. Half of
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  the law partners received the brief with a cover
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  letter, subtly implying the author was a white
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  associate. And the other half? The other half
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  received the identical brief, but the cover letter
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  implied the author was an African -American associate.
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  Now, if I am playing devil's advocate here, I
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  have to ask how bias can possibly alter the evaluation
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  of a standardized document. Right, because a
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  typo is an empirical fact. A legal error either
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  exists on the page or it doesn't. Shouldn't the
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  work product just stand on its own objective
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  merit? If we connect this to the bigger picture
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  we see why it doesn't. If human beings operated
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  like algorithms, yes. But human psychology relies
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  heavily on heuristics, you know, mental shortcuts.
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  Ah, so confirmation bias comes into play. Exactly.
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  Preconceived notions don't just change our final
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  opinion. They dictate the actual level of scrutiny
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  we apply to a task. Wait, so they actually graded
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  them differently? Yes. The study found that the
• 11:06
  partners who believed they were reading a brief
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  written by an African -American associate found
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  significantly more of the exact same intentionally
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  planted errors. because they unconsciously expected
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  a lower quality of work, so their brains actively
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  hunted for flaws. Bingo. Consequently, they scored
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  the exact same documents significantly lower
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  than the partners who believed a white associate
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  had written it. So the bias acts as a... literal
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  magnifying glass. Yeah, the expectation of a
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  flaw structurally alters how the evaluator reads
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  the document. That's terrifying, honestly. If
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  our definition of professionalism is that susceptible
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  to unconscious bias, what does Laurie propose
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  as a solution for evaluating talent? Her argument
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  is that organizations must aggressively interrogate
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  the vague gatekeeping terminology they use during
• 11:52
  performance reviews and hiring. Oh, think about
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  how often talent is evaluated using phrases like
• 11:58
  executive presence or gravitas. Right. Someone
• 12:02
  gets passed over for a promotion because leadership
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  claims they just lack executive presence. But
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  like, what does that actually mean on a measurable
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  level? Laurie argues that often these terms are
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  simply coded language. It really just means this
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  person does not look, speak or act like the leaders
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  we have historically promoted. It's just a mirror
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  for the status quo. Exactly. To counter this,
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  she suggests organizations need to shift toward
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  what psychologist Carol Dweck calls a growth
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  mindset. Let's unpack the mechanics of that,
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  because growth mindset is a term that gets thrown
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  around a lot in corporate seminars. But how does
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  it specifically apply to dismantling biased professionalism?
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  Well, in traditional hiring, organizations often
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  operate with a fixed mindset, meaning they look
• 12:45
  for a finished product. They just look at the
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  endpoint, like, did this candidate attend a prestigious
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  university? Do they possess a specific, polished
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  communication style? Right. A growth mindset,
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  however, operates on the belief that skills and
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  capabilities are dynamic. When evaluating a candidate,
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  you don't just look at their current coordinates,
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  you evaluate their trajectory. So it's about
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  the journey. Yes. Laurie argues that evaluators
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  need to ask, what specific systemic barriers
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  did this individual have to overcome simply to
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  get to this interview chair? Wow, that completely
• 13:20
  changes the framing. It does. When you value
• 13:22
  the resilience, the adaptability, and the distance
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  traveled, you stop allowing narrow, subjective
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  definitions of professionalism to blind you to
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  a highly capable talent. That makes perfect sense.
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  So let's follow the logical progression of Laurie's
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  framework here. An organization adopts this growth
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  mindset. They successfully bypass their own biases
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  and bring these diverse, dissenting voices into
• 13:43
  the room. Now they get them in the door. But
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  how does the organization actually support them
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  once they're there? Which brings us to the third
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  myth. The more is better trap. Ah, yes. This
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  is the assumption that the most effective way
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  to foster inclusion is through broad overarching
• 13:59
  diversity initiatives. It's basically the default
• 14:01
  setting for many large organizations. The instinct
• 14:04
  is to cast the widest net possible, creating
• 14:08
  massive generalized programs under the assumption
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  that, you know, a rising tide lifts all boats.
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  Here's where it gets really interesting, though.
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  Laurie points out that relying on massive data
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  sets creates dangerous blind spots. What kind
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  of data is she looking at? She cites a Google
• 14:24
  technical workforce report to illustrate this.
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  According to the data she highlights, less than
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  half a percent of Google's technical workforce
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  are Black women and less than one percent are
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  Latinx women. Those are tiny percentages. Exactly.
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  If an organization looks at those microscopic
• 14:39
  numbers and decides the solution is to group
• 14:41
  them into a massive generalized women's employee
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  resource group simply because more is better,
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  they are entirely ignoring the highly specific
• 14:49
  realities those individuals face. Right. Because
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  when you aggregate data at that scale, the unique
• 14:55
  experiences of the extreme minority are completely
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  washed out by the majority within that same demographic
• 15:02
  group. It's like using a giant paint roller to
• 15:05
  touch up a really highly detailed portrait. That's
• 15:07
  a great analogy. Yeah, sure, you cover a lot
• 15:09
  of canvas quickly, but you completely obliterate
• 15:12
  the fine details. It's like a hospital deciding
• 15:15
  to prescribe a broad spectrum antibiotic. to
• 15:18
  every single patient in the building just to
• 15:20
  save time. Right. Sure, it might accidentally
• 15:23
  cure a few people with generic infections, but
• 15:26
  it completely ignores the highly specific, sometimes
• 15:30
  critical diagnoses of the individual patients.
• 15:32
  The broad approach actually becomes a form of
• 15:35
  medical or, in this case, corporate neglect.
• 15:37
  That is a very precise way to understand the
• 15:40
  mechanism of failure here. And to prove why the
• 15:42
  broad spectrum approach fails, Laurie brings
• 15:45
  in research conducted by Anita Rattan and Carol
• 15:47
  Dweck at the London Business School. Okay, what
• 15:49
  did they look at? They surveyed over 400 African
• 15:52
  -American employees across various organizations.
• 15:55
  And what did the data reveal? The data revealed
• 15:57
  that 67 % of these employees reported spending
• 16:01
  a portion of their workday actively dealing with
• 16:04
  racial comments. 67 %? That is wild. And the
• 16:09
  research makes clear these were not just subtle
• 16:11
  misunderstandings. They included overt stereotypes,
• 16:15
  assumptions of laziness, racial slurs, and baseless
• 16:18
  references to criminality. Which means these
• 16:21
  employees are essentially working a second shift.
• 16:23
  Exactly. They are expending massive amounts of
• 16:26
  cognitive and emotional energy navigating hostility
• 16:28
  while simultaneously just trying to perform their
• 16:31
  actual job duties. And that emotional labor is
• 16:33
  exactly what drives turnover. However, the study
• 16:36
  also identified a mechanical lever for improvement.
• 16:39
  What was it? They found that when organizational
• 16:42
  leaders actively and specifically addressed those
• 16:45
  incidents, when they didn't just release a generic
• 16:48
  statement about corporate values, but explicitly
• 16:50
  tackle the specific racial bias occurring in
• 16:53
  their teams, the retention rates for those marginalized
• 16:55
  employees increased. Let's explore the why behind
• 16:59
  that data point. Why does addressing the specific
• 17:01
  comment directly move the needle on retention?
• 17:04
  Psychologically, it restores a sense of psychological
• 17:06
  safety and validates the employee's lived reality.
• 17:10
  It makes them feel seen. Exactly. When leadership
• 17:13
  acknowledges a specific harm, it shifts the burden
• 17:16
  of managing that toxic environment off the individual
• 17:19
  employee. and places it onto the organization
• 17:21
  where it belongs. So what's the actionable takeaway
• 17:25
  Lori extracts from this research? She says organizations
• 17:28
  must radically shift their feedback mechanisms.
• 17:32
  Instead of relying solely on massive, anonymous,
• 17:34
  company -wide surveys that round out the margins,
• 17:37
  leadership must conduct specific focus groups
• 17:39
  and targeted one -on -one interviews. They have
• 17:42
  to ask the difficult questions to understand
• 17:44
  the daily frictions experienced by the less than
• 17:47
  1%. And according to Lori, They have to be prepared
• 17:50
  to confront some very ugly realities that emerge
• 17:52
  from those targeted conversations. Like what?
• 17:55
  It means addressing the fact that a black software
• 17:57
  engineer might be asked to clear away dishes
• 17:59
  in the corporate cafeteria. Or that Latinx women
• 18:02
  in senior roles are continually asked if they
• 18:04
  are part of the cleaning staff. Wow. You definitely
• 18:07
  cannot fix highly specific stereotyping like
• 18:10
  that with a generic empowerment seminar. No,
• 18:13
  you can't. Laurie's proposed solution to this
• 18:15
  is engaging with initiatives like the IM movement.
• 18:18
  What is that? This is a structured exercise utilized
• 18:21
  in organizational psychology, where individuals
• 18:24
  are encouraged to articulate their multifaceted
• 18:27
  identities to their colleagues. How does that
• 18:29
  actually work in practice? Like, what is the
• 18:31
  mechanism of the I Am exercise? In a facilitated
• 18:34
  setting, employees share statements that embrace
• 18:37
  their full complexity. For example, someone might
• 18:40
  say, I am a mother, I am a senior developer,
• 18:43
  I am Latina, I am a marathon runner. Oh, I see.
• 18:47
  The psychological mechanism at play here is cognitive
• 18:50
  disruption. By forcing colleagues to see the
• 18:53
  intersectional complex reality of an individual,
• 18:56
  you break the brain's reliance on flat, one -dimensional
• 18:58
  stereotypes. It demands that the organization
• 19:01
  see the employee for their authentic complexity,
• 19:04
  rather than just flattening them to fit comfortably
• 19:06
  into a broad demographic category. It requires
• 19:08
  a tremendous amount of intentionality to design
• 19:11
  a culture that way. Which really brings us to
• 19:13
  the ultimate question underlying this entire
• 19:16
  deep dive. What is the point? Yeah, why do all
• 19:18
  this work? Why should an organization or an individual
• 19:22
  voluntarily endure the friction of dissent, the
• 19:25
  discomfort of interrogating their own biases,
• 19:28
  and the hard work of addressing these specific
• 19:31
  painful realities? It's a lot to ask. It is.
• 19:34
  And to answer that, Laurie closes her talk by
• 19:37
  stepping away from the corporate data and sharing
• 19:39
  a deeply moving historical account about her
• 19:41
  great grandfather and his brother. It serves
• 19:43
  as a powerful anchor for her entire thesis, reminding
• 19:47
  the audience of the historical stakes of inclusion
• 19:49
  and exclusion. Yeah. She explains that during
• 19:52
  World War II, despite being naturalized American
• 19:55
  citizens who had built their lives in the United
• 19:57
  States, her great grandfather and his brother
• 20:00
  were sent to Japanese -American internment camps.
• 20:02
  Which is just a profound example of a systemic
• 20:05
  refusal to see individuals for who they truly
• 20:07
  are. Exactly. The government systematically stripped
• 20:10
  them of their rights, their property, and their
• 20:12
  dignity. entirely based on their heritage. But
• 20:15
  the story doesn't end there, does it? No. Laurie
• 20:18
  explains that after the war, when they were finally
• 20:20
  released, they did not retreat into isolation.
• 20:24
  Instead, they made the deliberate choice to build
• 20:26
  a Buddhist temple in San Jose, California. They
• 20:29
  chose to construct a physical and spiritual sanctuary?
• 20:32
  Yes. They wanted to create a community gathering
• 20:35
  place. A space where people who had been violently
• 20:38
  excluded could come together, pool their collective
• 20:41
  strength, and systematically rebuild their lives.
• 20:44
  That's incredible. And that temple is still standing
• 20:47
  and operating today. This raises an important
• 20:50
  question, which Lori poses as a final synthesis
• 20:52
  for her audience. What temple are you building?
• 20:55
  I love that framing. Her argument is that the
• 20:58
  true silver lining of living through fractured,
• 21:01
  often divisive times, is the opportunity it presents.
• 21:04
  We have a rare historical chance to build a much
• 21:07
  bolder, more rigorous vision of inclusion. A
• 21:09
  place where people aren't just tolerated. Right.
• 21:12
  We can construct workplaces and institutions
• 21:14
  where the unique complex value of every single
• 21:17
  individual is deeply known and utilized. But
• 21:20
  as we have learned today, building that temple
• 21:22
  requires every piece of the collective. It requires
• 21:25
  the friction of differing opinions, the discipline
• 21:28
  of a growth mindset, and the willingness to look
• 21:31
  closely at the fine details rather than panting
• 21:33
  over them with broad strokes. It is definitely
• 21:36
  not easy, but the things that are built to last
• 21:39
  never are. So true. Before we wrap up, I want
• 21:42
  to leave you with a final lingering thought to
• 21:45
  mull over. Okay, let's hear it. We spent our
• 21:47
  time today analyzing the idea that dissent, differing
• 21:51
  perspectives, and constructive friction are the
• 21:54
  fundamental mechanisms that make a group smarter.
• 21:56
  It is the friction that helps us spot the missing
• 21:58
  information, like that elusive third eyewitness
• 22:02
  in the jury study. Right, the cognitive resistance
• 22:04
  is the prerequisite for rigorous thinking. Exactly.
• 22:07
  But if that premise is true... How might the
• 22:11
  algorithms and AI feeds we interact with every
• 22:13
  single day be affecting us? Oh, that's a brilliant
• 22:14
  point. Right. We are increasingly relying on
• 22:17
  tools that are mathematically designed to optimize
• 22:20
  for our comfort, agree with our preferences,
• 22:23
  and seamlessly feed us consensus. They literally
• 22:26
  engineer the friction out of our lives. Yes.
• 22:28
  So could the absolute lack of friction in our
• 22:31
  digital diets be accidentally blinding us to
• 22:34
  the most important missing information in our
• 22:36
  own lives? It is a critical question about how
• 22:39
  we manage our own intellectual environments.
• 22:42
  Thank you for exploring these complex dynamics
• 22:44
  with us today. It has been a privilege to share
• 22:47
  this analysis with you. Keep asking the hard
• 22:49
  questions and we'll see you next time.