WEBVTT

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Matt Abrahams: Swift trust can
help your communication and

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your teams be more effective.

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My name's Matt Abrahams, and I
teach Strategic Communication at

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Stanford Graduate School of Business.

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Welcome to Think Fast,
Talk Smart, the podcast.

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Today, I look forward to
speaking with Melissa Valentine.

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Melissa is an associate professor in
the Management Science and Engineering

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Department at Stanford and a senior
fellow at the Stanford Institute for

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Human-Centered Artificial Intelligence.

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Her research focuses on how emerging
technologies, including artificial

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intelligence and algorithms, are
fundamentally transforming work,

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organizational design, and team dynamics.

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Melissa, along with her co-author
Michael Bernstein, wrote the fascinating

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book Flash Teams: Leading the Future
of AI-Enhanced, On-Demand Work.

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Well, welcome, Melissa.

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I'm really excited to have you join us.

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Thank you.

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Melissa Valentine: This show is
so fun, and I love the guests you

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have, so I'm delighted to be here.

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Matt Abrahams: Well, thank you,
and thanks for being one of them.

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Shall we get started?

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Melissa Valentine: Let's do it.

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Matt Abrahams: Excellent.

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I have to say, I really enjoyed
your book, Flash Teams, very much.

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Really, really interesting.

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Can you define for all of us what a
flash team is and explain what people,

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processes, and infrastructure enable flash
teams to get aligned and execute quickly?

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Melissa Valentine: Yeah.

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So my PhD is in organization
science, basically.

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So I got my PhD at a business school,
and then my collaborator is a computer

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science professor, and he was doing
a lot of work on crowdsourcing.

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So what's cool about crowdsourcing is
the crowd is, like, millions of people

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online, and you can get things done
quickly 'cause you just put a task out,

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and then there's millions of people who
are available to come work on the task.

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But what he was seeing at the time
that he and I started working together

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was crowdsourcing was stuck because
they were doing, like, really,

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they called them micro tasks, but
just really, like, small tasks.

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And then I had this toolkit, organization
science, and my dissertation had been

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about how you can use team scaffolds or
lightweight team structures, and then you

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populate the team structure with experts.

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And the team structure and
the role structure helps them

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know how to work together.

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So we sort of were able to combine
the logic of both of these.

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So you have these, like, lightweight
structures that allow people who are,

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like, relative strangers to come together
and work together on really complex stuff.

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So this system that we built with a
great team of a PhD student, Daniela

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Ratelny, she organized this great lab at
the time we first did our flash teams.

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So we built a platform that basically
took all the logic of organization

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science and team science, and then
the speed and scale of crowdsourcing,

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and then put them together.

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So the way the system works, you have
this platform where I'm somebody who

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wants to get something done, so I go
to the platform, I design the team,

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and then the platform integrates
with something like, we used Upwork.

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So there's like 10 million
freelancers who are on Upwork.

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And then, so I'll say, "Here's the task
that I need done. Here's the role I

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need filled." And then the platform can
integrate with Upwork, and then it's

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open call to the 10 million freelancers.

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Who's got the right expertise?

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They join the team.

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So you can just convene teams really fast.

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And what we showed with this
research is that you can get

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things done really quickly.

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You can pull teams together.

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They build really complex stuff.

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And it was really inspiring.

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I mean, it's even faster now with GenAI.

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Matt Abrahams: So you set a framework
and expectations and then leverage a

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tool that pulls people in, and then
the flash team is really the focused,

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concerted effort that it's all about.

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One of the essential elements
of any teaming or groups

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coming together is trust.

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What are some of the communication
skills or other skills that people

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can deploy to establish trust quickly?

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I'm assuming part of what flash teams
do, besides accomplish their work,

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is they're able to coordinate action,
perhaps through building trust.

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Melissa Valentine: Yeah, trust in flash
teams is essential and complex, right?

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'Cause it is relative strangers.

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You get together and you work
together really intensely,

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and then you disassemble.

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So I think that there's this idea in the
literature called swift trust, and there's

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an assumption that you just assume trust.

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You just meet somebody for the first
time, you assume they're competent, you

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assume that they know how to do their
role, you assume you're both there for the

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same reason, to work hard, get it done.

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So that, yeah, the assumption
of swift trust is really useful.

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It doesn't always work out,
but the sort of like offering

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of swift trust is part of it.

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And then paying attention to when it's
not going right and being willing and

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able to repair quickly is also important.

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Matt Abrahams: I love
this idea of swift trust.

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So you approach from a place of trust,
assuming that you are trustworthy,

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and I will trust you, and you will
do the same, can expedite things.

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Because there's a lot of this testing that
goes into trust and time, and if you start

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from that place, and obviously it might
fail or people could take advantage of it.

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But the second part, what you said,
I think really is the helpful part,

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is to have that meta-awareness and
watching for it, and then being willing

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to speak up and try to repair it.

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So I think it's not only swift
trust, being open to trust, but being

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open to repair when it's not there.

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I really like that idea of swift trust.

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So much in my life I think would
be better if we just approached

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everything with this notion of like,

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Melissa Valentine: Oh, swift trust.

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Yeah.

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Yeah.

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I mean, there is a real difference
'cause I think of the person I wrote

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the book with, Michael, he and I
have worked together for 15 years

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now, and that is a different kind
of trust than like swift trust.

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But swift trust is a tool that's useful.

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Matt Abrahams: Right.

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It's, and it's a way to at least
initiate and then you can build

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deeper, the trust and relationship.

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That can only happen, I think,
after repeated exposure and time.

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You talk about discursive diversity,
and I had to practice saying

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that multiple times, by the way.

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Can you share what you mean by
discursive diversity, and how can

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teams recognize when they need to shift
their communication style from a more

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open-ended brainstorming, ideating to
a very highly coordinated approach?

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Melissa Valentine: Yeah.

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So that is from the dissertation of one
of my really brilliant PhD students.

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So her name is Katharina Lix,
and she invented that measure.

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So what she was able to do, she
had all of the Slack transcripts of

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different flash teams, and she was
able to, she did this NLP processing.

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Matt Abrahams: And NLP is natural
language processing, I assume.

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Melissa Valentine: Yeah, yeah.

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Before it was cool, she learned
how to do it, and she was able to

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create this measure where she was
looking at the similarity of the

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language that people were using.

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So you have all of the Slack
interactions, and you can basically

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compare people talking on the team and
how similar are the words that they're

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using, the sentence structure, right?

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Are they using the same
adverbs, like adjectives?

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Sense of urgency gets
encoded in all of that.

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And what she was able to show is that the
similarity of the language that people

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are using or the difference, so this is
where, let's see, discursive diversity.

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Matt Abrahams: Discursive diversity.

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Yeah.

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Melissa Valentine: Yes.

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Matt Abrahams: Different
types of words and language.

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Melissa Valentine: Exactly.

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Yeah.

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So that sort of would predict the team
meeting a milestone in different ways.

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So there were times when you really
want the language to diverge.

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So this is a moment of
brainstorming, ideation, right?

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You want a lot of creativity,
you want a lot of divergence.

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But then as you get closer to
the deadline, you really, for the

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team to meet the deadline, then
the language needs to converge.

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Like, people need to start sounding more
like each other to hit the deadline.

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Matt Abrahams: So one,
it's a measure really.

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So you can look at, you know, if I'm a
manager or somebody looking back at doing

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a postmortem or after the project is done,
and I can look at the communication, be

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it Slack, Jira, whatever the tool is,
and I can actually see the, the language

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might be a hint as to where we are.

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And as you're trying to get closer to the
decision, more similar language is a sign.

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What I'd be curious, and I don't know if
there's any research on this, is can you

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actually use language to influence that?

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So can I, as a manager, encourage
more diverse language through

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ideation, but want us to start moving
towards a decision, encourage people

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to start using similar language?

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I wonder if you, if
it's causal in that way.

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Melissa Valentine: I think
that's a great research question.

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Matt Abrahams: Yeah.

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I think that's really interesting.

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So I encourage everybody listening to
think about the language you're using

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for the different tasks you have and
start to notice what that looks like.

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And maybe you can run your own
experiment and play with that.

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I want to keep on flash teams, and then I
want to make a, have a broader question.

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But when flash teams hit a snag, for
example, like a miscommunication, what

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is the most effective way to fix that
so they don't fraction and deal with

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too much friction in those situations?

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Melissa Valentine: So I'm so
glad you asked this question.

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I have an unpublished paper.

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So we ran three really complex flash teams
one summer, and we had all of the DMs.

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So we had all the Slack front stage and
then all of the Slack DMs, the backstage.

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And the thing that was really interesting
in analyzing all of that data is a

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lot of repairs happened backstage.

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So something would happen in the
public Slack channel, and then a dyad

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would go to the back channel, and
they'd be like, "What is this bug?"

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And they would sort it out and then
come front stage with the solution.

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So it created a lot of smooth operations.

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Like the flash teams, they
all accomplished their goal.

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There didn't seem to be a ton of conflict.

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So this pattern of backstage repair
was really interesting to discover.

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I think any human behavior,
it's got different sides to it.

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So I think it did
support smooth operation.

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But what I saw in the analysis that I
have not yet published is that the people

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who are more involved in backstage repair
ended up with more influence over time.

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So these are the workers and the
managers who were, like, really

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helping make the decisions.

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So it's something about access to where
the real problems get solved was, like,

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creating a lot of influence for people.

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Now, I don't totally know
what to do with that.

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As someone who is interested in flash
teams going well, I would maybe say you

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need like a postmortem on a flash team.

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What were the problems?

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Who helped solve them?

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What do we learn about this together?

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Matt Abrahams: It's really intriguing
that the people involved in that

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repair or that dealing with those
problems end up being more influential.

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Melissa Valentine: Yeah.

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'Cause it's like they had the
realer story of what was going on.

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And sometimes it was in the backstage
repair that decisions were made

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and then presented as if they were
quite done, if that makes sense.

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Matt Abrahams: That's really intriguing.

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I'm putting on my manager hat and thinking
if I were in the midst of any team, be

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it a flash team or a regular team, how
I could be aware that the folks who are

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involved in helping fix, repair, dive
deep into problems, what that means

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for them in terms of their currency and
how we interact on the public stage.

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And I just think it's interesting that
we now have these two channels and ways

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of communicating that can be measured.

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I know you think about
storytelling and change.

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How can everyday employees in an
organization use storytelling to drive

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broader systemic change and build
coalitions to help achieve whatever

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it is they're trying to achieve?

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Melissa Valentine: Yeah.

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So one of the studies that I did
when I first got to Stanford was

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actually of an academic cancer center.

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I saw stories be really
influential in this study.

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So it feels a little different than what
we've been talking about with AI and

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algorithms and so forth, but it still to
me is a study of organizational design,

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which is what I'm really interested in.

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What happened in this study, so I
was studying as this cancer center

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was trying to do a transformation.

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They were trying to decrease
the coordination burden on

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patients and their families.

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And during the study, there was a group of
patient advocates or activists who really

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wanted the cancer center to understand how
much coordination they were having to do.

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So the way that they made their case, this
is why I'm thinking of it, is they had an

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initiative they called Patient Stories.

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And so they went to great effort to
collect a lot of patient stories where

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patients just talked about, like a family
member had to quit their job to become

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the full-time coordinator for the patient.

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So they came up with
dozens of patient stories.

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And then in this paper that I have,
I analyze how they basically use

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the stories to make the case and
to spread the movement, spread the

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message across the cancer center.

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And at the end of the study, they had
convinced the cancer center to take

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on some of the coordination work.

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So it ends up being this end-to-end
story of patient stories, patient

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narratives actually changing
the organizational design, which

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is why I'm thinking about it.

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It was like a very powerful thing
that these patient activists did.

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Matt Abrahams: Stories can really
resonate and motivate people.

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Was there anything specific to the stories
that you think were really important?

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Was it the fact that the stories accounted
for all the specific coordination events,

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or was it the emotionality, or was it the
fact that these people just collected a

00:11:32.188 --> 00:11:35.007
bunch of stories and the cancer center's
like, "Wow, there are all these stories.

00:11:35.008 --> 00:11:36.068
We should probably do something"?

00:11:36.527 --> 00:11:39.097
Melissa Valentine: I think a lot of us
interface with the healthcare system,

00:11:39.137 --> 00:11:40.367
and we could just see ourselves.

00:11:40.377 --> 00:11:43.157
So the patient stories were just
like, "This is us. This is you

00:11:43.157 --> 00:11:46.187
and me." And then it illustrated
the problem really specifically.

00:11:46.237 --> 00:11:49.568
So somebody's sitting in a wheelchair
in a hallway 'cause they had been

00:11:49.618 --> 00:11:50.807
dropped or something like that.

00:11:50.817 --> 00:11:54.047
And so it's like, wait, like, I think
the cancer center is so full of people

00:11:54.048 --> 00:11:58.317
who care, and then hearing like the
specific instance in a really relatable

00:11:58.328 --> 00:12:01.248
story, they were just like, "Oh,
that's a problem that I can help with."

00:12:01.438 --> 00:12:02.247
Matt Abrahams: I think you hit on it.

00:12:02.287 --> 00:12:04.317
It's relatable and real,
and we can connect.

00:12:04.317 --> 00:12:04.788
Thank you.

00:12:05.536 --> 00:12:10.806
Can you take what you've learned about
flash teams and give us any insight

00:12:10.826 --> 00:12:12.545
that we can just apply to a normal team?

00:12:12.545 --> 00:12:15.526
So I've got a team that's been around
for a while, and we meet regularly.

00:12:15.866 --> 00:12:18.665
Is there any insight from your work
on flash teams that could perhaps

00:12:18.665 --> 00:12:22.146
help my team be more efficient,
feel more connected, ideate better?

00:12:22.576 --> 00:12:24.945
Melissa Valentine: One thing that Michael
and I used to say when we were writing the

00:12:24.945 --> 00:12:28.726
book, we were trying to think of what's
the mindset here that any manager would

00:12:28.726 --> 00:12:33.516
find empowering, and the phrase we came up
with is experts everywhere all the time.

00:12:33.845 --> 00:12:35.185
So you've got your trusted team.

00:12:35.445 --> 00:12:35.785
Great.

00:12:36.146 --> 00:12:38.415
Keep working together, taking good
care of each other, working hard,

00:12:38.616 --> 00:12:43.946
but really recognize that your
organization, the world, the internet,

00:12:44.256 --> 00:12:47.985
the world is just full of experts who
can help, and people like helping and

00:12:48.035 --> 00:12:49.705
bringing their expertise to something.

00:12:50.115 --> 00:12:53.525
So it's just having a mindset of
recognizing how much collaboration

00:12:53.545 --> 00:12:56.645
is available, how much expertise
is available, and maybe it,

00:12:56.655 --> 00:12:59.185
like, invites you to think of the
boundaries of the team a little more.

00:12:59.615 --> 00:13:01.436
Matt Abrahams: That's funny you said
that 'cause that was exactly the word I

00:13:01.436 --> 00:13:05.866
was thinking is porous, is that it can
be very easy to insulate a team and say,

00:13:05.875 --> 00:13:09.315
"This is the team," but being a little
more open and pulling in expertise.

00:13:09.566 --> 00:13:12.666
When I was managing a team, I
ran a learning and development

00:13:12.666 --> 00:13:16.036
group, and we had this very tricky
thing we had to train people on.

00:13:16.486 --> 00:13:20.916
And it turned out that somebody in the
company who was an admin was using our

00:13:20.916 --> 00:13:24.595
tool, and they actually knew how to do
things that we were trying to figure

00:13:24.596 --> 00:13:25.925
out how to train people on better.

00:13:26.225 --> 00:13:30.325
That person was an expert, and by
just dumb luck, we figured that out

00:13:30.325 --> 00:13:31.865
and incorporated them into the team.

00:13:31.995 --> 00:13:32.975
And I like that idea.

00:13:33.325 --> 00:13:35.485
Melissa Valentine: I think that
there are a lot of tools that can

00:13:35.486 --> 00:13:39.346
be very helpful to managers in terms
of how the team works together,

00:13:39.386 --> 00:13:40.405
coordinates, and stuff like that.

00:13:40.625 --> 00:13:44.375
The other thing we said in the book is
AI-driven team design, so just making

00:13:44.375 --> 00:13:47.595
use of the tools to be very thoughtful
in how you're structuring your team.

00:13:47.915 --> 00:13:50.336
Matt Abrahams: So AI can help us
structure the team and maybe even

00:13:50.346 --> 00:13:53.005
identify who some of the experts
are that, that we might know.

00:13:53.026 --> 00:13:53.475
I love that.

00:13:54.638 --> 00:13:55.638
Melissa, this has been great.

00:13:55.698 --> 00:13:58.668
Before we end, you know I like to ask
three questions one I make up just for

00:13:58.668 --> 00:14:00.158
you and two I've been asking everybody.

00:14:00.158 --> 00:14:00.748
Are you up for that?

00:14:00.798 --> 00:14:01.428
Melissa Valentine: Yeah, let's do it.

00:14:01.648 --> 00:14:04.898
Matt Abrahams: Beyond the academic
research you do, you're also a creator,

00:14:05.008 --> 00:14:08.778
and you study the algorithms that
serve up information on social media.

00:14:09.258 --> 00:14:12.407
What advice do you have for
others who are creators?

00:14:12.607 --> 00:14:16.248
Melissa Valentine: Okay, so
I love Instagram and TikTok.

00:14:16.248 --> 00:14:19.007
I don't, like, I have, I think
it's people have complicated

00:14:19.007 --> 00:14:20.417
relationships with social media.

00:14:20.597 --> 00:14:21.877
So the attention stuff is real.

00:14:21.917 --> 00:14:27.088
My attention span is shot, but I have
learned so much from content creators.

00:14:27.147 --> 00:14:28.357
I am such a fan.

00:14:28.787 --> 00:14:30.227
My advice is keep going.

00:14:30.518 --> 00:14:33.257
If you're an expert, put it out in
the world, like, people will find it.

00:14:33.428 --> 00:14:35.837
Different life transitions I've gone
through, different, like, health

00:14:35.847 --> 00:14:37.997
stuff, different fitness stuff,
different hobbies, like, I have

00:14:37.998 --> 00:14:39.717
learned so much from the internet.

00:14:39.728 --> 00:14:41.267
So thank you, content creators.

00:14:41.568 --> 00:14:43.788
Matt Abrahams: You know, as a creator
myself, and it took me a while to

00:14:43.847 --> 00:14:47.997
identify as a creator, but I think
many of us are motivated to help

00:14:48.007 --> 00:14:52.147
people, and it's that motivation
that actually helps us get through.

00:14:52.377 --> 00:14:56.027
It's hard to put out the content,
and the algorithm can sometimes

00:14:56.027 --> 00:14:57.197
help you and sometimes not.

00:14:57.388 --> 00:15:01.377
So it's that passion, desire to learn and
to help, I think, that really motivate.

00:15:01.377 --> 00:15:03.277
And I can hear that in your
voice, and I see it in the

00:15:03.288 --> 00:15:04.687
things that you post and create.

00:15:04.998 --> 00:15:08.478
Question number two, who is a
communicator that you admire and why?

00:15:08.837 --> 00:15:11.607
Melissa Valentine: So I'm at a
moment where I'm thinking a lot about

00:15:11.617 --> 00:15:16.128
communication, where we really take
each other in in a really deep way.

00:15:16.288 --> 00:15:19.847
So I have a friend who is
a therapist and a Buddhist.

00:15:20.017 --> 00:15:23.547
She has a quality of listening and
expression that it, that allows

00:15:23.557 --> 00:15:25.487
for, like, true communication.

00:15:25.498 --> 00:15:27.507
So I would say I'm gonna,
I'm gonna nominate her.

00:15:27.788 --> 00:15:30.748
It's, like, a fascinating thing about
being very aware of yourself that

00:15:30.767 --> 00:15:33.637
allows you to be very aware of others
and just, yeah, like, it is a lot of

00:15:33.638 --> 00:15:36.717
presence, as you're saying, like, a
lot of kind of presence and connection.

00:15:37.197 --> 00:15:39.257
Matt Abrahams: Yeah, I like that,
self-awareness and other awareness.

00:15:39.257 --> 00:15:39.707
Thank you.

00:15:40.267 --> 00:15:43.447
And final question, what are the
first three ingredients that go into

00:15:43.447 --> 00:15:45.448
a successful communication recipe?

00:15:46.087 --> 00:15:49.878
Melissa Valentine: Something that I've
come to appreciate is how useful, like, a

00:15:49.878 --> 00:15:53.687
deep awareness of your own experience is,
'cause then you're even more able to take

00:15:53.687 --> 00:15:56.037
in another's in all of its complexity.

00:15:56.357 --> 00:16:01.007
So yeah, self-awareness, other awareness,
and then working from there, I think

00:16:01.047 --> 00:16:03.157
what's possible between you is, like, new.

00:16:03.188 --> 00:16:04.717
It's like something that
neither of you would have done

00:16:04.897 --> 00:16:06.718
without that kind of connection.

00:16:07.328 --> 00:16:09.917
Matt Abrahams: I sort of bristle at
the word synergy, but in this case

00:16:09.917 --> 00:16:13.117
that's exactly what you're talking
about, is it's the power of the two

00:16:13.117 --> 00:16:14.897
is greater than either individually.

00:16:14.947 --> 00:16:18.708
But that comes, as you said, from a
self-awareness and then other awareness.

00:16:19.378 --> 00:16:22.097
Thank you for the three ingredients,
and thank you for the conversation.

00:16:22.298 --> 00:16:26.648
Your work to me is really intriguing
because it focuses both on technology,

00:16:26.907 --> 00:16:30.467
but the human aspect of people coming
together, and the fact that there are

00:16:30.468 --> 00:16:34.417
structures that we can rely on to help
expedite and make things more efficient.

00:16:34.627 --> 00:16:35.868
Melissa, this has been fantastic.

00:16:35.868 --> 00:16:37.467
Thank you, and thank
you for the work you do.

00:16:37.517 --> 00:16:37.847
Melissa Valentine: Totally.

00:16:37.858 --> 00:16:38.687
Really fun for me too.

00:16:38.697 --> 00:16:39.138
Thank you.

00:16:41.110 --> 00:16:43.180
Matt Abrahams: Thank you for joining
us for another episode of Think

00:16:43.180 --> 00:16:45.000
Fast, Talk Smart, the podcast.

00:16:45.430 --> 00:16:49.810
To learn more about groups, listen in
to our episode 241 with Colin Fisher.

00:16:49.980 --> 00:16:52.810
And to learn more about social
media algorithms, please check out

00:16:52.840 --> 00:16:55.260
episode 268 with  Angèle Christin.

00:16:55.610 --> 00:17:00.190
This episode was produced by Katherine
Reed, Ryan Campos, and me, Matt Abrahams.

00:17:00.449 --> 00:17:04.549
Our music is from Floyd Wonder, with
special thanks to Podium Podcast Company.

00:17:04.959 --> 00:17:07.820
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