Latest / Whereabouts Tales | Stories of Belonging and Immigrant Experiences / Life, Tech, and the Art of Remaking Your Rules: A Conversation with Emily Pabst

Transcript

Life, Tech, and the Art of Remaking Your Rules: A Conversation with Emily Pabst · Whereabouts Tales | Stories of Belonging and Immigrant Experiences

• 0:00
  Humans are not making small problems anymore, right?
• 0:02
  That is just not what we do. We only make huge, complicated,
• 0:07
  very difficult challenges. This new information landscape
• 0:10
  that we find ourselves in is unlike anything that we were
• 0:14
  ever trained for, and it was unlike anything that our brains
• 0:18
  have ever evolved to manage. We're living through an
• 0:20
  extraordinary era of choice inflation where people are being
• 0:25
  asked to make way more choices that are way more taxing.
• 0:30
  We get in this pattern of exhausting ourselves, this
• 0:33
  decision fatigue with how many choices we have to make, and
• 0:37
  that leads us to make poorer and poorer choices.
• 0:42
  All of these choice tech tools is information technology tools.
• 0:46
  They are just that. They are just tools.
• 0:48
  They are not your life. They are everywhere and they do
• 0:52
  have potential, but they don't have to be anything and that
• 0:57
  what is most important is who you want to be and how you want
• 1:01
  to live and what relationship you want to have with these
• 1:04
  tools, not the other way around. Emily, good evening on my side.
• 1:22
  Good afternoon on your side. Welcome to the Whereabouts Tales
• 1:27
  podcast. Thank you so much for having me.
• 1:30
  Great to be here. Today I have the honor to speak
• 1:34
  with Emily Pabst. Is it Pabst or Pabst Pabst?
• 1:39
  Both, yeah. OK, now you have to explain why
• 1:42
  both. Well, I mean most I'd say most
• 1:46
  people say a Pabst. I say a Pabst but like post is
• 1:53
  something that I register and and recognize too.
• 1:55
  I'd say it's a. It's a common accented
• 1:57
  pronunciation of the name. OK, I think it's depending to
• 2:00
  the to the people's to the person sitting in front of you
• 2:03
  and their origin. How do they decide to read it?
• 2:06
  Emily is the founder of remake the rules where she helps people
• 2:12
  rethink how they make decision in a world full of noise.
• 2:17
  And we'll get a bit more into into that topic later.
• 2:22
  But first, Emily, I would like always in this podcast, I would
• 2:27
  like to know you first. And first of all, I'd like to
• 2:30
  ask what are your whereabouts? Sure.
• 2:34
  Well, right now I live outside of Denver, Co, part of the
• 2:38
  Denver, Co metro area. So Colorado is a state in the
• 2:42
  United States that's kind of western middle and that Rocky
• 2:47
  Mountains are there. It's it's pretty well known for
• 2:49
  skiing and snowboarding and winter sports which I don't
• 2:52
  really partake in but I live here anyways.
• 2:57
  That's cool. Well, are you original from
• 2:59
  there or you you moved there? I moved here.
• 3:02
  I've I've been here for maybe 12 or 13 years now, but I'm
• 3:06
  originally from a medium sized town right in the middle of
• 3:10
  Missouri, which is a state in the United States that is like
• 3:13
  the middle of the middle of the middle.
• 3:16
  I would you mind saying the name of the state of the of the city
• 3:23
  of the city? Yeah, it's Columbia, MO.
• 3:26
  No idea. I I.
• 3:27
  Tried. Yeah, Yeah, right.
• 3:28
  Yeah, when I've, when I have traveled before and, you know,
• 3:33
  met people and talk to people, it's, it's always lovely to
• 3:36
  engage with folks. But inevitably the question
• 3:39
  comes up like, where are you from?
• 3:40
  And, and I, over the years I've kind of tried different
• 3:44
  strategies, you know, right. I'm like, oh, I'm from, well,
• 3:48
  let's see, do you know where Chicago is?
• 3:50
  And folks are kind of like, kinda.
• 3:52
  And I'm like, well, I'm like 600 miles from there, right?
• 3:56
  Yeah. You know where Chicago is that
• 3:58
  not from there. Yeah, no, no, I did, though,
• 4:02
  funnily enough, I went to grad school in Kansas, which is
• 4:05
  nearby. And and so there was a time in
• 4:08
  my life where people say where you from?
• 4:09
  And I say Kansas. And overwhelmingly, people from
• 4:14
  all over the world would say, oh, Wizard of Oz.
• 4:17
  And I'd be like, Oh, yes, yeah, Wizard of Oz, yeah.
• 4:20
  Yeah, Dorothy, I mean, you know, I have a cultural problem with
• 4:27
  Wizard of Oz and I, I want to go on this Rand now because I keep
• 4:31
  discussing with my work colleagues.
• 4:32
  I I live in general at the moment, but I keep discussing
• 4:35
  with my work colleagues about Wizard of Oz and it took me a
• 4:38
  while to explain them what Wizard of Oz is.
• 4:41
  And I mean, it's amazing, like how pervasive the Wizard of Oz
• 4:48
  is across the world, apparently. I mean, not, not everybody knows
• 4:52
  about it, but I was really surprised to learn that that
• 4:55
  that was like a cultural touchstone that that so many
• 4:58
  people were aware of about the United States.
• 5:00
  Yeah. And now I have to go in another
• 5:04
  small detail. Do you know that sound of The
• 5:07
  Sound of Music? So I think a movie that almost
• 5:12
  everyone knows on the face of this earth is not known in
• 5:14
  Germany at all because because the family inside The Sound of
• 5:23
  Music is of a former Nazi Nazi officer.
• 5:27
  And that's why they don't they never.
• 5:30
  I think they played it once, but there was never no on TV.
• 5:34
  I mean, I, I could definitely see how the sort of
• 5:37
  glorification of that story and the whimsy of it is a little
• 5:39
  different, you know? Exactly.
• 5:41
  Exactly. Yeah, but it was a fun fact for
• 5:44
  me. I'm sorry for the rent.
• 5:48
  How was Emily? How was how was growing up in a
• 5:51
  in a small city in the middle of the middle of the US?
• 5:54
  Yeah, it was. It was lovely and also both sort
• 5:59
  of like kind of exactly what you might be imagining and nothing
• 6:03
  at all like what you might be imagining.
• 6:06
  I, I, I grew up in sort of a mid sized city that also was the
• 6:11
  university town for like the entire state.
• 6:15
  So the, the big college was there.
• 6:17
  There were two other universities that were there two
• 6:19
  colleges, 1 university that was there.
• 6:21
  And so even though we were kind of in the middle of what would
• 6:27
  be largely agricultural, there was this very large cultural hub
• 6:33
  that even had a pretty large international population.
• 6:36
  So, So that was kind of my experience once I left the city
• 6:41
  and started going to College in the United States, meeting more
• 6:43
  people. I've, I've only ever lived in
• 6:45
  the United States, but that that as I was sort of describing what
• 6:49
  my Missouri experience was like to people, they would be like,
• 6:52
  oh, that is, that is not the stereotype I was expecting.
• 6:56
  And it's kind of both. It's both the the middle of the
• 6:59
  middle of the middle, but also this sort of interesting aspect
• 7:03
  of being a really large university town.
• 7:06
  I want to ask you about the community, but as it was not
• 7:10
  such a small town, I would guess that the community community was
• 7:13
  more related to your neighborhood.
• 7:15
  But still, I would like to ask you how was the because I, I
• 7:19
  keep telling the story until someone will get bored.
• 7:20
  But I read Michelle Obama's book and she said that I was raised
• 7:24
  by by the neighborhood. So everyone on this on the on my
• 7:27
  street knew me and knew my name and knew who was my father and
• 7:30
  my mom. And they will call me and tell,
• 7:32
  you know, Michelle did this. And it wasn't the same feeling
• 7:35
  in in your city like you had the feeling that you know everyone
• 7:38
  from her neighborhood not. I would say that wasn't my
• 7:43
  experience, though. So where I lived, a lot of the
• 7:53
  properties nearby were rental properties, which usually means
• 7:57
  that folks will stay there maybe for a handful of years, maybe
• 8:01
  just one year, but but not a lot longer than that.
• 8:05
  So my family was in one of the sort of owned homes in the
• 8:09
  neighborhood. So we were there.
• 8:11
  We lived there almost my entire life and or my entire childhood,
• 8:17
  I suppose. And so, so it was interesting
• 8:22
  that like, the place is very near and dear to me and that
• 8:26
  place really raised me, but the people maybe weren't as
• 8:30
  consistent, if that makes sense. So.
• 8:34
  So there certainly was some change over.
• 8:36
  Yeah, Right. But at the same time, like, I
• 8:38
  changed a lot during those 18 years too, right.
• 8:41
  So I, I definitely remember, I'm an elder millennial.
• 8:44
  So I like remember when the first personal computer was
• 8:47
  brought into our home, right. And but I also remember riding
• 8:52
  bikes in the streets with all of the other young kids and then,
• 8:57
  you know, having to like, rush home when the streetlights
• 8:59
  started coming on because you have to be home by when the
• 9:01
  streetlights are on. Right.
• 9:05
  I come from Romania. We had not done that many
• 9:07
  streets, right? And and besides that, I was
• 9:10
  allowed to stay home as I stay outside.
• 9:13
  And then it was, it was dark because we haven't had any
• 9:17
  lights. That's why.
• 9:19
  But it's funny that we are a combination of both words.
• 9:21
  Now that you said, I realize it's like you, we are able to
• 9:25
  use a computer MacBook, call it, call it however you want, but we
• 9:29
  are able to use it. But they also know how is to
• 9:32
  ride the bike and have your knees completely covered in
• 9:36
  blood or because of the falling with the bike and so on.
• 9:40
  That's an that's an interesting thing that I, I have to say,
• 9:43
  it's interesting. Yeah, for sure are learning how
• 9:46
  to drive and navigate without any navigation tools other than
• 9:50
  a paper map. You know, talk, talk about a
• 9:52
  different experience. Driving with the bike also on
• 9:56
  the over the hill and being able to come back without your phone
• 10:00
  telling you how to come home. And.
• 10:03
  And being afraid to come home, like you said before, being
• 10:05
  afraid to go home because nobody had had the possibility to call
• 10:08
  you. And the only moment in which you
• 10:09
  get your punishment, like your your lesson was when you you
• 10:14
  were coming home and that's why you were postponing as long as
• 10:17
  possible that moment, even though it you couldn't, you
• 10:19
  could not make it better. But cool.
• 10:25
  When do you remember the first personal computer entering your
• 10:27
  home? I, I could not tell you the age.
• 10:34
  I think, I mean, I definitely was in elementary school, which
• 10:39
  is sort of up through the age of 10 or 11 in the United States.
• 10:43
  So I was, it was probably a single digit age and it was an
• 10:50
  old Tandy, if that was meaningful to you at all.
• 10:53
  It had the green screen and I played a game on it where like a
• 10:58
  little stick man fell from the sky and landed in a wagon And
• 11:02
  and that was like thrilling. Absolutely thrilling.
• 11:06
  I had the one with the lines you remember with the lines and the
• 11:10
  ball moving in in the between the lines, so you had to there.
• 11:13
  Was a Oh, yes, yeah, yeah, yeah, absolutely.
• 11:16
  Yeah, I don't know what the name of it, but.
• 11:19
  Thrilling, thrilling. Nothing better.
• 11:24
  I, I, I, one of my friends had an, there was a actually a
• 11:31
  Romanian computer, so I remember was an HC-90.
• 11:35
  And the only mobile way in which you could load games was with
• 11:40
  tapes, like with cassette? Yeah, because there was a sound
• 11:43
  coming from the cassette and we had to wait 6-7 tapes until they
• 11:48
  loaded the game and they had an error at 95%.
• 11:51
  They had to start from scratch. Oh, wow, Yeah, I remember the
• 11:56
  big floppy disk that is like as far back as my, like, utility
• 12:00
  goes. Yeah, yeah. 3.3.53.5 I think it
• 12:04
  was called. Yeah cool.
• 12:08
  No, we are not told no. We just read a lot on the
• 12:11
  Internet about all those informations.
• 12:15
  Just watching a lot of nostalgic television, yeah.
• 12:18
  When was the moment, or let me ask you any different, what kind
• 12:23
  of kid you were? What kind of what kid?
• 12:26
  What kind of kid you were? Yeah.
• 12:29
  I was. So I am the youngest of four and
• 12:34
  so I think that impacted me a lot that I was, you know, kind
• 12:42
  of this like independent little roamer, right?
• 12:45
  And, and I think there was a combination of of growing up
• 12:49
  pretty quick because I was learning so much for my older
• 12:52
  siblings, but also just like, and now that I'm older, right, I
• 12:56
  can like, really better appreciate the sort of like
• 13:01
  exhaustion that my parents must have felt, you know, by the time
• 13:04
  Ford came around, right. That's just like you just, you
• 13:08
  know what, It seems like you're doing a good job of managing
• 13:11
  yourself. And I'm just going to let you by
• 13:13
  all means, right. You know?
• 13:17
  Yeah, it's given a lot of independence and, and, and I
• 13:23
  loved it. That's what made you questioning
• 13:26
  the rules somehow from that age or give you the freedom to do
• 13:30
  that. I think so, yeah.
• 13:33
  I think this is like what kind of what I do now is so much a
• 13:38
  part of who I am and this idea of the independence, you know,
• 13:48
  like independence can be wonderful and, and there can be
• 13:51
  a lot of freedom in that, but also there's a lot of
• 13:54
  responsibility and requirement to figure out what's going on.
• 13:58
  You know, this sort of like lack of guidance or control or kind
• 14:04
  of whatever flavor that shows up in it does mean that you are
• 14:09
  kind of figuring it out. And and I think that I happen to
• 14:17
  take a fair amount of pleasure in that.
• 14:19
  So that's really good. That was very lucky for me,
• 14:22
  yeah. Would you call it the kind of a
• 14:25
  street smart? Yeah, I would say so, yeah.
• 14:30
  Yeah, like. I see that you actually directly
• 14:33
  understood, I mean this, this idea of thinking outside of the
• 14:36
  rules and think how to how can you solve the problem without
• 14:40
  considering the rules like let's see what we can do to solve it.
• 14:43
  And I think that's something that we got a lot in that age.
• 14:46
  And I thought it was only from Eastern Europe as I'm coming
• 14:49
  from there, but I see not it was an age thing most probably.
• 14:53
  Yeah, potentially and and I think I, I think you're probably
• 14:58
  right that this is kind of been interesting crossroads with
• 15:04
  folks that you know, right. And and now this is all
• 15:06
  hindsight that we're thinking about this, but that we have
• 15:09
  this sort of increased sort of pressures and responsibilities
• 15:14
  on adults in the family unit. While you also are sort of like
• 15:18
  pretext slash tech is coming in and you've got a lot of folks
• 15:24
  like this is where we really are are turning a corner, especially
• 15:28
  when it comes to technology. And the way in which that like
• 15:31
  digital technologies, computational technologies have
• 15:34
  really changed our lives and have really changed how we think
• 15:37
  and how we live. And and that we have been sort
• 15:41
  of on this long arc that has brought us here to 2025 of these
• 15:47
  big changes and, and, and just having to figure it out.
• 15:50
  Yeah, figure it out. Everybody's winging it, so we
• 15:55
  have to try as well. Everyone has to find their way.
• 15:59
  Do you have do you have kids, Emily?
• 16:02
  I don't. I don't have.
• 16:03
  I don't OK that that's I have AI have a small boy and that's one
• 16:06
  of the things that I'm struggling the most to it to to
• 16:09
  find the break even point between pampering him and giving
• 16:14
  him the freedom to to do whatever I have done.
• 16:18
  Because I realized more and more than even in in school, they
• 16:21
  have this crazy care of having this close circuit.
• 16:27
  Nobody's allowed to get in. They don't get any connection
• 16:30
  with outside of the school. And this is something that kind
• 16:32
  of scared me for the for the real world because this this
• 16:36
  attitude of come on, nothing can happen.
• 16:38
  Nothing bad can happen. Just play calm.
• 16:41
  This is something that you actually need when you go out of
• 16:43
  that bubble in school. Yeah, it's it like I don't have
• 16:49
  kids myself, but I have a ton of like empathy and curiosity about
• 16:56
  like those questions exactly. Because I, I think that we,
• 17:01
  everyone, we are not living in the world that any of us grew up
• 17:04
  in, right. And so even the lessons that we
• 17:08
  may have been able to learn within our own childhoods and
• 17:13
  development and even as adults who are preparing for adulthood,
• 17:18
  responsibility, parenthood, whatever, if those lessons were
• 17:21
  learned 10 years ago, then we also have a problem.
• 17:25
  Right. Exactly.
• 17:26
  Exactly. Yeah.
• 17:28
  Yeah, it is. It is tough out there.
• 17:30
  I keep saying that besides the the basics of I don't know, do
• 17:35
  not steal, do not kill, do not like like the basics.
• 17:41
  Everything else is subject to change.
• 17:43
  Like really everything else is subject to change.
• 17:45
  My, my favorite 1 is this. If we talk about the, the food
• 17:50
  industry, I think 30 years ago, nobody said anything about sugar
• 17:55
  and everyone I was talking about fat since 10 years ago.
• 17:59
  Now everyone's talking no, no, no, you should give fat to the
• 18:02
  kid because the brain is only made from fat.
• 18:04
  But you should not give him sugar anymore because sugar is
• 18:06
  bad. And this is just a small
• 18:08
  example. This is something that came from
• 18:10
  the top of my head. And I'm, I'm talking a lot with
• 18:15
  my wife about this. And it's, it's a, you cannot,
• 18:18
  there is. So they don't come with that.
• 18:20
  They unfortunately, they don't come with the user's manual.
• 18:24
  They, there is no user's manual. There's no introduction in
• 18:27
  parenting. I love people giving lessons,
• 18:34
  how to raise your kid without having a kid.
• 18:36
  I love them. Yeah.
• 18:42
  And another thing. Yeah.
• 18:45
  I love them. I just love them.
• 18:48
  You have no idea. I don't go into detail and
• 18:52
  every, every small detail that you can think about.
• 18:55
  And it's, it's incredible how much they are copying you.
• 19:00
  And I think the one thing that I, my son is will be 7 in
• 19:05
  September. So I'm still young in this role
• 19:08
  and I'm still learning. And most probably, I don't know
• 19:10
  everything by the time he's 18 and he left the house.
• 19:14
  But the only thing that I can, I can, I can say it.
• 19:18
  It's practice what you preach because he doesn't listen to
• 19:22
  what you're saying. He's watching what you're doing.
• 19:26
  And if you want him to, I don't know, do sports, you have to
• 19:29
  make sports before him. If you want him to behave, you
• 19:32
  have to behave in front of him. Yeah.
• 19:36
  Yeah, it's it's a crazy, it's an interesting world.
• 19:38
  It's an interesting world also with the with the social, with
• 19:41
  social media. It's an interesting world also
• 19:43
  with the with the with the devices in general, with the
• 19:46
  screens. There are so many split opinion
• 19:49
  about the screens and above the devices and nobody actually know
• 19:52
  what exactly are the long term of effect, because everything
• 19:57
  it's a, it's a supposed. Yeah, we can think that it can
• 20:00
  be that, but we have no idea. Yeah, we don't know because the
• 20:03
  time hasn't passed yet. Exactly.
• 20:04
  We are, we are like all live, experimenting on ourselves as we
• 20:09
  go and and we're going to see and.
• 20:11
  You know what's funny really that I think it will take
• 20:13
  another at least 100 years to to find out because by the time we
• 20:17
  get some experience with the devices from today, the new
• 20:20
  devices coming up and you don't get to actually work out and and
• 20:28
  get make some real experience with something with their.
• 20:31
  I read an study about smoking that was done in a village in
• 20:37
  somewhere in Russia for about 45 years.
• 20:40
  You cannot even do that anymore because now the different, there
• 20:43
  are different kind of of cigarettes coming out every
• 20:45
  month. So.
• 20:48
  Yeah. And like like such kind of what
• 20:51
  you're saying, like with that example, with the example of
• 20:54
  like, what are we even supposed to eat?
• 20:55
  You know, it's so interesting how, like, science moves out of
• 21:01
  pace, right? And it is a pace that is
• 21:04
  significantly slower than how now with all of our technology
• 21:08
  tools, we can communicate with each other, right.
• 21:11
  And that disparity, that discrepancy is definitely
• 21:15
  causing us a lot of heartache right now.
• 21:17
  Yeah. So, so we're kind of finding
• 21:19
  ourselves in these like huge information cycles, these huge
• 21:23
  like waves of, of ideas where they can happen so much more
• 21:29
  faster than new knowledge, right?
• 21:32
  Not just information, but new knowledge can be gained.
• 21:35
  And that we're just kind of trapped in that, right.
• 21:38
  Like these crashing waves, like, Oh no, Oh no, I got to eat
• 21:41
  totally different now. I've been doing it wrong for,
• 21:43
  you know, and, and a tough, it's a tough position to be in.
• 21:47
  Yeah. But we are winging it.
• 21:51
  Yeah, we sure are. And, and I think that there's,
• 21:57
  you know what one of the things I try to bring to people when we
• 22:00
  have these conversations and, and unfortunately, like this is
• 22:03
  not about easy answers. Like I, I tell folks like humans
• 22:09
  are not making small problems anymore, right?
• 22:11
  That is just not what we do. We only make huge complicated,
• 22:16
  like very difficult challenges and because of that the scale of
• 22:22
  the solutions is also going to have to be really big.
• 22:26
  But as individuals, it, it can include understanding the
• 22:32
  environment for what it is, right?
• 22:34
  Kind of seeing these big patterns and how they are
• 22:39
  enacting upon us as individuals, upon our culture and societies
• 22:44
  and, and what they are doing and what they really mean though,
• 22:47
  right? So this idea of sort of
• 22:49
  separating what is happening informationally with what is
• 22:53
  happening scientifically is maybe a baby step to like
• 22:57
  reframing really what's going on and really kind of what we're
• 23:01
  encountering through these supercomputers that we all carry
• 23:05
  around in our pockets. Do you think there's going to be
• 23:08
  a moment where we are able to use the progress of technology
• 23:12
  to increase the speed in the progress of science?
• 23:16
  I think that is already happening, yeah.
• 23:20
  Not on the, not on the pace where we would all be happy with
• 23:25
  to be. Honest.
• 23:26
  Oh sure. I mean, we're like, we're not
• 23:27
  catching up to the problems that were right, you know?
• 23:34
  But I've seen a picture, I've seen a picture a few days ago,
• 23:36
  I've read an article, I think in the New York Times if I remember
• 23:39
  it correctly, and they said that ChatGPT found on an X-ray a
• 23:47
  small, small dot, and it identified to be a breast, a
• 23:50
  future breast cancer, and it discovered it before it could
• 23:54
  evolve. That's what AI should be used
• 23:56
  for, not to create pictures of Trump.
• 23:59
  A hag hugging mask. Yeah, I, yeah, I, I so great
• 24:04
  potential, right? Like it is a tool with
• 24:08
  extraordinary potential. And then it just comes down to
• 24:12
  how we choose to use that and how we choose to incorporate it
• 24:15
  into our lives and our cultures and our societies.
• 24:17
  Yeah, Correct. Mm, hmm.
• 24:20
  Correct, Emily, in one of your previous interviews or podcasts,
• 24:25
  because I have my notes done through all of them and I don't
• 24:28
  remember it was an interview of the Postit, but you said that
• 24:31
  you, like you, are drawn to art that upsets your brain.
• 24:39
  Doesn't sound like something I would say yes.
• 24:44
  Yeah. Do you think that's a native
• 24:46
  curiosity that it's triggering you there?
• 24:51
  I think I think what I love about art that upsets my brain
• 24:58
  is the same thing that I also enjoy being proven wrong because
• 25:04
  what it does for me is reminds me of how much more possibility
• 25:10
  and expansiveness there is outside of my own brain.
• 25:14
  And you know, that that even though myself is how I
• 25:19
  experience the world and who I am and I and I love all of those
• 25:22
  things, there really is so much more.
• 25:24
  And at the end of the day, what I know and what I experienced
• 25:29
  and what I can understand and process is very limited.
• 25:33
  So the fact that that there is so much more and that I can keep
• 25:37
  encountering that so much more is a real pleasure.
• 25:39
  Yeah. So I love weird out.
• 25:41
  Like the weirder the better. Yeah.
• 25:44
  Any anything that kind of twist my brain up?
• 25:47
  Big fan. You said to to read the complete
• 25:52
  quote. You said I enjoy caves,
• 25:53
  limericks, water slides, R&R. That upsets my brain.
• 25:58
  Yeah, yeah, all those are true. Yeah, I.
• 26:00
  Loved it and I said I have to take this.
• 26:03
  I love the fact that you said that you like someone
• 26:05
  challenging you and showing you a different point, like showing
• 26:09
  giving you a different perspective of what you said.
• 26:11
  I think that's the base, the, the, the discussions with people
• 26:15
  that we don't agree with are the ones that brings us bring us
• 26:19
  further because we are able to experience an A different
• 26:25
  opinion and we are able either to challenge it somehow with our
• 26:28
  opinion, either to accept it as as the new opinion.
• 26:31
  And but you need a lot of, I would say a lot of character to
• 26:36
  be able to accept the fact that you are wrong.
• 26:40
  Yeah, I think, I think I also think of it, think of it as
• 26:48
  flexibility, you know, kind of going back to what you were
• 26:51
  talking about with your kid, right?
• 26:53
  And how perceptive they are and how how much, you know, they're
• 26:58
  watching you and that that is sort of creating the person that
• 27:01
  they are. We're all like that, right?
• 27:05
  Like we the difference between who we are and the environments
• 27:10
  that we are in is really not that different that we just
• 27:15
  become some sort of synthesis of all of the information that we
• 27:19
  encounter and that we process. And kind of understanding that
• 27:25
  there is incredible variability in people's experiences and that
• 27:30
  we are incredibly good at adapting to that variability
• 27:34
  just means that you are going to have people who are operating
• 27:38
  with completely different rules for very good reasons.
• 27:43
  Yeah. And, and so I think kind of
• 27:45
  having that flexibility of mind is kind of helpful in being able
• 27:53
  to reorienting to this idea that a person isn't who they are for
• 27:59
  no reason, right. A person becomes who they are
• 28:02
  for usually very good reasons. And, and kind of exploring it
• 28:06
  from that perspective. I I usually enjoy.
• 28:10
  Do you usually think that we are developed or not developed only
• 28:18
  because of the people that we sit around with?
• 28:23
  I think that we, our brains are very much attracted to other
• 28:28
  humans and what other humans do. So that definitely does occupy,
• 28:32
  like, a really powerful space for us, but it really is our
• 28:38
  entire environments, too. Yeah.
• 28:43
  And and this is like where a big turn has occurred for us.
• 28:46
  Like, it used to be that our environment was needed to be
• 28:50
  physically near us for us to sense it, right.
• 28:54
  And that's no longer the case anymore.
• 28:57
  Like our environments are potentially as expansive as the
• 29:01
  Internet. I love the fact that we are able
• 29:05
  to do this and I love the Internet because we are able to
• 29:08
  do this what we are doing now. But we have a few 1000 miles
• 29:13
  between US and, and we have this conversation, which is amazing.
• 29:16
  But on the other side, it said when you do this and you are in
• 29:20
  the same city or maybe you are a few a few kilometers away
• 29:24
  because of the comfort of living your, your nest.
• 29:29
  And I think this is something you're right.
• 29:30
  I think it's something that we got used to maybe a bit too much
• 29:33
  in the last period and we really don't know how to navigate the
• 29:37
  the change yet and. I mean, how how could we really?
• 29:42
  No. Yeah.
• 29:43
  Because the this is something so new for everyone.
• 29:46
  Like we, we are learning it right now.
• 29:50
  Yeah. Emily So you, you moved you you
• 29:57
  studied in your hometown as far as I as far as I understood.
• 30:01
  And then you moved for work or you moved for for study?
• 30:06
  For study. Yeah, for studying.
• 30:09
  Where have you moved? So I left my hometown to go to
• 30:17
  university in Colorado. So that is the first time I kind
• 30:22
  of ended up where I live now and why I eventually came back here.
• 30:26
  But before I kind of settled down here, I was back in
• 30:30
  Missouri for a while after college, and then I went and got
• 30:34
  a master's degree in Kansas, Wizard of Oz, of course, as we
• 30:38
  all know, and and then I eventually made my way back to
• 30:42
  Colorado. Cool.
• 30:45
  What what? What kind of what roles have you
• 30:48
  hold before before launching Remake the rules?
• 30:53
  Say it again. What, what, what jobs?
• 30:55
  What roles have you had before launching?
• 30:58
  Remake the rules. Sure.
• 31:01
  Well, I have pretty much always worked in public service.
• 31:06
  So for government agencies, that's something that was a big
• 31:12
  part of my family growing up and is definitely something that I I
• 31:17
  just pursued because of that, I think.
• 31:20
  And so I worked in a court system in Missouri, so part of
• 31:26
  actually an alternative sentencing court.
• 31:28
  So it was seeking better options for people with mental health
• 31:32
  disorders, traumatic brain injuries, and then addiction
• 31:36
  issues that were more about resolving those underlying
• 31:40
  problems than about sort of punitive, like jail time or what
• 31:46
  have you. And then from there, I went and
• 31:51
  got my master's degree in geography.
• 31:55
  So after that, I ended up doing redistricting for the state of
• 32:00
  Kansas. So I I can do a crash course in
• 32:05
  redistricting. Yeah.
• 32:08
  So essentially, redistricting is about how people in the United
• 32:12
  States vote. The idea is that every person
• 32:16
  should get the same like one vote, one person, one vote.
• 32:20
  So my vote should be worth the same amount of vote as everyone
• 32:24
  else's vote. But because people are dispersed
• 32:28
  differently all over the country, the way that they draw
• 32:32
  sort of the voting district boundaries needs to take account
• 32:37
  of this. So it's essentially how like you
• 32:41
  determine where a voting district is.
• 32:43
  So where my representative? So if we have a representative
• 32:50
  that is in Congress, they should represent about the same number
• 32:56
  of people as another representative.
• 32:58
  Does that make sense? Yeah, does not not make sense
• 33:01
  and is the same for the presidential elections.
• 33:05
  So it does matter for the presidential elections because
• 33:15
  it's by Electoral College, which is yes.
• 33:18
  Yeah, right. But, but, but, but it's not the
• 33:19
  same. So representatives are not the
• 33:21
  same. They are more than the the, the,
• 33:24
  the electors in the electoral in, in voting for the president,
• 33:29
  right. Like kind of how they would
• 33:31
  relate with each other is that there's only so many
• 33:35
  representatives, and so every 10 years, depending on how many
• 33:40
  people are in each state, they allocate the representatives to
• 33:44
  each state. OK, so like if one state's
• 33:48
  population goes up a lot and another state's population goes
• 33:52
  down a lot, 1 can gain a representative and one can lose
• 33:55
  a representative. Oh, that's interesting.
• 33:57
  So that's changing. Yes it yes it can change.
• 34:02
  Emily, you raise my curiosity. I'm a big I'm a fan.
• 34:05
  I'm AUS fanboy. I have to say that I've said
• 34:08
  this several times and I I read, I read a lot about the US
• 34:11
  elections because I think it's an interesting process.
• 34:15
  OK, which is old on some in some cases, but I think still the
• 34:21
  best. It's still the best democracy in
• 34:23
  the world and it's the only democracy that was never
• 34:29
  imperium or a dictatorship. And I think it makes has a lot
• 34:33
  to do with the election process because made so complicated so
• 34:38
  that nobody can easily go around it.
• 34:42
  And I was always fascinated about this, but I didn't know
• 34:44
  that you are able so that you are switching the
• 34:46
  representative. That's something really
• 34:48
  interesting. Yeah.
• 34:50
  I mean, if you love math and you love, like, American politics,
• 34:54
  get into elections because they are, they're very interesting.
• 34:59
  Yeah. So like the state that I live in
• 35:01
  now, Colorado, actually gained a representative during the last,
• 35:05
  like, sort of census cycle when they determine all of these
• 35:08
  things. So not only did the population
• 35:11
  inside of the states change around, right?
• 35:13
  So then you have to sort of move districts to make sure you have
• 35:17
  the same number of people or near the same number of people
• 35:19
  in each district, but they even added one.
• 35:22
  So now you got to redraw like all the boundaries to figure out
• 35:25
  what representative is going to be representing which people.
• 35:29
  And how often is this process done?
• 35:31
  Because I guess it's a continuous process in which you
• 35:34
  do the calculations and so on, but you still have cut off
• 35:36
  times, right? So it it actually is done once
• 35:40
  every 10 years. So the United States does a
• 35:44
  census where they actually try to count every single person in
• 35:48
  the country every 10 years. They do things in between.
• 35:52
  The American Community Survey is what it's called.
• 35:54
  So they still are collecting data to understand the people in
• 35:58
  the country. But the census is where they try
• 36:01
  to literally count everyone. And then based on that data,
• 36:04
  they're able to say, OK, how do these representatives get
• 36:08
  dispersed, you know, essentially.
• 36:10
  And then now that we have as good a snapshot as we're going
• 36:13
  to get of where everybody lives, we can start drawing these
• 36:16
  boundaries. Oh my God, that's interesting.
• 36:19
  I agree. I honestly, I honestly want to
• 36:24
  to grab a promise from you that we're able to do 1 episode about
• 36:26
  the system because I'm fascinated.
• 36:28
  About this, I can talk about this for days.
• 36:30
  I so honestly, I'm, I'm more than open.
• 36:33
  If you are open and you have the time, let's do it.
• 36:35
  Try to do it in the next weeks because I love the topic.
• 36:38
  I'm I'm fascinated about the US elections because they are so
• 36:43
  interestingly done. I always watch this calling from
• 36:48
  the TV stations like when they called the the state for a
• 36:52
  certain president because they said OK this I managed to learn
• 36:56
  by seeing a lot of them and reading a lot of the about them.
• 36:59
  But I I never get to see someone to explain the process like
• 37:03
  this. Is body interesting?
• 37:06
  I've been out of the game for a while, but I am happy we can
• 37:10
  still we can still get into it. Yeah, OK, I got that promise.
• 37:15
  I will. I will get in contact with you
• 37:16
  after after this. I love it.
• 37:21
  Cool. So you did re.
• 37:23
  How did you call it? Redistricting.
• 37:26
  Redistricting. Exactly.
• 37:29
  Yeah. Why did you left?
• 37:30
  It's so amazing. Well, it is mostly because it's
• 37:34
  only done once every 10 years, right?
• 37:36
  Yeah, I can. I can imagine that.
• 37:41
  And after that, after redistricting.
• 37:45
  After that I moved again, this time kind of my last move to
• 37:51
  Colorado where I am now, and I got a job working as a data
• 37:56
  analyst with the City and County of Denver.
• 38:00
  OK. So still still working somehow
• 38:02
  for the for the state institutions.
• 38:05
  Exactly. Did someone the did somehow the
• 38:09
  the strict rules that you had in these shops made you go towards
• 38:17
  rethinking the rules and remaking the rules?
• 38:21
  I think I so my, I have always had a strong or as long as I can
• 38:27
  remember, I've had a very strong interest in rulemaking and rule
• 38:32
  breaking right. That, that most like any social
• 38:36
  rule that we are participating in, be it judicial, be it
• 38:40
  legislative, be it criminal, that they, they are ones that
• 38:46
  are socially constructed and they, and there are points in
• 38:51
  which they are empowered and followed.
• 38:54
  And then there are points in which they are not right and
• 38:58
  people start departing from that.
• 39:01
  And this sort of dynamic, this sort of soft structure of these
• 39:08
  rules has always been very interesting to me and how they
• 39:11
  can become very rigid and very powerful.
• 39:14
  And then also very not so. So that's kind of how I sum up
• 39:20
  my, my interest and how I kind of got pulled into the work that
• 39:25
  I do and into the conversations that I have is this sort of
• 39:29
  individual rulemaking and rule breaking, this societal level
• 39:34
  rulemaking and rule breaking and, and sort of how we
• 39:37
  construct these ideas and these rules for ourselves and, and how
• 39:42
  powerful they can be on our choices and our behaviors.
• 39:45
  And then how sometimes they can just disappear and and what that
• 39:50
  means too. Interesting.
• 39:54
  Interesting point of view, because you would think that in
• 39:57
  your, like you said, you worked a lot in the government and you
• 40:02
  think you have a lot of power to change things.
• 40:05
  But at one moment you realise you don't like you, you are
• 40:09
  constricted by by different rules that someone made made a
• 40:13
  few a few a few time ago. I would just say it without
• 40:18
  mentioning the time. But do you think that everything
• 40:23
  that has to do with the government is something that
• 40:26
  it's it's a. It's a hard process to be
• 40:30
  changed. Often, but that isn't always a
• 40:37
  bad thing either. I think that when they're so
• 40:48
  separate from the idea of whether or not an institution is
• 40:53
  acting well with and on the people, right, because
• 40:56
  absolutely often sometimes they do not and that there are big
• 41:01
  problems in how these institutions are you hearing
• 41:07
  that? Yeah, I'm hearing.
• 41:10
  No, I'm not. There's no Yeah, I'm back.
• 41:14
  OK. So sometimes you've got these
• 41:18
  big these government institutions and they can be
• 41:22
  acting very problematically upon the people and they can also be
• 41:26
  acting very positively on the people.
• 41:29
  But also there is a lot of sort of stability and intermingling
• 41:38
  that's going on with these institutions too.
• 41:42
  So they just tend to be these really powerful forces in a
• 41:46
  community. And because of that power, they
• 41:52
  absolutely should be able to change.
• 41:55
  They should absolutely be able to improve.
• 41:58
  And there really needs to be structures in place to make sure
• 42:01
  that they can do that and they can do that well.
• 42:04
  But also, if those institutions can change on a dime, then who's
• 42:11
  to say that that major change is for the positive, right?
• 42:15
  It can absolutely be for the negative too.
• 42:19
  So while the in institutional inertia can absolutely be very
• 42:24
  frustrating, I also think that these are not, these are huge
• 42:28
  boats, right? And big boats do not turn
• 42:30
  quickly and they there can be pros and cons to that.
• 42:34
  It's always depending on where the power is.
• 42:37
  I think that's, that's a good, that's a fairpoint saying that
• 42:41
  it's better to have it hard to, to change it because it's always
• 42:45
  a problem when the power is in the wrong hands and they have
• 42:48
  the power to do the things that were done before.
• 42:51
  I think that's, that's an important point that we have to
• 42:54
  keep in the in the back of our mind.
• 42:57
  Do you think that the rules from the government institutions are
• 43:01
  made in the favour of the citizens or against them?
• 43:08
  And what I mean by against them? I'm sorry for interrupting you,
• 43:11
  Emily, but I usually have the feeling, and this is an European
• 43:15
  experience, less AUS experience is that every rule that is made,
• 43:22
  it's made. It's making you, it's making for
• 43:25
  you as the citizen a bit hard to access that institution, to
• 43:31
  contact that institution. This is my this is my feeling
• 43:34
  and is made more in the advantage of the person working
• 43:39
  there because he has a lot of on his mind and he has to somehow
• 43:42
  protect himself. I I mean, I think that anytime
• 43:48
  like boundaries and power dynamics are established, that
• 43:52
  folks are going to build them to some advantage and to some
• 43:57
  disadvantage. Right?
• 43:59
  Yeah. And which, again, is why it's
• 44:01
  incredibly important to try to make sure that we have systems
• 44:05
  in place that do not allow for an overwhelming advantageous
• 44:11
  system for some and an overwhelming disadvantageous
• 44:15
  system for others. And, you know, certainly the
• 44:20
  United States has a long history of providing great advantage to
• 44:24
  some groups of people and great disadvantage to some groups of
• 44:28
  people, which is something that we still have huge problems
• 44:32
  attempting to resolve and extract and, and, and to
• 44:38
  minimize the harms of those systems.
• 44:40
  And, and yes, right, that that is how these these power
• 44:46
  structures work and are built and, and they they are capable
• 44:50
  of great potential for both harm and for good.
• 44:55
  It's always it all. We always come back to the
• 44:58
  addictiveness of power somehow and, and how the how that can
• 45:04
  can influence our life. It's it's so interesting, but
• 45:06
  they are absolutely right. It's a, it's a, it's a, it's a
• 45:11
  big risk that we have there and we have to be aware of.
• 45:16
  And I think you know my my background in data analysis, a
• 45:20
  lot of the questions when you're considering when you're working
• 45:23
  inside of these institutions is what, what are they doing?
• 45:29
  How are they working right. I kind of worked in like an
• 45:32
  operational administrative capacity and, and those are
• 45:37
  really big questions that it is very important to ask and to ask
• 45:42
  well and to answer well. Yeah, yeah.
• 45:46
  So, so I that, that is definitely where my big interest
• 45:50
  in sort of the information of it.
• 45:54
  All right. And now that we have these big
• 45:56
  powerful tools that can help us with all of this data collection
• 46:01
  and computational processing to to get a different lens into.
• 46:08
  Shouldn't have been the result of the Department of Government
• 46:13
  efficiency. It should have been.
• 46:19
  Yeah, that's. Absolutely like to because you
• 46:23
  have the numbers, like you said, you have numbers, you have the
• 46:25
  data, you have the possibility to gather the data, you have the
• 46:27
  possibility to gather conclusions from the data.
• 46:35
  And right. And like this is kind of where I
• 46:39
  made my turn for the work that I do now, which is what I was
• 46:45
  seeing what you know, was that very smart, very reasonable,
• 46:50
  very well meaning people, right, which is the best case scenario.
• 46:53
  And that is not always the case that the information tools that
• 46:58
  we were building were they were they were outpacing people's
• 47:04
  abilities to really use them to incorporate them into their
• 47:08
  decision making, right? I mean, again, these are very
• 47:14
  smart, very well meaning people. This is the folks that I work
• 47:16
  with. But this new information
• 47:19
  landscape that we find ourselves in is unlike anything that we
• 47:23
  were ever trained for, and it was unlike anything that our
• 47:27
  brains have ever evolved to manage.
• 47:30
  So trying to figure out really how to ingest and process this
• 47:36
  amount of information in my own human brain, right, in a way
• 47:39
  that will allow me to make better and better choices to ask
• 47:43
  better, better questions. It's very, it's very
• 47:45
  challenging. I think the critical part is to
• 47:47
  build a relational connection between the data, to relate them
• 47:51
  somehow, to understand what's connected with what and why.
• 47:55
  And I think because of the amount of data that we are
• 47:58
  getting today, I think it's hard to it's hard to put it in in an
• 48:04
  Excel file to make. It for sure, and this is like
• 48:06
  the meaning making of it all is kind of how I refer to that,
• 48:10
  right? And it's not just the meaning,
• 48:13
  mate. You know, So like when you go
• 48:15
  way downstream on these processes, the meaning making is
• 48:18
  essentially like what you care about, right, which is maybe the
• 48:22
  choices your employees make is what you're attempting to figure
• 48:26
  out. And if they're making the quote
• 48:28
  UN quote, right choices. And then you have this data
• 48:31
  processing system that is documenting probably not that,
• 48:36
  but maybe something close to it. But now we're treating as that
• 48:39
  right? And, and there's a lot of
• 48:44
  organization that can actually can absolutely be done super
• 48:47
  well and it can absolutely be done not very well.
• 48:51
  And, and then it's being presented to folks who are
• 48:55
  supposed to use it to make some really impactful and important
• 48:58
  decisions. And and you better hope that
• 49:02
  that everything is working good by the time it gets up there.
• 49:05
  What was that aha moment when you realize there there is this
• 49:09
  need that you can cover? I had it it.
• 49:15
  It kind of grew over time. I don't know if it was a single
• 49:19
  moment, but I think, I think, you know, I kind of had it
• 49:28
  twofold where it was happening to me in my professional life,
• 49:31
  right where I was. I was kind of the person who was
• 49:34
  bridging between these information tools that were
• 49:38
  being built and the folks who were needing to use them to, to
• 49:42
  make choices. So kind of in both having the
• 49:46
  like very hands on experience of understanding those systems and
• 49:50
  also understanding the the needs of the folks who were asking for
• 49:54
  them, right. So the team that was building
• 49:56
  and the people that we're using, but then also just watching the
• 50:03
  the rest of human existence as it was happening in the 21st
• 50:06
  century, right. That I like I did online dating
• 50:11
  for many years and a bunch of my friends did and still are.
• 50:14
  And watching sort of these same patterns of frustration come out
• 50:20
  of just a a lack of reorienting to this problem of how do we get
• 50:28
  our human brains to collaborate effectively with these what are
• 50:34
  at the end of the day dating app or otherwise very powerful
• 50:37
  information tools. That that that is sort of like
• 50:42
  how I essentially just started in in literally daily
• 50:47
  conversations, sort of talking people through like what that
• 50:51
  information really was and how we got there and what its
• 50:55
  limitations were and whether or not the assumptions they were
• 50:58
  making about it were likely to be true or not.
• 51:01
  This sort of holistic probabilistic thinking that we
• 51:05
  now have to bring to our daily decision making.
• 51:08
  Right. Yeah, which, which you know,
• 51:10
  I'm, I'm now trying to bring to to whoever has an information
• 51:14
  tool. And they're like, why is it not
• 51:16
  giving me what was promised to me?
• 51:18
  I was told that this information tool would get me everything
• 51:21
  that I need to get what I want. And so frequently that is not
• 51:26
  the case. You, you said that we, we keep
• 51:32
  optimizing, but we never stopped to ask who are we optimizing or
• 51:38
  designing the systems for? And I think that's a, that's an
• 51:43
  amazing statement which fits, fits exactly what what you are
• 51:47
  saying. Because I think the difference
• 51:51
  between what the system or the computing system is giving you
• 51:55
  as a result of data and what they expect and what the, what
• 52:00
  the end user is expecting, It's a, it's a huge gap.
• 52:03
  And I think translating that message at the end, it's a it's
• 52:08
  a translation that we that we would need to have.
• 52:13
  And I think if you if you managed to cover this with
• 52:16
  remake the rules, I think that's going to be a money printing
• 52:19
  machine in the near. Future if I can somehow get a
• 52:25
  simple solution to one of the hardest problems we've ever
• 52:28
  created. No.
• 52:30
  But still you are on that on that pattern.
• 52:33
  Yeah, generally you talk about optimization fatigue.
• 52:45
  How did how did remake the rule rules become your your answer to
• 52:51
  the the culture pressure? I think, you know, like for me,
• 52:59
  Remake the rules is about understanding that we
• 53:03
  essentially live in a dynamic landscape with a bunch of
• 53:09
  pressures that were not designed for us individually in mind.
• 53:14
  So they might not work very well for us or they might actively be
• 53:18
  working against us, right? And absolutely, there are a lot
• 53:24
  of powers from these information technology tools that I do think
• 53:29
  have a lot of positive potential, but but they are not
• 53:33
  about us and they are not about the positive potential that that
• 53:38
  I can achieve. Dating apps is like a really
• 53:42
  good example, right? I think that they can be great
• 53:48
  and that folks can absolutely use them to great effect, but
• 53:53
  that they aren't really designed to actually get people what they
• 53:56
  want, which is high compatibility relationships with
• 54:02
  people. So kind of one of the things I
• 54:06
  tend to talk about a lot is that the information within dating
• 54:10
  app profiles does not actually tell you anything about that,
• 54:14
  right? It does connect you with people.
• 54:15
  It does give you some information that may or may not
• 54:18
  be true, right? But really it's about quantity
• 54:21
  and access and it does those things really well, but it
• 54:25
  doesn't do the compatibility really well, right?
• 54:28
  The actual sort of desire complicated social desired
• 54:33
  outcomes that people are looking for.
• 54:36
  But don't you think it has a, it has a part of of input problem?
• 54:42
  Because like we usually call it shit in shit out.
• 54:46
  But unfortunately now we talk about the dating gaps.
• 54:51
  I think people are feeding a narrative there.
• 54:57
  I love to read a lot. I love to spend time watching
• 55:00
  the sunset on the beach on a Tuesday morning.
• 55:06
  And I think a big part of it is still our fault in translating
• 55:12
  not what we want to have, but translate, or not what we are,
• 55:16
  but translating what we want to be.
• 55:19
  Or not even that what we think other people want us to be,
• 55:22
  which is probably both wrong, honestly.
• 55:25
  Absolutely. Yes.
• 55:26
  Completely agree. Completely agree.
• 55:28
  Yeah. And this is where that sort of
• 55:30
  optimization issue, right. So that is what I would say is
• 55:34
  happening there too, that folks are saying they they think my
• 55:39
  problem is not enough people are saying yes to me, right.
• 55:43
  Or swiping right to me, which means that I need to present my
• 55:47
  way myself in a way that optimizes the number of people
• 55:51
  that say yes, I want this person.
• 55:54
  I want to match with this person.
• 55:56
  It's a matter of numbers, not of quality.
• 55:58
  Exactly right, which which then just leads to everyone being
• 56:03
  super frustrated that they're now spending a bunch of time
• 56:05
  interacting with people that they don't get along with right
• 56:09
  But you know, it's like OK, well let's back it up a little bit.
• 56:12
  Let's see how we got there, right?
• 56:14
  And this, this is sort of the mindset shift that I work with
• 56:17
  people, but it's, it's based in these information dynamics,
• 56:21
  right? That like what you are doing is,
• 56:24
  is actually setting yourself up for a worse situation because
• 56:29
  now you have a larger pool of people who are less compatible
• 56:35
  with the outcomes that you want. So you're just creating sort of
• 56:38
  more informational labor for yourself, which is already the
• 56:41
  problem that we have. So we're just kind of
• 56:43
  exacerbating that same issue. So we are, we are, yeah, yeah.
• 56:50
  I think the focus on quantity over quality, it's something
• 56:53
  that we have it as an issue in the society at the moment
• 56:57
  because we do that in mostly everything.
• 57:01
  And I think the absolutely right you are, you are not focusing on
• 57:06
  having that perfect match of 1 to 1, you are you want to have
• 57:09
  that match of 1 to many so that you can choose again because you
• 57:13
  don't really know what you want. Yeah, And in some cases there is
• 57:18
  power in volume, but it is not the solution to every problem.
• 57:23
  And actually like where the power in volume comes from is
• 57:28
  the capacity to then distill valuable information from that,
• 57:34
  right? So again, the dating app is
• 57:36
  doing that pretty good, especially depending on what
• 57:39
  you're sort of locational dating app culture is, right?
• 57:43
  If most people are using the same dating app, if you live in
• 57:46
  a large city, that can be a ton access to a ton of people.
• 57:50
  But if you are just maintaining that volume, it what it it's
• 57:54
  nothing to right? It's not giving you anything
• 57:56
  meaningful. If you would have to put it in,
• 58:01
  let's say one sentence, what do you say?
• 58:03
  The mission of Remake the rules would be more than one sentence.
• 58:10
  I don't want to keep you straight.
• 58:12
  Thank you. I, I really want to.
• 58:19
  So there are so many large institutions, governmental, you
• 58:23
  know, for profit companies, whatever, who are able to have
• 58:29
  big data teams. You know, folks like me who are
• 58:32
  really taking strong advantage of information dynamics,
• 58:37
  information science, decision science and and creating a lot
• 58:43
  of profit from it, right? A lot of hopefully societal
• 58:50
  benefit from it, depending question mark, right?
• 58:52
  Exactly. And and that's something that,
• 58:58
  you know, in my capacity as a public servant, I was proud to
• 59:02
  work on for many years. But I got to a point where I
• 59:06
  kind of wanted to shift the access to this skill set, this
• 59:12
  like reframing to be more accessible to more people,
• 59:16
  right, to work on problems that were just as impactful to
• 59:20
  people's lives. Like the, you know, like I do
• 59:25
  still work on really big projects with executive
• 59:28
  leadership teams. But the online dating is still
• 59:31
  really important to me because for most people, who they choose
• 59:35
  to invite into their life is the most important decision they'll
• 59:38
  ever make in their life, right? Who who we choose to be with
• 59:43
  tremendously impactful. And it is now so complicated by
• 59:49
  this like informational landscape, right, that nobody is
• 59:52
  used to using well, so, so that that is really what what drew me
• 59:58
  to the work and, and why I love it so much.
• 1:00:02
  Really good point about the money making goal of the of the
• 1:00:09
  of the choice tech because the the the only thing that we are
• 1:00:13
  pushed to is either towards buying either towards feeding
• 1:00:16
  the algorithm so that we get the right commercial.
• 1:00:19
  I was screwing my phone and I'm sorry for that, but I I'm
• 1:00:22
  reading, listening a book now, which is called Careless People,
• 1:00:27
  which is written by Sarah Wynne Williams.
• 1:00:31
  She was a, if I remember it correctly, the political liaison
• 1:00:41
  for Facebook. And she thought at the beginning
• 1:00:44
  when she started to work there, that she can make an impact by,
• 1:00:48
  by improving in a good way, the way in which Facebook is dealing
• 1:00:53
  with political interactions, for dealing with political regimes
• 1:00:57
  and so on. And let's see, that was not a
• 1:01:02
  goal. Yeah, a good book.
• 1:01:05
  I'm familiar with the story and what you were talking about.
• 1:01:07
  OK, you know it, you know it, right?
• 1:01:09
  It's, it's, it's an amazing book and it's amazing how how good or
• 1:01:15
  with which positive attitude she entered that world and how hard
• 1:01:19
  was for her to enter that world. And for anyone who hasn't read
• 1:01:23
  the book, book, I think it's a, it's a food recommendation from
• 1:01:26
  both of us. It's a really good book.
• 1:01:30
  Yeah, yeah, I like there is, there is so much capacity for
• 1:01:40
  how we use these information tools as individuals, as
• 1:01:43
  leaders, as kind of the other big bucket of folks I work with
• 1:01:46
  as small business people, right. Because they are managing so
• 1:01:50
  much, so many information tools that are supposed to make their
• 1:01:53
  business run or run into the ground or who knows what, right.
• 1:01:57
  And, and a person's livelihood, especially if they're also
• 1:02:00
  managing a small team, right, is incredibly stressful and
• 1:02:03
  incredibly important choices that they are making.
• 1:02:08
  But I totally lost my train of thought.
• 1:02:13
  What are we talking about again? I love it.
• 1:02:18
  I love it. I love it because it we ran so
• 1:02:20
  much that we forgot where we started from.
• 1:02:23
  But I love this is the natural flow of discussion that I love.
• 1:02:25
  I love it. We started from the mission of
• 1:02:28
  rebuild the rules and how do we how we can use the data in the
• 1:02:31
  benefit of the user, not in the benefit of the company.
• 1:02:35
  For sure, for sure. And like right now, there is a
• 1:02:38
  huge power imbalance there, a huge power imbalance, right?
• 1:02:42
  And a lot of that is for me, I think about who is able to take
• 1:02:47
  advantage of the technology itself, literally building it,
• 1:02:52
  right, But also the skill set around orienting around it,
• 1:02:57
  harnessing it, how it's being understood and collaborated
• 1:03:01
  with. And, and I guess I'm just ready
• 1:03:05
  to, to work with folks who are being tremendously impacted by
• 1:03:11
  this technology, but not necessarily have as many
• 1:03:14
  resources as many people who just like, have their back and
• 1:03:18
  are in their court about like, what does this mean for you?
• 1:03:21
  Like, how can we really figure out how to live well in this
• 1:03:26
  wild new reality that we all find ourselves in?
• 1:03:29
  Right. And and that's what I love doing
• 1:03:31
  for folks. Maybe it's A2 direct question,
• 1:03:37
  but how do you, how do you help someone because we, we have to
• 1:03:42
  hear 2 two different issues as far as I was able to identify
• 1:03:49
  them. One of it is that we have this,
• 1:03:52
  I'm sorry, we have this data that we provide to the company
• 1:04:00
  willingly in our benefit that is used in our benefit to improve
• 1:04:08
  our the things that we see. And the second problem that I
• 1:04:14
  also I considered an even bigger one.
• 1:04:18
  We get this, this is this nudges to make the decisions based on
• 1:04:24
  the small informations that we get that is slightly nudging us
• 1:04:31
  left or right without us even noticing it.
• 1:04:35
  Yes. And I think that the the the the
• 1:04:38
  second one is the biggest issue from my point of view because
• 1:04:41
  you don't realize it when it's happening.
• 1:04:43
  What weapons do we have on our side as B pet human being
• 1:04:50
  without being able to analyse all the data that is provided to
• 1:04:54
  us? Yeah, to face this issue or to
• 1:04:58
  push this issue away from us. Yeah.
• 1:05:01
  So that issue, I mean, that is one of the huge, huge things
• 1:05:04
  that I work with folks on is making that invisible, visible
• 1:05:10
  in the decision making process as folks are trying to use these
• 1:05:14
  sort of digital information tools is choice tech, right.
• 1:05:16
  Any any tech tools that are going to be impacting the way
• 1:05:20
  that we make choices. And I like essentially the work
• 1:05:26
  that I do ends up being I always center it sort of on whatever
• 1:05:29
  practical problem that a person is struggling with at the time.
• 1:05:34
  But the work that we do kind of ends up being like 40% practical
• 1:05:38
  maybe and then 60% existential as we are like exactly wrapping
• 1:05:44
  our heads around what is actually happening when a person
• 1:05:50
  is interacting with digital information.
• 1:05:53
  How is it pushing and pulling and speaking to you in those
• 1:05:58
  ways that that maybe are very honest to you and maybe you have
• 1:06:02
  no idea about? And when I work with folks,
• 1:06:06
  right, we are kind of doing that together.
• 1:06:08
  So I, I am using my understanding of brains and also
• 1:06:13
  of these information platforms to sort of talk folks through
• 1:06:18
  this process. Like when you look at this
• 1:06:21
  information, what does it tell you?
• 1:06:23
  And based on what you think it tells you, what then are you
• 1:06:28
  doing next? But something we also do and
• 1:06:31
  something that everybody can do. When you encounter information
• 1:06:35
  and, or, or even just in your daily life, I'll have moments.
• 1:06:42
  And I know everybody has these moments where they will maybe be
• 1:06:45
  struck by an anxiety or by a fear.
• 1:06:50
  And one of the first things that I do for myself and that I do
• 1:06:54
  for clients is ask them where that feeling is coming from.
• 1:06:59
  And whether or not it is coming from information that has been
• 1:07:03
  brought to them and delivered to them right outside of their own
• 1:07:07
  body, outside of their own experience.
• 1:07:10
  Or whether or not this is an anxiety and a fear about
• 1:07:15
  something that they are literally living through that
• 1:07:18
  their body and brain are a part of experiencing, right?
• 1:07:23
  That that there is maybe some sort of problem or hurdle or
• 1:07:26
  concern that they are living through and that trying to
• 1:07:31
  figure that out, right? Is this part of my in person,
• 1:07:35
  embodied lived experience or is this just part of this huge wave
• 1:07:41
  of information that is sort of being shot at me, right?
• 1:07:44
  Like a cannon over and over and over and over again all day
• 1:07:47
  long? And that while there still could
• 1:07:50
  be a problem, you know, right. Like we got lots of scary
• 1:07:53
  information, anxiety provoking information that that does get
• 1:07:56
  delivered to us. And that doesn't mean that it
• 1:07:58
  isn't a problem and that it isn't anxiety provoking, but it
• 1:08:01
  is very different about sort of where the problem sits and ergo
• 1:08:07
  where the solution to that problem might sit.
• 1:08:10
  If that's something that we can, that you can work on as an
• 1:08:15
  individual, or if this is something where it is more a
• 1:08:20
  conversation about collective action, right, and cultural and
• 1:08:24
  societal action. It's a, it's a hard, it's a
• 1:08:29
  process, right? It's not something that you can
• 1:08:31
  do from today to tomorrow. It's a process because it's we
• 1:08:35
  got inside the situations step by step so it don't happen at
• 1:08:40
  once. Yeah, absolutely.
• 1:08:44
  And I think that's, that's impressive that we, we got this,
• 1:08:50
  like you said, this powerful computers, like you said before,
• 1:08:53
  to to in make your our life easier.
• 1:08:55
  But instead they are even without us knowing, starting to
• 1:09:04
  controlling the way that we think or the way that we take
• 1:09:08
  decisions. And that's kind of wrong.
• 1:09:16
  Can you, are you able to share a client transformation story?
• 1:09:20
  I'll be curious. With as less details as
• 1:09:29
  possible, but yeah, I'm curious. I think so.
• 1:09:35
  So, OK. So here's one one that I kind of
• 1:09:42
  here's like a transformation that I may be seeing a pattern
• 1:09:44
  of right is we'll take it from the perspective of small
• 1:09:50
  business owners. But what I'm seeing with these
• 1:09:54
  folks is just an incredible crush of choice tech that is
• 1:10:02
  being like rained down upon them, but it's supposed to like
• 1:10:05
  be fix their business, right? And, and so there's essentially
• 1:10:09
  that they're experiencing this sort of environment where
• 1:10:13
  solutions are being brought to them just like raining, raining
• 1:10:17
  down upon them of all of these software information solutions.
• 1:10:22
  And they are being told that without it, in this new
• 1:10:28
  environment, right, where there's so much novelty, where
• 1:10:31
  there's so much change that they will absolutely need it to
• 1:10:34
  survive. And without it, they will go out
• 1:10:36
  of business. And not only that, but it's kind
• 1:10:39
  of embarrassing that they don't understand this technology
• 1:10:42
  already that literally didn't exist six months ago, right?
• 1:10:45
  So there's kind of a lot of shaming and uncertainty and just
• 1:10:53
  just that I think it's like pretty unfortunate, right?
• 1:10:56
  Pretty pretty mean ways of manipulating these folks into
• 1:11:05
  feeling like they need this tool to survive, right?
• 1:11:11
  And so kind of the role, one of the roles that I end up playing
• 1:11:16
  is essentially just being in that person's corner, right?
• 1:11:19
  And they have an expertise, but it isn't an information
• 1:11:21
  technology, right? So they're like, I'm just out
• 1:11:24
  here trying to be an expert in what I do.
• 1:11:27
  But now apparently I also have to be a complete expert in like
• 1:11:31
  every operational and administrative software tool
• 1:11:33
  that has ever existed, right? Yeah.
• 1:11:36
  And so, so I kind of get in their corner and we really talk
• 1:11:41
  about what is and is not happening with their business,
• 1:11:45
  what it means for when somebody says that they have an
• 1:11:49
  information tool that understands their business
• 1:11:51
  better than they do, right, which is almost certainly not
• 1:11:54
  true. And now we can sort of of of
• 1:12:00
  recenter that business owner and in what they are attempting to
• 1:12:06
  achieve and what they need to do to actually add stability, get
• 1:12:12
  where they need to go, organize their information, whatever it
• 1:12:14
  is that they need to do, right. We can re identify the problem.
• 1:12:18
  And so much of actually what I end up doing with folks is
• 1:12:23
  identifying the actual problem because right now it's even hard
• 1:12:27
  to understand what the problem is.
• 1:12:31
  And we got a lot of information telling us what the problem is,
• 1:12:33
  right, Because there's a lot of people who want to sell us the
• 1:12:35
  solution to whatever problem they say we have.
• 1:12:38
  Yeah, yeah. And.
• 1:12:40
  If the if the problem is not there, we are.
• 1:12:43
  Let's create the problem so that we give a solution for.
• 1:12:47
  So, so for me, like that transformation for folks is so
• 1:12:51
  important because I want to both in that moment, like help them
• 1:12:57
  to sort of re figure out what the actual problem is.
• 1:13:00
  Recenter them, give them the tools for managing the sort of
• 1:13:04
  deluge of of the solutions that are coming at them, solutions
• 1:13:08
  that are coming at them. But then also, you know, the
• 1:13:11
  skill set that I'm transferring to people is not as like a data
• 1:13:16
  scientist, right? Like not everybody is going to
• 1:13:18
  be a data scientist. Like, I don't know, maybe in
• 1:13:22
  future generations everyone's going to have to be, I don't
• 1:13:24
  know. But right now that's not really
• 1:13:27
  feasible. That's not the point, but the
• 1:13:29
  point is to give people the capacity to better understand
• 1:13:37
  what the information is that's coming at them, why it's coming
• 1:13:41
  at them, and how to sort of ask questions that will empower, re
• 1:13:46
  empower them in this dynamic, right?
• 1:13:49
  So that they can take a little bit more of that control back.
• 1:13:53
  They don't maybe need to know everything or understand exactly
• 1:13:58
  what this person is talking about.
• 1:13:59
  But what we can figure out is whether or not a person is
• 1:14:03
  willing to answer their questions, right?
• 1:14:06
  And if they're not willing to answer their questions, we have
• 1:14:07
  a huge problem on our hands and we probably don't want to talk
• 1:14:09
  to that person anymore. Yeah, right.
• 1:14:11
  Kind of kind of situations like that.
• 1:14:15
  I, I started this podcast about 5 months ago and I can, I, I'm
• 1:14:20
  not able to count anymore the amount of CEO experts that
• 1:14:25
  contact me to optimize my channel.
• 1:14:27
  And due to the fact that I have, I'm not, I'm not saying that I'm
• 1:14:33
  an expert in anything, but I have some, I have a bit of
• 1:14:38
  background of everything that is happening around this.
• 1:14:40
  I and it's, it's interesting. I, it fits your, your, your
• 1:14:44
  description, Emily. This is what's, that's why I was
• 1:14:47
  smiling the, the whole time because it fits 100% the
• 1:14:51
  description. Yeah, sending me a print screen
• 1:14:54
  of a YouTube video with a lot of Red Arrows like this is wrong,
• 1:14:57
  this is wrong. This is wrong to give you that
• 1:14:59
  anxiety to give you that pressure to take you have to
• 1:15:02
  take this is a now because you are losing a lot of a lot of
• 1:15:06
  possible viewers that you could have, but you don't have because
• 1:15:09
  not optimized. And I'm the expert, I'm the guy
• 1:15:11
  I work with that and that and that.
• 1:15:13
  And I'm, I, I cannot believe it's, it's, it's a shame that
• 1:15:17
  you don't get the views because the, IT fits 100% of pattern.
• 1:15:23
  And to be honest, I always ask the same question.
• 1:15:26
  And it's such an easy question. I always ask, OK, show me your
• 1:15:29
  YouTube channel. And then there is nothing
• 1:15:31
  afterwards. There you go.
• 1:15:33
  Yeah, there you go. You gotta, you have a good
• 1:15:35
  litmus test. Yeah.
• 1:15:41
  And I think too, like if it all comes down to to what the point
• 1:15:47
  of this is for you, right. And this is kind of where the
• 1:15:50
  recent ring comes like is the point for you to invest whatever
• 1:15:56
  is necessary to become the like whatever as high a possible
• 1:16:01
  viewer rate on YouTube as Yeah, right.
• 1:16:03
  So like. I think that's the problem.
• 1:16:05
  And we can then we can not worry about, right, Because the
• 1:16:09
  solutions that are being brought to you, one, they might not do
• 1:16:12
  that at all, right? That's kind of a separate
• 1:16:14
  question, but that is what they are purporting to do and you
• 1:16:17
  don't even want that, right? So, and, and there's a lot of
• 1:16:21
  sort of that that that's happening too when I work with
• 1:16:24
  folks about that recentering, like what is the purpose behind
• 1:16:30
  what you are doing? Like this is about living a
• 1:16:32
  life, right? And, and you get to choose how
• 1:16:37
  you get to live it. Are there restrictions?
• 1:16:39
  Are there challenges? Absolutely, absolutely.
• 1:16:42
  But but you should still be empowered to participate in the
• 1:16:47
  major decisions of your life, you know, even though a lot of
• 1:16:50
  these tools are trying to to change that for you.
• 1:16:53
  A. Few A few years ago I read
• 1:16:58
  Nudge. I don't know if you know the
• 1:17:01
  book, you know it. I'm familiar.
• 1:17:04
  It was an amazing book and this was one of the of the main main
• 1:17:09
  points from there as well that you have to know what you want.
• 1:17:14
  And yes, sometimes the nudges that you get from I don't there
• 1:17:18
  is a good example comparing the healthcare in US with the
• 1:17:24
  healthcare in I think it's Sweden, if I remember it
• 1:17:26
  correctly, where in US you have to choose your provider.
• 1:17:30
  In Sweden, you were automatically assigned to 1 and
• 1:17:34
  you were able to switch. But because of that, the amount
• 1:17:38
  of people that registered for Medicare in Sweden was more than
• 1:17:41
  the guys registering in the US because there was nothing active
• 1:17:45
  that you had to do. So let's say, like you said at
• 1:17:48
  the beginning, there are good examples and bad examples for
• 1:17:51
  sure. But I think it's, it's hard for
• 1:17:56
  someone who's a plumber, who's a good plumber.
• 1:17:58
  It's hard to navigate this world that because it's not able to
• 1:18:02
  understand it. Of course, my, my daily job is
• 1:18:05
  helping me and my experience that I got until now, but I
• 1:18:08
  think that's a critical point and I cannot recommend it
• 1:18:12
  enough. If someone has an issue to come
• 1:18:15
  to you, because before you pay someone to give you a
• 1:18:22
  subscription for the next two years, for for for something
• 1:18:26
  that you don't need, that someone consult you in that way,
• 1:18:31
  because that's a, that's a dangerous one.
• 1:18:34
  And one of the most challenging parts to about the time that
• 1:18:38
  we're living in is that novelty is not going to slow down
• 1:18:44
  anytime soon, right? So like, even if you can wrap
• 1:18:47
  your brain around one of these tools in order, you know, like
• 1:18:52
  you become an expert in it and then you make a choice about it,
• 1:18:55
  right? But two years from now, the
• 1:18:58
  chances that the tool landscape is totally different is pretty
• 1:19:01
  high, right? So it's it's really more about
• 1:19:04
  being able to manage that uncertainty, manage that novelty
• 1:19:08
  than becoming an expert and in anyone given tool.
• 1:19:13
  And what we have to say, Emily here is that the the the small
• 1:19:18
  business owners that were sell were sold something.
• 1:19:22
  I think there are the, I don't want to say the happy example,
• 1:19:25
  but still not so sad examples as the people in there, let's say
• 1:19:33
  mid 50s, mid 60s who get scammed by different technical,
• 1:19:38
  different social media tricks. There was A and I realized that
• 1:19:44
  when you said it's the, there are always new ideas coming in
• 1:19:47
  because there was a scam that was happening in Romania a few
• 1:19:52
  months ago where they was, they were calling via WhatsApp and,
• 1:19:58
  and just saying that. They need a code that they got
• 1:20:02
  via WhatsApp because I'm your daughter.
• 1:20:04
  I'm your, I don't know son. And they were holding the the
• 1:20:09
  WhatsApp account and then they were taking the possession of
• 1:20:12
  the phone and transferring money from the mobile banking apps.
• 1:20:17
  Yeah. And this is really on a
• 1:20:20
  different level, but still somehow going into the same
• 1:20:23
  direction. Like be aware of what you need
• 1:20:26
  actually. How can we take control of this
• 1:20:34
  algorithm, Emily? How can we make sure that we are
• 1:20:38
  not the slaves of it? I, I think that that is the
• 1:20:47
  question, right? Well, the first question is what
• 1:20:51
  is the benefit to me, right? What, what is the balance here?
• 1:20:55
  The comparative because you know, for, for the folks who are
• 1:21:01
  willing, ready and able to throw away all their electronic
• 1:21:04
  devices and go beyond a goat farm, like more power to you,
• 1:21:08
  right? Like great.
• 1:21:11
  But there's a lot of us who are maybe unable or unwilling to
• 1:21:16
  fully step away from all of the technology tools at our
• 1:21:20
  disposal. And then it just becomes a
• 1:21:24
  question of is this the right choice for me?
• 1:21:29
  Now, again, understanding that there is going to be quite a lot
• 1:21:34
  of uncertainty there, but that that isn't necessarily a bad
• 1:21:39
  thing because that is not something that we're ever going
• 1:21:41
  to be able to fully get rid of. But it is kind of a thoughtful
• 1:21:46
  question that we can engage with where again, we are sort of like
• 1:21:50
  recentering ourselves, our goals, what we want, what the
• 1:21:53
  cost to us is and whether or not that is a cost that makes sense
• 1:21:59
  for us. And then there you have it.
• 1:22:04
  Do you think it's it's a good deal to share our data for and
• 1:22:14
  never? No, probably not.
• 1:22:17
  I I didn't even get to finish the sentence, but I'm fully with
• 1:22:20
  you. There is no benefit in it.
• 1:22:23
  Hopefully not. Yeah, Yeah, it's interest.
• 1:22:29
  You know, one of the things that I think about a lot and I tend
• 1:22:32
  to write about a lot is the way in which we are externalizing,
• 1:22:36
  or I'll also say outsourcing our thinking and our deciding.
• 1:22:43
  So it's essentially this idea that we are letting computers or
• 1:22:47
  maybe social norms or whatever process information for us, like
• 1:22:53
  tell us what we should and shouldn't be doing, what is, and
• 1:22:58
  it's not happening, right? And, and now we're sort of
• 1:23:01
  putting a lot of that into digital tools too.
• 1:23:06
  So one of the things I'm working on as an example is like this,
• 1:23:09
  when to rest, right? Like, that feels like it should
• 1:23:13
  be a very simple question for us as biological creatures, but it
• 1:23:17
  actually is incredibly complicated to figure out when
• 1:23:21
  to rest, right? And that's like a long history
• 1:23:26
  of why that's the case. And it's certainly, you know, we
• 1:23:30
  were not fully just falling down and going to sleep whenever
• 1:23:35
  we're tired, right before computers were around, right?
• 1:23:39
  We have structured sleep for a long time, but but now we also.
• 1:23:46
  Have I'm sorry for nothing but it sounds when you put it like
• 1:23:49
  this, it sounds so stupid. I'm sorry.
• 1:23:55
  Wait, which part? Just like laying down and
• 1:23:56
  sleeping whenever you're tired. Exactly.
• 1:23:58
  Like no, no, no, not not doing it.
• 1:24:00
  So like you said, it's that we, we have to make a rule.
• 1:24:02
  No, we don't. We just we, our body is tired.
• 1:24:05
  Then we go to sleep. It's it's so easy.
• 1:24:09
  But no, not even, not even close, not even close, right?
• 1:24:14
  And now, even if you have a schedule that allows for that,
• 1:24:18
  you know, I feel like a lot, there's a lot of cultural
• 1:24:21
  pressure depending on your culture to not rest, even if you
• 1:24:25
  have the time to rest, because maybe it's the afternoon or you
• 1:24:28
  haven't, you know, checked off enough on your To Do List or
• 1:24:31
  whatever, whatever, right? Like it's really complicated now
• 1:24:37
  and, and now we're sort of putting a lot of our own
• 1:24:42
  thinking and processing and decision making into these
• 1:24:44
  digital tools that are extracting that data and are
• 1:24:47
  making algorithms and are sort of like re impressing these
• 1:24:52
  patterns on us in ways that we, we don't even know like where
• 1:24:58
  it's going to go. Most probably, it's coming to
• 1:25:00
  the same conclusion. Whenever you feel tired, go to
• 1:25:03
  sleep. Go to sleep, you're tired.
• 1:25:06
  Lay down. I think in the last period we
• 1:25:12
  have a lot of AI, we are have a lot of AI usage in taking
• 1:25:17
  decisions, but in decision making that usually was
• 1:25:23
  something that we were able to do on our own.
• 1:25:27
  The sleeping is one example, but for me, the the most, the most
• 1:25:35
  important ones are the one when we say, OK, because there are a
• 1:25:39
  lot of a lot of apps that use AI to tell you what you cook to the
• 1:25:42
  what you should cook today. That tells that uses AI to tell
• 1:25:47
  you, I don't know how, how many kilometres should you run today
• 1:25:51
  to be to feel good? What's your take on this?
• 1:25:56
  I think like, again, to me, like I, I don't mean to be too
• 1:26:02
  repetitive, but a lot of it comes down to that balance.
• 1:26:06
  Like I think that we're living through an extraordinary era of
• 1:26:10
  choice inflation where people are being asked to make way more
• 1:26:15
  choices that are way more taxing, right?
• 1:26:18
  So we get in this pattern of exhausting ourselves, you know,
• 1:26:22
  this decision fatigue with how many choices we have to make.
• 1:26:25
  And that leads us to make poorer and poorer choices because we
• 1:26:31
  don't have the energy to make some choices.
• 1:26:33
  So really, we kind of have to conserve where we can and where
• 1:26:38
  the stakes are low, right? Just how I think about it.
• 1:26:41
  So like, what to eat dinner tonight, those stakes, you know,
• 1:26:44
  for me, right, as long as I get fed.
• 1:26:47
  But right what how to run my business, what the strategic
• 1:26:54
  goals of my company are going to be this quarter, who I'm going
• 1:26:57
  to invite into my life. Like those are questions that
• 1:27:00
  are worth conserving energy for in order to make really well,
• 1:27:05
  that are worth taking the time and care to really think through
• 1:27:10
  and build knowledge and processes for to do really well.
• 1:27:15
  So like I think that there is good potential for help in some
• 1:27:22
  decision making depending on the type of decision, but there is a
• 1:27:26
  real potential for it to be very problematic if we're asking for
• 1:27:29
  too much help with some of these choices that really we should we
• 1:27:33
  should be taking full control over.
• 1:27:35
  I think we are making ourselves less risk takers because we are
• 1:27:42
  afraid to take the decision if we don't have the support of the
• 1:27:45
  AI. I think we are getting less St.
• 1:27:50
  marked because we we talk at the beginning about this getting
• 1:27:54
  less problem solving without the help of the Internet.
• 1:27:57
  I don't know if you know to last week, last week or the beginning
• 1:28:00
  of last week, there was a big power outage in the whole Spain
• 1:28:03
  and Portugal and and part of France.
• 1:28:07
  When we think about the situation like this where we are
• 1:28:10
  not able to take our own decisions without, without,
• 1:28:15
  without our phone, that could be a problem in that case.
• 1:28:19
  But of course, to, to go into the business world, I think
• 1:28:24
  that's even a difficult one to, to ask an AI or try to tell the
• 1:28:31
  AI what could be your strategic goal of your, of your company.
• 1:28:37
  I don't know if you know the the story of the fisherman, which I,
• 1:28:41
  which I love most probably know it, but stop me if you do with
• 1:28:45
  the businessman meeting a fisherman coming from the he was
• 1:28:49
  in holiday. The businessman and the
• 1:28:51
  fisherman was coming back with some midday was midday with a
• 1:28:56
  small bag of fish. And so there.
• 1:28:57
  But where do you come? Where have you been?
• 1:29:00
  I was fishing. Why do you come back so fast?
• 1:29:02
  Yep. So I usually catch some fish,
• 1:29:05
  then I go home. I'd even to my wife.
• 1:29:07
  She's cooking them and then we sit around in the house.
• 1:29:11
  Then we have a glass of wine in the evening and that's it.
• 1:29:13
  But no, no, no, you are doing. Do you know the story?
• 1:29:16
  No. You're doing it all wrong.
• 1:29:19
  No, you should stay the whole day to fish so that you you are
• 1:29:22
  making some water and then you you you eat some of them and
• 1:29:25
  then you sell some of them. Yeah, but but why?
• 1:29:28
  Yeah, because then you with the money from that you get from
• 1:29:31
  selling the fish, you get to buy another boat to hire some more
• 1:29:33
  people and do the stuff for you so that you don't have to do
• 1:29:37
  this anymore. Yeah, but why?
• 1:29:40
  So that you can stay home and have a glass of wine with your
• 1:29:42
  wife. Mm.
• 1:29:43
  Hmm. Mm, hmm, yeah.
• 1:29:46
  And this is, this is somehow the world that we are going in now
• 1:29:50
  because we are, we are pushing, we're pushing, pushing, pushing
• 1:29:53
  and we don't know exactly what we want.
• 1:29:55
  And I think the decision making is a is a big process.
• 1:29:58
  And somehow we're going around the circle going the hard way,
• 1:30:02
  but ending up having the same, the same decision, actually the
• 1:30:08
  same result. For sure.
• 1:30:10
  Yeah. And I mean, like, right, making
• 1:30:13
  making complex choices was not easy, was never easy, right?
• 1:30:19
  And now we've also added these incredibly powerful digital
• 1:30:26
  information tools into the mix, right?
• 1:30:27
  This, this whole landscape of choice tech.
• 1:30:31
  And that's right, that's my sweet spot is this, this
• 1:30:34
  understanding that it's both that complex decision making was
• 1:30:38
  never easy and there's a lot going on there from person's
• 1:30:43
  perspective and what they got going on from their culture,
• 1:30:46
  from society, whatever, whatever.
• 1:30:48
  But then also we're like layering in tons of choice tech
• 1:30:53
  and, and it's, it's making it even harder.
• 1:30:57
  I think the, the big benefit of, of any computing power is to
• 1:31:02
  help you in the research process and to show you the variables.
• 1:31:06
  And I think the, the thing that we should not do, we should not
• 1:31:11
  let be done by the AI or by the computing part or whomever is
• 1:31:14
  to, to do the hard part, like to take the decision for us.
• 1:31:19
  Because when you have all the information and you are able to
• 1:31:22
  get them faster, I think that's something that Tehran would do.
• 1:31:25
  But to be able to read through those information, I think
• 1:31:29
  that's that's something that that we should do around on on
• 1:31:33
  our own. Yeah, it's like this.
• 1:31:38
  I mean, kind of in line with what you're talking about.
• 1:31:42
  One of the problems that I see with AI use or even just
• 1:31:47
  conversations around lots of information is this idealized
• 1:31:52
  average that what is kind of often being brought to you is
• 1:31:57
  some sort of average amalgam of the middle.
• 1:32:02
  And then that becomes a reality, right?
• 1:32:05
  And it's really limiting to the variability of what is
• 1:32:10
  happening, but also what is possible to happen too.
• 1:32:14
  And that and that, that is a big problem.
• 1:32:17
  And I think where we're seeing some of the best benefit of
• 1:32:20
  these AI tools and where we will continue to see the best benefit
• 1:32:23
  are ones that are built for very specific purposes because you
• 1:32:28
  can't actually make them work very well for one thing, right,
• 1:32:32
  like the cancer detection being that example, like AI is being
• 1:32:36
  built to answer that one question.
• 1:32:39
  And and if it is done well, if it is done thoughtfully, like we
• 1:32:43
  are seeing that there are positive outcomes there.
• 1:32:45
  But the idea that you have sort of like a big broad tool that
• 1:32:48
  can do anything, what it's going to give you is this, you know,
• 1:32:52
  idealized average of whatever the data set is that it's
• 1:32:56
  pulling from, which we already know is probably going to be
• 1:32:59
  pretty problematic because a bunch of humans made it, right.
• 1:33:03
  Yeah. True, true.
• 1:33:06
  Yeah. Yeah.
• 1:33:08
  What's 1 of the what's what would be 1 business topic or one
• 1:33:13
  cultural social topic that you would try to get get AI
• 1:33:17
  completely out of? I my, my stance is really about
• 1:33:32
  doing it well. OK, Yeah.
• 1:33:35
  And I think that humans are very capable of doing things very
• 1:33:39
  poorly, as is AI, right? I mean it they're, they're one
• 1:33:45
  in the same, really. But there are benefits to both.
• 1:33:51
  And they're big downsides too. Yeah.
• 1:33:55
  True. Yeah, absolutely.
• 1:33:56
  There we go on both sides. Emily, what's the what's the
• 1:34:01
  long term impact that you hope to to have with Remake the
• 1:34:08
  rules? I, I, I just hope to be part of
• 1:34:12
  this bigger conversation about what living in the information
• 1:34:17
  age means to people and about what living well in the
• 1:34:22
  information age can look like. You know, I, I do hope to have
• 1:34:29
  positive impacts on the folks that I work with, but I think
• 1:34:33
  that this bigger conversation is, is something that's going to
• 1:34:38
  be really important to pretty much everybody and I hope at
• 1:34:43
  least hope to be a part of that. It was a it was AI hope I for so
• 1:34:52
  I hope that that that you'll be part of the of the of the future
• 1:35:00
  decision making process because you you are well intended and
• 1:35:06
  that's not something that's happening this in this world
• 1:35:09
  anymore. And I think.
• 1:35:10
  Thank you. I appreciate that.
• 1:35:12
  That's working. You're welcome.
• 1:35:16
  Working the benefit of the people.
• 1:35:17
  It's something that we don't do. No, none of the big companies
• 1:35:22
  are doing it because usually there is no profit out of that.
• 1:35:26
  And the main goal is money. And after that it's something
• 1:35:30
  that we maybe we can do something to cover the money
• 1:35:33
  that we made. And I think that's I really hope
• 1:35:37
  that that would be a huge success out of this because it's
• 1:35:43
  you deserve it. I have to say, after this
• 1:35:45
  discussion that we had, it was a a pleasure for me.
• 1:35:51
  But before we wrap it up, I have AI have a small set of of rapid
• 1:35:57
  fire questions. And thank you so much for that
• 1:36:01
  was incredibly complimentary. I really appreciate it.
• 1:36:03
  Oh, thank you. No, that was an honest opinion.
• 1:36:06
  Thank you so much. But you're welcome.
• 1:36:07
  You, you, you, you word it. I'm just stating the facts.
• 1:36:15
  I haven't had any nudge from any direction.
• 1:36:19
  That you know of. OK, OK, now I'm afraid.
• 1:36:29
  Emily, what's 1 app that you secretly love but you kind of
• 1:36:33
  hate? Reddit.
• 1:36:38
  I I saw the same today. I most of my guests are known
• 1:36:46
  through Reddit. Two different subways, but it
• 1:36:48
  takes you a lot of time. Yeah, it's, I mean, I whatever.
• 1:36:53
  I love people. I find them fascinating.
• 1:36:55
  I know we're complicated creatures, Reddit, you know,
• 1:36:57
  it's where people go. It's interesting.
• 1:37:01
  I think it's I, I was raised in in the and I think you and both
• 1:37:07
  were raising the period of the forums.
• 1:37:10
  You had forums? Yeah, that I was a little on the
• 1:37:15
  IA little young I guess, but yes.
• 1:37:17
  OK. And I think Reddit kind of seems
• 1:37:21
  the forum like app again that somehow made me feel and I love
• 1:37:26
  the fact that somehow people are more open because they are
• 1:37:28
  anonymous there and I think that makes them quite easy.
• 1:37:36
  Yeah, but I know what you mean. Like I'm I'm there.
• 1:37:39
  I thought about this like, what's the less informed
• 1:37:45
  decision that you took in your life?
• 1:37:48
  I mean, if if I were to tell you that I was like mature,
• 1:37:57
  perfectly capable 17 year old choosing where to, like, go
• 1:38:02
  after high school, it would be a lie, right?
• 1:38:04
  I was. I was a young person who was
• 1:38:07
  barely figuring it out. And it worked out, thank God.
• 1:38:12
  But yeah, I did not know what I was doing.
• 1:38:14
  I love this one. I really, I love this one
• 1:38:16
  because this is something that there isn't generally something
• 1:38:19
  which is called the gap year. And usually everybody's taking a
• 1:38:21
  gap year. And if the US is the same, but
• 1:38:23
  everyone's thinking a gap year. I think that gap year is the
• 1:38:27
  best thing that someone ever invented to have give you the
• 1:38:30
  time to, I don't know, work some jobs to know how hard it is and
• 1:38:36
  then maybe figure out what you like.
• 1:38:38
  And even if you, if you don't figure out what you like to
• 1:38:40
  figure out what you don't like, then.
• 1:38:43
  Just give your brain another year, like at that age that's a
• 1:38:46
  big deal. Yeah, as far as I heard, it
• 1:38:50
  takes until 25 to completely develop the centre of the
• 1:38:53
  frontal cortex. So that's quite a lot.
• 1:38:58
  Yeah, but fully, fully with you. I I loved it.
• 1:39:01
  What's the what's the best dishes and you've ever made?
• 1:39:04
  No, not ever made. Sorry you've made recently.
• 1:39:08
  Best dish? Best decision you've made
• 1:39:11
  recently? I mean, I'm so happy I started
• 1:39:19
  remake the rules like big risk and so far like medium reward,
• 1:39:27
  which is exactly right, you know?
• 1:39:29
  Yeah, it's been great. Nice, nice.
• 1:39:32
  Yeah. It's always, always the same
• 1:39:34
  thing. Lower, lower the expectation
• 1:39:36
  then you are. Be all you are.
• 1:39:37
  Always happy. Always, always.
• 1:39:38
  Yeah, I, I get to like, I am the fisherman and it is great.
• 1:39:43
  Yeah, Yeah. I love it, I love it.
• 1:39:47
  I want I identify my boat. What's What's one tech trend you
• 1:39:56
  love but still question a? Tech trend.
• 1:40:04
  I love but still question all of them.
• 1:40:07
  All of them, yeah. I'm trying to think of one that
• 1:40:17
  I love. I think I, I think I maintain a
• 1:40:23
  pretty healthy skepticism across the board.
• 1:40:27
  But that skepticism does does come with the the power of
• 1:40:34
  positive potential. Yeah.
• 1:40:39
  Yeah. Not not a very satisfying
• 1:40:41
  answer. That's what I got though.
• 1:40:45
  I did expect something like don't I don't know what, a dance
• 1:40:48
  trend or something. I mean always like what am IA
• 1:40:52
  monster give me more dog videos every day all day, right?
• 1:40:58
  Who never invented cat videos? I hate that person.
• 1:41:01
  I Yeah. I love the idea that a single
• 1:41:06
  person did that. Some artistic genius came up
• 1:41:09
  with the idea of the cat video. I mean, it's always the
• 1:41:12
  question, what was there first, the egg or the chicken?
• 1:41:16
  But it had it had it was for sure one video that's one made
• 1:41:21
  with the cat and the other thought that could be
• 1:41:25
  interesting. Cultural phenomenon.
• 1:41:32
  I like to have scenarios in my head running because this is how
• 1:41:35
  I keep myself busy. I love the quote from from
• 1:41:38
  Sheldon Cooper. You do you know Big Bang Theory?
• 1:41:43
  I'm familiar with it, I haven't watched much but.
• 1:41:45
  Sheldon Cooper is saying no. I love to spend time with
• 1:41:48
  myself. I never get bored.
• 1:41:53
  What's what's something your personal is still trying to
• 1:41:57
  remake? I think, I mean, I think it is a
• 1:42:11
  lifelong process of figuring out who you are.
• 1:42:19
  First of all, we humans are very sneaky creatures and it is
• 1:42:25
  amazing what you cannot know about a person, including
• 1:42:29
  yourself. And and then as part of that,
• 1:42:36
  you know, understanding more the forces that are sort of acting
• 1:42:40
  upon me and, and creating me in ways that maybe I don't
• 1:42:45
  appreciate and, and trying to minimize those in my life too.
• 1:42:49
  That was a that was a that was a big one.
• 1:42:53
  That was that was that was a really good one.
• 1:42:55
  That's and that's I think the hard part for everyone, but the
• 1:43:02
  fact that you accept the, the, the fact that you accept the
• 1:43:05
  fact that they're those forces out there, I think that's the
• 1:43:07
  most important step. Yeah, just acknowledging it and
• 1:43:12
  then and then you'll be wedding them out for the rest of your
• 1:43:14
  life, hopefully. Any final advice for for someone
• 1:43:22
  who's feeling overwhelmed or stuck?
• 1:43:27
  Yeah. I think the most important thing
• 1:43:30
  to remember is that all of these choice tech tools, this
• 1:43:36
  information, this information technology tools, they are just
• 1:43:41
  that. They are just tools.
• 1:43:43
  They are not a life, They are not your life.
• 1:43:47
  And they are everywhere and they do have potential, but they
• 1:43:53
  don't have to be anything. And that what is most important
• 1:43:58
  is who you want to be and how you want to live and what
• 1:44:02
  relationship you want to have with these tools, not the other
• 1:44:05
  way around. And it's OK, it's OK not to be
• 1:44:10
  able to handle them on their own.
• 1:44:12
  And if you need help to handle those, Emily, where people can
• 1:44:15
  find you, I. Need a message
• 1:44:19
  folkscanfindmeemilypabst@remaketherules.com my website and then at remake
• 1:44:25
  the rules on many social platforms too.
• 1:44:28
  I will link all the social links in the show notes captions
• 1:44:31
  anyhow on YouTube and Spotify. Emily I, I, I cannot thank you
• 1:44:37
  enough for this nice conversation.
• 1:44:40
  It was a pleasure to get to know you.
• 1:44:42
  It was a lot of fun. Thank you for your time.
• 1:44:46
  Thank you so much. I had a great time.
• 1:44:47
  Had a great time. The same for me and looking
• 1:44:50
  forward to the elections episode.
• 1:44:52
  I still hold on to that. All right, we're going to get
• 1:44:55
  into it. Thanks every.
• 1:44:57
  See you next time. Thank you.
• 1:44:59
  Thank you. Bye.