Latest / 6 Ps in AI Pods (AI6P) / 🗣️ AISW #123: Jenn McRae, Canada-based writer and strategist

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🗣️ AISW #123: Jenn McRae, Canada-based writer and strategist · 6 Ps in AI Pods (AI6P)

0:00
SPEAKER_00: Hi everyone.
0:00
SPEAKER_00: This is Karen Smiley.
0:02
SPEAKER_00: Welcome to 6P's in AI Pods.
0:07
SPEAKER_00: This post is part of our AI 6P interview series on AI software and wetware.
0:13
SPEAKER_00: Our guests share their experiences with using AI and how they feel
0:17
SPEAKER_01: about AI using their data and content.
0:21
SPEAKER_00: I'm delighted to welcome Jennifer McRae from Canada as my guest today on AI software
0:26
SPEAKER_00: and wetware.
0:27
SPEAKER_00: Jen, thank you so much for joining me on this interview.
0:29
SPEAKER_00: Please tell us about yourself, who you are, and what you do.
0:32
SPEAKER_01: Yeah, Karen, thank you so much for having me.
0:34
SPEAKER_01: I've really admired your work since we connected, so it's really cool to be doing this.
0:39
SPEAKER_01: Thank you very much.
0:41
SPEAKER_01: So yeah,
0:42
SPEAKER_01: I'm a writer and independent strategist,
0:45
SPEAKER_01: and I've spent the last 20 years working at the intersection of the future of work
0:49
SPEAKER_01: and learning, broadly speaking.
0:51
SPEAKER_01: I publish a subset called Fuck I Love You' and we'll call it Philly
0:56
SPEAKER_01: from this point forward in the interview.
0:58
SPEAKER_01: On that subject I write broadly speaking about cultural transformation or
1:02
SPEAKER_01: as I often talk about it is radical imaginations for futures worth living in
1:08
SPEAKER_01: and I'm very convinced by Terence McKenna's idea
1:12
SPEAKER_01: that culture is your operating system and so my thesis or
1:16
SPEAKER_01: the base assumption underneath of Philly and all of the work that I do in general is
1:21
SPEAKER_01: that we're living in this time of very significant transformation.
1:24
SPEAKER_01: And what I've seen in all of my foresight work over,
1:28
SPEAKER_01: we're going
1:29
SPEAKER_01: on 20 years now is I see this attempting emergent relational cultural operating
1:35
SPEAKER_01: system.
1:35
SPEAKER_01: And so I say we're moving from a transactional operating system to a relational one.
1:40
SPEAKER_01: I've more recently simplified this or talk about this as we're upgrading
1:44
SPEAKER_01: the operating system from the old good life to the new good life.
1:48
SPEAKER_01: And I really see that new good life, it has a relational foundation and I see love as reality.
1:56
SPEAKER_01: It's not a feeling, it's a thing that you do.
1:59
SPEAKER_01: And it's really the core of everything.
2:02
SPEAKER_01: And so I think about that a lot.
2:03
SPEAKER_01: I write about that a lot.
2:04
SPEAKER_01: And to me, AI has a lot to do with that.
2:07
SPEAKER_01: And so you'll find very strong AI themes on my Substack and as well
2:11
SPEAKER_01: as neurodivergence,
2:12
SPEAKER_01: partially because it's my lived experience,
2:14
SPEAKER_01: but partially because I think the old good life if you will to really try
2:18
SPEAKER_01: to force us down this track of a cognitive monoculture there's one right way
2:22
SPEAKER_01: of doing of thinking of being and I think what's emerging in relationality is
2:28
SPEAKER_01: a cognitive polyculture and I think it's really important to talk
2:32
SPEAKER_01: about cognitive diversity because all humans have cognition and it's relational
2:36
SPEAKER_01: about the way that your brain and neurobiology interacts with culture
2:40
SPEAKER_01: and environment.
2:41
SPEAKER_01: And I think that that's a very inclusive way to think about it.
2:44
SPEAKER_01: We have so much to be gained from thinking about cognitive diversity.
2:47
SPEAKER_01: And I've written some pieces exploring the relationship between AI and cognitive diversity.
2:54
SPEAKER_01: I think there's some really interesting similarities I see between my own brain and
2:57
SPEAKER_00: the way that AI works.
2:59
SPEAKER_01: And I've also read a lot about AI as a cognitive prosthetic.
3:04
SPEAKER_01: To reduce what I and sometimes others call the translation pack.
3:08
SPEAKER_01: My experience is that it allows a brain like mine that's really can't help itself,
3:12
SPEAKER_01: but go toward complexity and patterns and deep dives and systemic insights.
3:17
SPEAKER_01: That's not very compatible with transactional quick.
3:20
SPEAKER_01: Give me the insight.
3:21
SPEAKER_01: Give me the deck.
3:22
SPEAKER_00: Give me five talking points.
3:24
SPEAKER_00: AI is really supportive.
3:25
SPEAKER_01: I find in reducing those transactional barriers and transactionality is still
3:32
SPEAKER_01: The dominant paradigm, it's still very economically deterministic.
3:35
SPEAKER_01: I think that's a really interesting thing to explore.
3:38
SPEAKER_01: To wrap up,
3:39
SPEAKER_01: I'd say speaking of
3:40
SPEAKER_00: economic imperatives,
3:42
SPEAKER_00: I do have a strategy practice, a consulting practice.
3:44
SPEAKER_01: I'm returning to it after a very long medical leave, so it's restarting slowly.
3:48
SPEAKER_01: I do offer insights into that practice.
3:52
SPEAKER_01: I have a section on my subset called Futures Worth Living In.
3:56
SPEAKER_01: And that's my more applied work, I'd say.
3:58
SPEAKER_01: If I was a speaking consultant,
4:00
SPEAKER_01: I would say that I support leaders and organizations
4:03
SPEAKER_01: to navigate these structural shifts that we're experiencing in work,
4:07
SPEAKER_01: learning, and economic participation.
4:09
SPEAKER_01: And the last thing I'm up to right now is my business partner, Anna,
4:13
SPEAKER_01: and I are working on a deep work retreat where we're trying
4:17
SPEAKER_01: to translate all these ideas about relationality and cognitive diversity to think
4:24
SPEAKER_01: about our environment as an intervention into our state.
4:28
SPEAKER_01: And we feel really strongly that our state determines our outcomes.
4:32
SPEAKER_01: So how can we offer an environment that helps people shift into ideally flow
4:37
SPEAKER_01: and have protected time to do the really important,
4:41
SPEAKER_01: creative,
4:41
SPEAKER_01: strategic,
4:42
SPEAKER_01: deep work that's really hard to get to
4:44
SPEAKER_00: when you're interrupted something like 275 times a day Microsoft found last year.
4:50
SPEAKER_01: We really want to explore environment as an intervention and that's going
4:53
SPEAKER_01: to be offered this fall.
4:55
SPEAKER_01: There's a website you can check out if you're interested.
4:58
SPEAKER_00: That sounds like a really interesting workshop.
5:00
SPEAKER_00: I had to chuckle when you mentioned the number of interruptions because that tracks.
5:05
SPEAKER_00: When I was working in corporate life, especially, I remember that.
5:08
SPEAKER_01: Yeah.
5:09
SPEAKER_01: Yeah.
5:09
SPEAKER_01: Microsoft, it's fascinating.
5:11
SPEAKER_01: I wrote a piece that they put out a report where they actually documented that
5:15
SPEAKER_01: because they can go in and look at all the data from Microsoft 365 and teams,
5:19
SPEAKER_00: they actually analyzed and found that
5:21
SPEAKER_00: the average
5:22
SPEAKER_01: knowledge worker is experiencing 205 interruptions a day.
5:26
SPEAKER_01: The cognitive load of that is shocking.
5:29
SPEAKER_01: So yeah, none of us are really working.
5:31
SPEAKER_01: We're just routing information.
5:34
SPEAKER_00: Yeah.
5:34
SPEAKER_00: In computer terms,
5:35
SPEAKER_00: we used to call that thrashing when you could go back and forth
5:37
SPEAKER_00: and never get anything actually done.
5:39
SPEAKER_00: I do remember seeing studies a long time ago that whenever there's one interruption,
5:44
SPEAKER_00: especially in software, you've got the mental model.
5:47
SPEAKER_00: Of the code that you're working on.
5:49
SPEAKER_00: And someone pops in with a question and it breaks your mental model and you've got
5:52
SPEAKER_00: to start rebuilding it all over again.
5:54
SPEAKER_00: And interruptions would cost people 15 to 30 minutes each time.
5:59
SPEAKER_01: So then how do you ever get anything done?
6:01
SPEAKER_01: It's amazing.
6:03
SPEAKER_01: I love that.
6:04
SPEAKER_01: That's a really great frame to think about it that way.
6:06
SPEAKER_01: And there's also a documented evidence-based thing now.
6:11
SPEAKER_01: 15 to 30 minutes is totally accurate.
6:12
SPEAKER_01: Yeah.
6:13
SPEAKER_01: Your lived experience checks out, Karen.
6:15
SPEAKER_00: Yeah, I think that study may have been from Microsoft too back in the day.
6:20
SPEAKER_00: It's quite some years ago.
6:21
SPEAKER_00: I'll see if I can dig it up because now I'm curious about whether or not it's held up.
6:26
SPEAKER_00: I can't imagine that it wouldn't have.
6:29
SPEAKER_00: I don't think it's gotten any better.
6:31
SPEAKER_00: Yeah, no, not with Slack and all these other teams and everything else.
6:36
SPEAKER_00: Yeah, very, very, very true.
6:38
SPEAKER_00: So you mentioned that you do write a bit about AI.
6:40
SPEAKER_00: Could you tell us about your level of experience with AI and machine learning
6:45
SPEAKER_00: and analytics,
6:46
SPEAKER_00: whether you've used it professionally or personally,
6:49
SPEAKER_00: or if you've ever studied any of the technologies.
6:53
SPEAKER_01: Yeah, I would call myself a passionate amateur.
6:55
SPEAKER_01: I am a non-technical user.
6:59
SPEAKER_01: I really came at AI first totally curiosity-driven.
7:02
SPEAKER_01: I was like, what is this thing that everybody's talking about?
7:04
SPEAKER_01: Why are we making Shakespeare sound like Snoop Dogg?
7:07
SPEAKER_01: What's going on when we're here?
7:09
SPEAKER_01: And I've just always loved technology and loved to experiment,
7:12
SPEAKER_01: and so I just OpenChat GPT and started chatting.
7:16
SPEAKER_01: At the time I was working on a foresight study for one of my consulting clients and
7:21
SPEAKER_01: through all that research and just my direct experience with the tools,
7:24
SPEAKER_01: I was like,
7:25
SPEAKER_01: there's no way around the conclusion that AI will be as or more transformative than
7:31
SPEAKER_01: the internet and this was I
7:32
SPEAKER_00: think mid 2024 or something.
7:35
SPEAKER_01: I've since published that study on my Substack.
7:37
SPEAKER_01: I retained rights to it.
7:38
SPEAKER_01: It's called Pathways to Prosperity.
7:39
SPEAKER_01: Like I said that was in 2024 and since then I've learned as much as I can
7:43
SPEAKER_01: about AI personally and professionally.
7:46
SPEAKER_01: I try to learn about the technical aspects so that I can be a more effective user.
7:52
SPEAKER_01: I've found that As a non-technical user,
7:55
SPEAKER_01: I found that my love of language and proficiency
7:59
SPEAKER_01: with language has been really useful in working with a large language model.
8:04
SPEAKER_01: I often find the more precise I can be with my words, the better the results that I get.
8:09
SPEAKER_01: And I've used it for everything from,
8:12
SPEAKER_01: yes, client analysis, research, different forms of editing and writing support.
8:17
SPEAKER_01: But I also engage quite a bit in the social
8:19
SPEAKER_01: and philosophical discourse around its development because I think AI is
8:24
SPEAKER_01: the primary accelerant in this transformation that my work documents and
8:29
SPEAKER_01: that I think about.
8:30
SPEAKER_01: It's really more than hit the gas pedal on where we're going, I think.
8:34
SPEAKER_00: So yeah, it's very important.
8:37
SPEAKER_00: Yeah.
8:37
SPEAKER_00: Thanks for sharing that.
8:38
SPEAKER_00: We'll get a link to your Pathways to Prosperity article into the article
8:43
SPEAKER_00: so people can find it more easily.
8:44
SPEAKER_00: Can you share a specific story with us about when you've used a tool that has AI
8:50
SPEAKER_00: or machine learning features?
8:50
SPEAKER_00: I'd like to hear about how the AI features worked for you
8:54
SPEAKER_00: or didn't basically what went well and what didn't go so well?
8:58
SPEAKER_01: Yeah.
8:59
SPEAKER_01: So being self-taught, I basically mess around and find out as much as I can.
9:03
SPEAKER_01: I don't have necessarily a specific story, but just a smattering of things.
9:08
SPEAKER_01: I've produced podcasts with Notebook LM.
9:11
SPEAKER_01: Like I said, I've collected and analyzed data.
9:14
SPEAKER_01: I've built a web scraper app with Quad.
9:17
SPEAKER_01: Gemini taught me how to build a second brain in Notion.
9:20
SPEAKER_01: Built numerous microsites.
9:22
SPEAKER_01: The DeepEnd retreat site, Claude and I built together.
9:25
SPEAKER_01: I've never built a website in my life.
9:27
SPEAKER_01: I have no idea, but I love the learning process.
9:29
SPEAKER_01: I love asking the models to teach me how to do things and be involved in the production.
9:35
SPEAKER_01: With the DeepEnd site specifically,
9:38
SPEAKER_01: Claude taught me how to deploy through Cloudflare pages and create Domain emails
9:44
SPEAKER_01: through essentially routing and masking and at Gmail address and all
9:48
SPEAKER_01: of these different things that I would never be able to do by myself,
9:53
SPEAKER_01: but now can do through
9:55
SPEAKER_00: curiosity and exploration.
9:56
SPEAKER_01: And I think when it goes right, it almost feels like magic.
10:00
SPEAKER_01: And I have lots of those stories.
10:03
SPEAKER_01: And I think that, yeah,
10:04
SPEAKER_01: the value is in this cognitive prosthetic function,
10:08
SPEAKER_01: reducing the translation tax,
10:10
SPEAKER_01: helping me do these things that I wouldn't have been able to do before.
10:14
SPEAKER_01: There's so much that's positive in that but then there's also it almost does create
10:18
SPEAKER_01: an extra layer of work because especially
10:20
SPEAKER_01: if I'm using it professionally I really have to trust what I'm putting out and
10:23
SPEAKER_01: so there's all of this verification work that has to be done on top of it.
10:28
SPEAKER_01: When I think about say things that have gone wrong to the second half
10:33
SPEAKER_01: of your question I told you I moved recently and I needed a floor planner app
10:38
SPEAKER_01: and I run out of freebies on the available tools online.
10:42
SPEAKER_00: So I was like, can we build a floor planner app?
10:45
SPEAKER_01: And I was like, absolutely, we can do that, you know?
10:48
SPEAKER_01: And it just confidently marched me down this direction.
10:50
SPEAKER_01: And two, three hours later, we still didn't have an app, wasn't actually working.
10:55
SPEAKER_01: And finally, I said, can you actually do this?
10:58
SPEAKER_01: Do you have the capability to do this?
10:59
SPEAKER_01: It was like, actually, no, I don't.
11:01
SPEAKER_01: So that's a silly version of the story,
11:05
SPEAKER_01: but I think there's lots and lots of stories people could tell about that where
11:08
SPEAKER_01: a model has confidently marched them down a particular path.
11:12
SPEAKER_01: And for my particular cognition,
11:15
SPEAKER_01: it's really easy for me to slip into rabbit holes and I'm really stubborn.
11:18
SPEAKER_01: I don't tend to just give up when it seems like something's not working.
11:21
SPEAKER_01: I'm like, oh, I must be doing something wrong.
11:23
SPEAKER_01: I must not have the technical knowledge to direct this process properly.
11:27
SPEAKER_01: So I'll get really stubborn too, and I'll keep trying.
11:29
SPEAKER_01: The model's never going to give up if you keep pushing.
11:32
SPEAKER_01: And so I find that one of the biggest risks or things
11:36
SPEAKER_01: that have gone wrong is essentially wasting time.
11:41
SPEAKER_01: The last thing that came up when I thought about your question was just around,
11:45
SPEAKER_01: it's a completely different track of thinking,
11:49
SPEAKER_01: but there's this purity politics that I find that's coming up right now around AI.
11:53
SPEAKER_01: I've written a couple pieces about it on my Substack,
11:56
SPEAKER_01: and I think there's so much nuance,
11:59
SPEAKER_01: I don't want to bury us in this conversation,
12:00
SPEAKER_01: I'll just bring it up and leave it,
12:02
SPEAKER_01: but I think we really need to be thinking hard about Why are we reacting
12:09
SPEAKER_01: to these tools like this?
12:10
SPEAKER_01: And there's almost a persecution that's starting to happen when people find out
12:15
SPEAKER_01: that you've used AI in your writing.
12:17
SPEAKER_01: People won't read you if you've used AI in your writing without any interrogation
12:24
SPEAKER_01: to why you use AI and how you use it and what your ethics are about it.
12:30
SPEAKER_01: AI's really become subject to this very black and white sort of politicized thinking
12:36
SPEAKER_01: that we've fallen into in a lot of domains.
12:39
SPEAKER_01: I understand it on the one hand and think it's really scary and problematic on the other.
12:44
SPEAKER_01: I think you restacked recently a piece I read, Karen,
12:47
SPEAKER_01: we both read it about the researchers at UVic that did the meta-relationality lab
12:52
SPEAKER_01: where they created the social cartographies, is that what they called them?
12:56
SPEAKER_01: And they identified these sort of three perspectives on AI,
13:00
SPEAKER_01: the blindly anti,
13:02
SPEAKER_01: the blindly pro, and the nuance, the people who live in the gray and the nuance.
13:07
SPEAKER_01: I thought it was a really helpful classification
13:08
SPEAKER_01: of what these emerging purity politics are about.
13:12
SPEAKER_00: Yeah.
13:13
SPEAKER_00: Her article was talking about the AI cheerleaders and then the AI,
13:16
SPEAKER_00: I don't know if she used the word doomers, but that's kind of what it was.
13:19
SPEAKER_00: And then the people in the middle that are trying to kind of balance saying,
13:23
SPEAKER_00: yeah, AI has got some problems.
13:24
SPEAKER_00: It also has some benefits that we need to find a way to gain the benefits
13:30
SPEAKER_00: and not completely ignore the harms either.
13:34
SPEAKER_00: And I think you and I both walked that middle line.
13:36
SPEAKER_00: I got one interesting reaction to that, like, oh, well, this is still a very negative view.
13:40
SPEAKER_00: Okay.
13:41
SPEAKER_00: But the intent is to be balanced, not to be very binary, not one or zero.
13:48
SPEAKER_01: Can I ask you,
13:49
SPEAKER_01: how do you feel about that emerging purity pulse that you experience that you're
13:54
SPEAKER_01: so deep in the space?
13:55
SPEAKER_01: Obviously,
13:56
SPEAKER_01: you've created SheWrites AI,
13:57
SPEAKER_01: you brought together,
13:58
SPEAKER_01: what are we at, like almost 700 of us now, you're publishing books.
14:01
SPEAKER_01: You could potentially have a very large target on your back,
14:04
SPEAKER_01: so to speak, for people who feel super strongly about this.
14:07
SPEAKER_01: Is there anything you're experiencing around this?
14:11
SPEAKER_00: Not from She Writes AI because it's about women who write about AI.
14:15
SPEAKER_00: It's not necessarily women who use AI.
14:17
SPEAKER_00: So there are some who are avid users and some who are very much focused on
14:24
SPEAKER_00: the ethics and here's why I don't use it and here's what we need to be doing
14:28
SPEAKER_00: to make it less biased, safer, more private than everything else.
14:33
SPEAKER_00: So in our community,
14:35
SPEAKER_00: we have the whole spectrum of uses and try to set it up from the beginning so
14:40
SPEAKER_00: that we can have respectful discussions.
14:42
SPEAKER_00: We don't get into disrespect or name calling or anything like that in the subscriber chat.
14:47
SPEAKER_00: That will get you booted.
14:50
SPEAKER_00: It's okay to disagree, but not to be disagreeable about it.
14:54
SPEAKER_00: I did have one question come up when we published our first book,
14:58
SPEAKER_00: our AI Everywhere Volume 1,
15:00
SPEAKER_00: and someone posted a comment to the effect of, I hope this is an anti-AI book.
15:07
SPEAKER_00: No, it's not.
15:08
SPEAKER_00: It's not anti-AI.
15:09
SPEAKER_00: It's also not rabidly pro-AI.
15:12
SPEAKER_00: The book had 20 chapters from 26 authors from 14 countries, and we had a wide range of views.
15:22
SPEAKER_00: And that was the point because that's reality.
15:25
SPEAKER_00: AI is everywhere and in our world,
15:27
SPEAKER_00: in our daily life,
15:29
SPEAKER_00: but people can and should explore for themselves what it means to use it ethically.
15:37
SPEAKER_00: What does that mean to them?
15:38
SPEAKER_00: What are their values?
15:39
SPEAKER_00: What trade-offs are in their lives that aren't in somebody else's?
15:42
SPEAKER_00: And how does that affect what they decide?
15:44
SPEAKER_00: And it doesn't make anybody wrong.
15:46
SPEAKER_00: My personal point of view is that everyone needs to define what your values are.
15:53
SPEAKER_00: Here's what I use AI for based on that.
15:55
SPEAKER_00: Here's what I don't, and here's why.
15:57
SPEAKER_00: And some people publish that, and that's great.
16:01
SPEAKER_00: Some people It's just more of an internal exercise.
16:04
SPEAKER_00: They don't feel comfortable publishing because of the purity of politics
16:07
SPEAKER_00: that you're talking about.
16:08
SPEAKER_00: And that's okay too.
16:10
SPEAKER_00: But I'd like to see us get to a world where we're not judging other people.
16:14
SPEAKER_00: I did an extensive post about that last week,
16:17
SPEAKER_00: comparing using an LLM to wearing glasses, which you and I both do.
16:22
SPEAKER_00: And the bottom line there is that we shouldn't be judging people were shaming them
16:29
SPEAKER_00: for wearing glasses or for using LLMs because that's really not the point.
16:34
SPEAKER_00: I think a lot of the shaming comes from the idea that the tools are inherently unethical.
16:39
SPEAKER_00: And the major ones, frankly, were not developed ethically.
16:44
SPEAKER_00: But shaming people who use them doesn't solve anything.
16:50
SPEAKER_00: Let's go shame the companies.
16:51
SPEAKER_00: Let's get them to compensate the people whose works they scraped
16:56
SPEAKER_00: and are now making great profits from.
16:59
SPEAKER_00: But shaming the people solves nothing.
17:03
SPEAKER_01: Yeah.
17:04
SPEAKER_01: Oh, I'm excited to check that out.
17:05
SPEAKER_01: I'm glad I asked you that question because I hadn't seen that piece and it fits in
17:11
SPEAKER_01: the big umbrella of cognitive prosthetic, right?
17:14
SPEAKER_01: Glasses are a prosthetic.
17:15
SPEAKER_01: They help us to do something that our body can't do by itself.
17:20
SPEAKER_00: So I'm really, yeah, really excited to see your views on that.
17:24
SPEAKER_01: Yeah.
17:25
SPEAKER_00: And some people don't need glasses,
17:27
SPEAKER_00: but that doesn't mean that they should be shaming people who wear them.
17:32
SPEAKER_00: If I had been born with great eyesight and never had to wear glasses,
17:34
SPEAKER_00: that would be a privilege.
17:37
SPEAKER_00: Not everybody has those privileges.
17:40
SPEAKER_00: But yeah, the whole social reactions to the tools and how they use them, it's interesting.
17:46
SPEAKER_00: And if you think about in the US and maybe in Canada also,
17:51
SPEAKER_00: they have something similar where for disabilities,
17:56
SPEAKER_00: the AI tools can be an accommodation,
17:59
SPEAKER_00: help them offset those disabilities or to be able to function in a way
18:05
SPEAKER_00: that they couldn't otherwise.
18:07
SPEAKER_00: That places that say you may not use AI tools are discriminating against people.
18:14
SPEAKER_00: It's ableist really.
18:16
SPEAKER_00: And I think there's some merit to that view,
18:18
SPEAKER_00: although companies obviously have the right to say,
18:21
SPEAKER_00: I don't want you putting our confidential information into that tool
18:25
SPEAKER_00: where it will get scraped and stolen and disseminated to our competitors.
18:30
SPEAKER_00: To say that people can't use the tools may be illegal, actually.
18:36
SPEAKER_01: Yeah, yeah, yeah.
18:38
SPEAKER_01: I wrote a whole section in my piece about the Canada Accessibility Act
18:41
SPEAKER_01: and how all those laws are going to end up interfacing with AI.
18:45
SPEAKER_01: And yeah, we're totally on the same page about that.
18:48
SPEAKER_01: And I actually think it's very underexplored in AI discourse.
18:52
SPEAKER_01: And I think workplaces are extremely blind to it.
18:55
SPEAKER_01: I think that it's going to be a very large and specific legal vulnerability for
19:02
SPEAKER_01: a lot of workplaces moving forward.
19:04
SPEAKER_01: And it intersects a lot with other issues that workplaces are struggling to deal
19:08
SPEAKER_01: with already around cognitive diversity and burnout and toxic culture
19:16
SPEAKER_01: and these types of things.
19:17
SPEAKER_01: And just because DEI was defunded and weaponized and so it's a very interesting subject.
19:25
SPEAKER_00: Yeah, very cool.
19:26
SPEAKER_00: So we talked a lot about using AI tools.
19:30
SPEAKER_00: Based on your own values and tradeoffs and such,
19:34
SPEAKER_00: are there any things that you specifically choose to avoid using AI tools for?
19:39
SPEAKER_00: If you have any examples of when and why you choose not to use AI for that one purpose?
19:46
SPEAKER_01: Yeah, I thought a lot about this and I couldn't come up with a very specific sort
19:53
SPEAKER_01: of use case in a singular way,
19:57
SPEAKER_01: but more generally,
19:59
SPEAKER_01: the one thing that I don't really ever allow myself to do,
20:03
SPEAKER_01: and it might be to my detriment, honestly, is put out purely generated content.
20:09
SPEAKER_01: So I won't go to a model and be like,
20:11
SPEAKER_01: write me a Substack about X, Y, Z, and then just post that.
20:16
SPEAKER_00: I did have one accident where that did happen.
20:19
SPEAKER_01: And as soon as I realized that a draft published,
20:21
SPEAKER_01: basically I'd put a draft in of a book LM report that I had intended to go back
20:26
SPEAKER_01: and use those source material.
20:28
SPEAKER_01: But I put the publication date in wrong on Substack and so it published
20:32
SPEAKER_01: and I didn't notice.
20:33
SPEAKER_01: And so anyway,
20:34
SPEAKER_01: I left it up and then I just put a note at the top of the piece and I just owned it.
20:37
SPEAKER_01: I was like, that's what's happened and decided not to take it down.
20:40
SPEAKER_01: But yeah,
20:41
SPEAKER_01: I think myself,
20:43
SPEAKER_01: a lot of writers,
20:44
SPEAKER_01: anyone who does any kind of online content creation,
20:47
SPEAKER_01: I think a lot of us feel a ton of pressure to be very consistent,
20:51
SPEAKER_01: to put out multiple either multiple pieces,
20:54
SPEAKER_01: but certainly various types of posts, notes, images, you name it, every single day.
21:00
SPEAKER_01: And that is not something I'm capable of, at least right now.
21:04
SPEAKER_01: I'm in this long process of recovering my capacity with my health,
21:08
SPEAKER_01: but number one, my capacity might not change.
21:11
SPEAKER_01: This might be it.
21:12
SPEAKER_01: And number two,
21:14
SPEAKER_01: my brain and constitution and cognition,
21:17
SPEAKER_01: it's really wired for these deep dives and these waves of production.
21:23
SPEAKER_01: Where I'm really focused on one thing for a while and then I'm moving to
21:26
SPEAKER_01: the next thing and that externally reads as inconsistency generally but especially
21:34
SPEAKER_01: to an algorithm and it's very punitive to try to create content and be inconsistent
21:38
SPEAKER_01: so it's very seductive to want to use models to keep me consistent and
21:43
SPEAKER_01: to keep me visible and for a mix of reasons my ethics just generally quality
21:51
SPEAKER_01: for better or worse I really am displeased with the word perfectionist,
21:56
SPEAKER_01: but I would say that I do hold myself to a very high standard
22:00
SPEAKER_01: and it doesn't mean it is excellent to everyone else.
22:03
SPEAKER_01: But for me, I don't feel like the models develop things that I would feel proud to put out.
22:08
SPEAKER_01: They don't feel like me.
22:09
SPEAKER_01: They don't sound like me.
22:10
SPEAKER_01: And so I get a ton of value through editing with Claude,
22:15
SPEAKER_01: through revisions, asking Claude to be my reader, getting feedback, implementing it.
22:20
SPEAKER_01: Like, oh my gosh, most of my pieces have been through 30, 40 plus revision cycles with a model.
22:28
SPEAKER_01: But I just remain very resistant
22:31
SPEAKER_00: to pure generation, I guess.
22:33
SPEAKER_00: I use analogies sometimes of an iceberg or a duck that is paddling furiously.
22:37
SPEAKER_00: You just see the duck gliding across the pond
22:39
SPEAKER_00: and you don't realize how hard it's working underneath the surface
22:42
SPEAKER_00: to propel itself forward.
22:43
SPEAKER_00: The iceberg is so much more below the waterline that people never see.
22:48
SPEAKER_00: And I think there are some people who say,
22:50
SPEAKER_00: write me an article about this,
22:53
SPEAKER_00: give me 500 words and cover these three points, and then they just publish it.
22:57
SPEAKER_00: But assuming that everybody who uses AI to assist in their writing is doing that is
23:02
SPEAKER_00: a disservice because there are people who,
23:05
SPEAKER_00: like you, go through 30 or 40 revisions where it's definitely being human-crafted.
23:11
SPEAKER_00: I've seen a lot of people write about using AI as a reviewer not as a writer
23:15
SPEAKER_00: but okay poke holes in this tell me where the thread of thought breaks down and
23:20
SPEAKER_00: then oh yeah you're right and then they'll fix that
23:22
SPEAKER_00: or yeah they don't what they're talking about this is fine but your human guidance
23:28
SPEAKER_00: and expertise is what comes through no definitely with things that you've written
23:32
SPEAKER_00: that I've read it's very very human in your thought process comes through
23:39
SPEAKER_00: and I would hope no one would actually be avoiding your writing because of that.
23:45
SPEAKER_00: Thank you.
23:46
SPEAKER_01: Yeah, I have had a few people,
23:48
SPEAKER_01: hasn't been tons,
23:49
SPEAKER_01: but I can think of five or six instances where I've had either unsubscribes
23:54
SPEAKER_01: or borderline vitriolic comments.
23:56
SPEAKER_01: And I think that is partially due to the changing culture on Substack and more sort
24:02
SPEAKER_01: of social media, Reddit-esque
24:04
SPEAKER_00: folks or maybe even bots coming into the ecosystem.
24:08
SPEAKER_01: One comment I got in particular was something about like, flop is an immediate block for me.
24:13
SPEAKER_01: And I'm like, number one, why bother leaving the comment?
24:15
SPEAKER_01: But number two, the thing that they commented on, I had actually written.
24:19
SPEAKER_01: What I find so interesting about that that leaves a few of our threads is,
24:24
SPEAKER_01: and I've seen at least a few people in our community write about this,
24:27
SPEAKER_01: is that there's very strong emerging evidence at least at
24:31
SPEAKER_01: the pattern anecdotal level that neurodivergent writing
24:34
SPEAKER_01: and AI writing are very similar.
24:38
SPEAKER_01: There's a whole piece around called Gestalt language processing that's very common
24:42
SPEAKER_01: in a lot of autistic cognition where we tend to treat words as like units
24:51
SPEAKER_01: of meaning very similar to how an LLM will treat tokens as units of meaning
24:57
SPEAKER_01: and There's also a lot of uses of em dashes and parentheticals and different things
25:02
SPEAKER_01: because our thoughts are flowing in these relational webs.
25:06
SPEAKER_01: They're not straight linear lines.
25:09
SPEAKER_01: And so I use AI a lot to help me get to those straight linear lines.
25:13
SPEAKER_01: But I also independently with or without AI, I'm going to be using AI.
25:20
SPEAKER_01: This lead scene of MDashes of conclusive evidence
25:23
SPEAKER_01: that you have used AI-generated writing is just actually increasingly a form
25:29
SPEAKER_01: of discrimination also.
25:30
SPEAKER_01: It's very interesting.
25:31
SPEAKER_01: I won't keep going on it,
25:33
SPEAKER_01: but I just think, yeah, there's a lot here to be thought about and unpacked.
25:37
SPEAKER_01: The last thing I'll say is I'm not sure if she's joined our community here
25:42
SPEAKER_01: where she writes AI or not, but there was a piece that was going around.
25:46
SPEAKER_01: I think you also read it.
25:48
SPEAKER_01: Her name is escaping me.
25:49
SPEAKER_01: But one of her main points is that folks in positions of power,
25:54
SPEAKER_01: hierarchically and otherwise,
25:55
SPEAKER_01: they have access to all kinds of executive assistants and ghostwriters and all
26:02
SPEAKER_01: of these other forms of additional capacity that are just assumed.
26:08
SPEAKER_01: It's like if you're going to get published in a magazine or write a book
26:12
SPEAKER_01: or even send an internal corporate communication and you're the CEO
26:15
SPEAKER_01: or vice president or whatever, somebody else wrote that for you, for sure.
26:20
SPEAKER_01: Or if you wrote it, six other people gave you edits on it.
26:26
SPEAKER_01: Most people don't pay attention to how large the size of the independent contractor business.
26:32
SPEAKER_01: Like when you look at the breakdown of the size of businesses in Canada,
26:36
SPEAKER_01: a huge majority are zero employee firms.
26:41
SPEAKER_01: And so it's people like me,
26:42
SPEAKER_01: people like you that are just,
26:44
SPEAKER_01: we're trying to do every single function of the business as well as work in
26:50
SPEAKER_01: the business.
26:51
SPEAKER_01: And we deserve to have access to tools that can provide us the kind of resources
26:57
SPEAKER_01: and support and capacity that is just a given,
27:01
SPEAKER_01: a neutral expected given that others have access to.
27:05
SPEAKER_01: And so I think that's also an important part of the consideration around that stuff.
27:10
SPEAKER_00: Yeah, the ghostwriting aspect is I think an interesting one or having the assistance
27:15
SPEAKER_00: and having people write things for you.
27:20
SPEAKER_00: Like you said,
27:20
SPEAKER_00: it's a form of assistance that most solopreneurs simply don't have
27:25
SPEAKER_00: and AI is providing that capability for them.
27:31
SPEAKER_00: Yeah, it doesn't seem fair.
27:33
SPEAKER_00: Yeah.
27:35
SPEAKER_00: Thanks for sharing all those thoughts.
27:37
SPEAKER_00: So that's a good perspective on using AI and how you're using it.
27:41
SPEAKER_00: And I think that is important.
27:42
SPEAKER_00: I haven't,
27:44
SPEAKER_00: I think,
27:44
SPEAKER_00: noticed if you have anything on any of your articles saying,
27:47
SPEAKER_00: you know,
27:48
SPEAKER_00: I used AI and this is how I used it or why I use it,
27:50
SPEAKER_00: or if you have an AI policy on your newsletter.
27:55
SPEAKER_01: I don't.
27:56
SPEAKER_01: I've thought about it many times and I do think aspiratially and ethically,
28:00
SPEAKER_01: I think I need to do that.
28:01
SPEAKER_01: I just haven't done it yet.
28:03
SPEAKER_01: And I have had pieces where,
28:06
SPEAKER_01: like I did a series called Normal Zebras and it was all about these intersections
28:10
SPEAKER_01: of neurodivergence and AI.
28:12
SPEAKER_01: And I had a conversation with Gemini and one of them I did use Gemini initially
28:19
SPEAKER_01: to help me generate a few paragraphs that I then rewrote but used as
28:24
SPEAKER_01: a source material to get me going and I gave a disclaimer about all that so I do try
28:30
SPEAKER_01: to be transparent when it's very obvious but I think you would have
28:34
SPEAKER_01: to actually read my work to know that you know I think some writers are very good
28:39
SPEAKER_01: at it's top of line.
28:40
SPEAKER_01: They acknowledge it right away,
28:42
SPEAKER_01: or they have even a section header on their Substack site that was like AI policy,
28:49
SPEAKER_01: these types of things.
28:50
SPEAKER_01: I think there's a ton of value to that.
28:52
SPEAKER_00: So yeah, thank you for reminding me about that.
28:56
SPEAKER_00: You're welcome.
28:56
SPEAKER_00: It's something that I encourage when I wrote my Everyday Ethical AI book.
29:00
SPEAKER_00: It's something that I listed as one of my recommendations that even
29:03
SPEAKER_00: if you don't initially share it, just writing it down.
29:06
SPEAKER_00: Now, Daria Cuperiano,
29:08
SPEAKER_00: I don't know if you read her writing, she's got a lot of really good points.
29:11
SPEAKER_00: One that she made was this idea of having three buckets that you put your work into.
29:17
SPEAKER_00: Three zones, she called them, and one zone is the sacred zone.
29:21
SPEAKER_00: These are things where the humanness of it matters,
29:23
SPEAKER_00: and I will never ever do those with AI, like having a conversation like this.
29:28
SPEAKER_00: I wouldn't send our agents to have this conversation.
29:30
SPEAKER_00: We do it ourselves because that human interaction matters.
29:34
SPEAKER_00: And then there are the automation zone.
29:36
SPEAKER_00: This stuff is just tedious.
29:37
SPEAKER_00: It's boring.
29:38
SPEAKER_00: Just made it for me.
29:39
SPEAKER_00: It doesn't even have to be AI,
29:40
SPEAKER_00: but just these are things that the more I free myself up from that burden,
29:44
SPEAKER_00: the better.
29:45
SPEAKER_00: And then there's kind of an augmented zone in the middle,
29:47
SPEAKER_00: which is where I still want to retain control over this,
29:51
SPEAKER_00: but I will use AI assistance for this.
29:54
SPEAKER_00: And so just thinking about your daily tasks and which of the zones they fall in
29:59
SPEAKER_00: and why,
30:00
SPEAKER_00: and then figuring out from there,
30:01
SPEAKER_00: okay, these are things that I we'll use AI tools for this way or that way.
30:07
SPEAKER_00: It's a good way to think about understanding your own ideas.
30:12
SPEAKER_00: We all have an AI policy, whether it's written down or not.
30:16
SPEAKER_00: We have a way that we make decisions and we think about what we do and what I'm going to use.
30:22
SPEAKER_00: I'm not going to use this for that.
30:23
SPEAKER_00: And thinking it through and writing it down, I think can bring a lot of insight.
30:29
SPEAKER_01: Yeah, thank you.
30:30
SPEAKER_01: That's a great reminder.
30:31
SPEAKER_01: And thank you also specifically for pointing out Daria and your work as resources,
30:36
SPEAKER_01: because it's really helpful to have examples,
30:40
SPEAKER_01: best practices,
30:41
SPEAKER_01: things to look at as guidance,
30:42
SPEAKER_00: because it can seem daunting once you put it in the frame of
30:45
SPEAKER_01: AI policy,
30:46
SPEAKER_01: you know, but I really like how you just explained Daria's approaches.
30:49
SPEAKER_01: It sounds very humanistic, you know, it doesn't sound like it's very corporate policy.
30:54
SPEAKER_01: We have, you know, 0.1, 1.1 A.
30:57
SPEAKER_01: So yeah, that's cool.
30:59
SPEAKER_01: Thank you.
30:59
SPEAKER_01: I'm going to look at that.
31:01
SPEAKER_00: Yeah.
31:01
SPEAKER_00: Policy is like the idea of a process when I used to use when I was working in corporate.
31:05
SPEAKER_00: We all have a process for getting up in the morning,
31:07
SPEAKER_00: whether we go put on the coffee or we brush our teeth or let the dog out
31:11
SPEAKER_00: or whatever.
31:12
SPEAKER_00: We have steps that we go through in the morning and we don't think about it as
31:15
SPEAKER_00: a process or write it down as 1.2.3a,
31:19
SPEAKER_00: but we have one and sometimes it's helpful to write it down and think about,
31:25
SPEAKER_00: okay, well, this is what I currently do.
31:26
SPEAKER_00: What if I did it this way instead?
31:28
SPEAKER_00: So yeah, processes are like policies.
31:32
SPEAKER_00: We all have them.
31:33
SPEAKER_00: That is great.
31:34
SPEAKER_00: Processes are like policies.
31:36
SPEAKER_00: Karen.
31:37
SPEAKER_01: It's a good one.
31:37
SPEAKER_01: You give me a lot to think about.
31:38
SPEAKER_00: I want to get back to the questions about AI and your thoughts about it.
31:43
SPEAKER_00: So one concern we've talked a little bit about this is these AI tools,
31:48
SPEAKER_00: most of them are developed by scraping, pulling data from the internet.
31:54
SPEAKER_00: That's what they use for training.
31:56
SPEAKER_00: And then they turn that around and sell the access to the tool to us.
31:59
SPEAKER_00: But in a lot of cases, they have not gotten the consent.
32:05
SPEAKER_00: Of the people whose works they took or they haven't credited them
32:09
SPEAKER_00: or compensated them for the use of it.
32:11
SPEAKER_00: And there are some people that advocate what they call the three C's
32:15
SPEAKER_00: of creative rights, consent, credit, compensation.
32:18
SPEAKER_00: And many people say that this is something that all creative people should be entitled to.
32:24
SPEAKER_00: If someone takes your Substack newsletter and uses it for training a model
32:30
SPEAKER_00: that you should have some rights to it.
32:31
SPEAKER_00: And other people say it's okay for them to take whatever is publicly available.
32:35
SPEAKER_00: That's okay with me where they can take my work.
32:38
SPEAKER_00: That doesn't mean that they should have the right to take everybody's.
32:41
SPEAKER_00: There's a lot of opinions around that.
32:43
SPEAKER_00: I'm wondering what your thoughts are about companies that get people's data,
32:50
SPEAKER_00: get people's content and use it for training these models.
32:53
SPEAKER_01: Yeah, it's a complex topic.
32:55
SPEAKER_01: I could really go on about it, but please help me stay as tight as possible.
33:01
SPEAKER_01: It would have been the whole conversation and I'll just,
33:05
SPEAKER_01: if I can offer a disclaimer and just ask for a little bit of grace
33:09
SPEAKER_01: because there's no way to get something so complex right.
33:13
SPEAKER_01: There's going to be generalizations and exclusions and things.
33:16
SPEAKER_01: Generally speaking,
33:17
SPEAKER_01: my first and foundational position is We have to go a layer above AI and look at
33:22
SPEAKER_01: the systems that we're operating in.
33:24
SPEAKER_01: Broadly speaking, there is just no ethical participation under capitalism.
33:29
SPEAKER_01: That's not a license to not care and to excuse oneself from pursuing more ethical options.
33:37
SPEAKER_01: It doesn't mean that we can just condone this stealing.
33:41
SPEAKER_01: I do think that the AI companies stole this work and I do think that stealing is
33:47
SPEAKER_01: the right word because not all of it was in the public domain and
33:51
SPEAKER_01: the American government persecuted Aaron Schwartz 15 years ago.
33:55
SPEAKER_01: For doing what the AI companies did today.
33:57
SPEAKER_01: And Aaron, he's not with us anymore.
33:59
SPEAKER_01: The stress and pain of that experience, he decided to end his life.
34:03
SPEAKER_01: If that's a case people aren't familiar with, I really encourage you to get familiar with it.
34:06
SPEAKER_01: Aaron Schwartz is a magnificent human being and is very related to the complexity
34:12
SPEAKER_01: of access to information.
34:13
SPEAKER_01: He basically downloaded a massive amount of academic journals and
34:18
SPEAKER_01: then made them publicly freely available on the internet.
34:20
SPEAKER_00: What I thought Aaron was doing was very ethical.
34:24
SPEAKER_01: Because he was trying to make information freely available and he wasn't trying
34:27
SPEAKER_01: to profit off of it and he took a very deep personal risk in doing so.
34:32
SPEAKER_01: He was trying to do the opposite of the hoarding and privatization of information
34:38
SPEAKER_01: for profit,
34:40
SPEAKER_01: whereas now the AI companies are hoarding
34:44
SPEAKER_00: and privatizing information for profit.
34:47
SPEAKER_01: So I think about those things.
34:49
SPEAKER_01: There's a thousand examples.
34:50
SPEAKER_01: It's very difficult.
34:52
SPEAKER_01: There's almost nowhere in the supply chain of the production of goods and services,
34:59
SPEAKER_01: including mine and yours.
35:00
SPEAKER_01: You know, we're using laptops with mined minerals from the Congo that children probably mined.
35:08
SPEAKER_01: If you properly stop and think about the full chain and system
35:13
SPEAKER_01: of what we're participating in,
35:15
SPEAKER_01: we will always arrive at very unethical and problematic foundations.
35:22
SPEAKER_01: And so I really try to differentiate the technology versus the company versus the system.
35:29
SPEAKER_01: So when it comes to consent,
35:31
SPEAKER_01: credit and compensation,
35:33
SPEAKER_01: I don't know how we draw fair and ethical,
35:36
SPEAKER_01: let alone legal lines around what,
35:40
SPEAKER_01: how do we even do that now that it's already been done, you know?
35:44
SPEAKER_01: I also think about how we all stand on the shoulders of giants.
35:49
SPEAKER_01: Do you or I pay our mentors or do we offer financial compensation
35:58
SPEAKER_01: to every sec writer that we've read or every single person that's influenced us
36:04
SPEAKER_01: in our career?
36:05
SPEAKER_01: It's very difficult to do that.
36:08
SPEAKER_01: We don't do it.
36:11
SPEAKER_01: My mentors once told me all great writers are voracious readers.
36:16
SPEAKER_01: And I agree so strongly with that.
36:20
SPEAKER_01: And so am I supposed to then now track,
36:23
SPEAKER_01: make an inventory of every single writer who has influenced me and go and pay them?
36:29
SPEAKER_01: That's not what we're doing.
36:31
SPEAKER_01: And I think human brains, how do I want to say this?
36:37
SPEAKER_01: Let me say it this way.
36:39
SPEAKER_01: Two months ago,
36:40
SPEAKER_01: Sam Altman came under huge fire for comparing humans to AI and saying like, well,
36:45
SPEAKER_01: we spend all this money and land and resources training humans,
36:50
SPEAKER_01: feeding them, educating them.
36:53
SPEAKER_01: And everyone's
36:54
SPEAKER_00: like, well,
36:55
SPEAKER_00: it was quite disgusting in context to think that
36:59
SPEAKER_01: training AI is more important
37:01
SPEAKER_01: and more efficient than training a human.
37:03
SPEAKER_01: And if you take it out of that context as a sort of one-to-one analogy,
37:09
SPEAKER_01: like human brains absolutely are trained in a very similar way to an LLM in
37:15
SPEAKER_01: that we take in this huge corpus of information and then we sense make
37:22
SPEAKER_01: and we turn around and make a career out of it and benefit economically, etc.
37:28
SPEAKER_01: There was no consent, credit or compensation for any of that in quotations training, you know?
37:35
SPEAKER_01: Then there's also the issue that companies were already using our data.
37:40
SPEAKER_01: They've been using our data since companies have existed.
37:43
SPEAKER_01: That's what marketing is.
37:45
SPEAKER_01: Even before we had machine learning or AI or digitization of information and data,
37:51
SPEAKER_01: you could analyze behavior as data and manipulate it to sell things to people.
37:55
SPEAKER_01: There's this story that your question for some reason got me thinking about that
38:00
SPEAKER_01: the way that women started smoking cigarettes was
38:03
SPEAKER_01: because Sigmund Freud's nephew sat down and analyzed the behavioral marketplace
38:09
SPEAKER_01: and was like, hmm, women don't smoke because it's culturally unacceptable.
38:13
SPEAKER_01: And so how can we break those norms and get women to smoke?
38:19
SPEAKER_01: Like, ah, we'll associate it with emancipation.
38:22
SPEAKER_01: We will call cigarettes freedom torches.
38:24
SPEAKER_01: And that's a bunch of data that was collected and analyzed for companies to make a profit.
38:30
SPEAKER_01: We don't often stop to think the level of sort of saturation and the effects
38:36
SPEAKER_01: of these dominant systems they have on us.
38:39
SPEAKER_01: And so I guess what I'm trying to get at is I think the only just and ethical answer
38:45
SPEAKER_01: to this argument is that in the absence of systemic transformation,
38:50
SPEAKER_01: it has to economically,
38:53
SPEAKER_01: like directly in dollars and cents
38:54
SPEAKER_01: into our pockets benefit every single human alive now and in the future.
38:58
SPEAKER_01: There's no way to differentiate.
39:00
SPEAKER_01: Karensmiley,
39:02
SPEAKER_01: what compensation should you get for your contribution into the corpus of knowledge
39:07
SPEAKER_01: that trained AI?
39:09
SPEAKER_01: And I don't think that this should be a redistribution through governments.
39:14
SPEAKER_01: I think that's a whole other kettle of fish.
39:16
SPEAKER_01: I think governments and corporations are not all that different.
39:19
SPEAKER_00: So AI is forcing
39:22
SPEAKER_01: not just conversations, but actual structural transformations.
39:26
SPEAKER_01: And yes,
39:27
SPEAKER_01: we don't have a solution on the table yet
39:29
SPEAKER_01: about how We are directly compensating people for the existence of this technology,
39:35
SPEAKER_01: but there has to be one.
39:37
SPEAKER_01: I think there is a third way that needs to emerge between public and private
39:45
SPEAKER_01: that lots of smart people are thinking about.
39:47
SPEAKER_01: There's lots of possibilities for it.
39:50
SPEAKER_01: Should there be consenting compensation?
39:52
SPEAKER_01: Yes, but is it actually possible under these current systems?
39:59
SPEAKER_01: I don't see how,
40:01
SPEAKER_00: you know?
40:02
SPEAKER_00: Yeah.
40:03
SPEAKER_00: Yeah.
40:03
SPEAKER_00: That's fair enough.
40:05
SPEAKER_00: So as someone who uses these tools,
40:08
SPEAKER_00: do you feel like the providers of the tools that you use have been transparent
40:12
SPEAKER_00: with you about sharing where they got the data that they used?
40:15
SPEAKER_00: No.
40:16
SPEAKER_00: That's what I hear from most people.
40:18
SPEAKER_00: They don't feel that it's been transparent for them.
40:20
SPEAKER_00: So as someone who is not necessarily choosing whether or not to use an AI tool,
40:24
SPEAKER_00: but just as someone who is existing in society,
40:27
SPEAKER_00: as a consumer,
40:29
SPEAKER_00: as a member of the public,
40:31
SPEAKER_00: our personal data and content are probably being used by AI-based tools or systems.
40:37
SPEAKER_00: And I'm wondering what your thoughts are about that.
40:40
SPEAKER_01: Yeah.
40:42
SPEAKER_01: You and I did some pre-prep on these questions and I found
40:45
SPEAKER_01: that I only had these larger systemic perspectives on it.
40:49
SPEAKER_01: I guess that's where most of my attention goes on this stuff.
40:52
SPEAKER_01: I don't
40:52
SPEAKER_01: have a personal story specifically,
40:55
SPEAKER_01: but I have these very strong curiosities or even called a founded hunch
41:00
SPEAKER_01: about my data,
41:02
SPEAKER_01: your data,
41:02
SPEAKER_01: our data as citizens is constantly being used by AI tools and systems
41:07
SPEAKER_01: without our consent and under false pretenses and often in benign ways in a sense.
41:14
SPEAKER_01: The thing that came to mind when I was reflecting
41:17
SPEAKER_01: on this was there's been this pretty big controversy going on in Canada over
41:20
SPEAKER_01: the last couple of years as the public starts to become more aware
41:24
SPEAKER_01: of how much government and bureaucratic work is being outsourced
41:28
SPEAKER_01: to private professional services firms.
41:31
SPEAKER_01: In 2025,
41:31
SPEAKER_01: we spent $23 billion outsourcing what would have been internal government work
41:37
SPEAKER_01: to consulting firms.
41:39
SPEAKER_01: Deloitte,
41:40
SPEAKER_01: for example,
41:41
SPEAKER_01: I was looking this up yesterday,
41:42
SPEAKER_01: they appeared 39 times in our public accounts,
41:46
SPEAKER_01: meaning Deloitte had 39 separate engagements across the whole of Canada's government
41:51
SPEAKER_01: with all these different departments.
41:53
SPEAKER_01: And one of the departments is employment and social development.
41:56
SPEAKER_01: They had a $100 million contract with Deloitte for things like informatics services
42:01
SPEAKER_01: and scientific and research services and That's the department
42:05
SPEAKER_01: that administers employment insurance.
42:07
SPEAKER_01: I've been on employment insurance.
42:09
SPEAKER_01: What data is the government giving to Deloitte?
42:13
SPEAKER_01: No one really knows.
42:14
SPEAKER_01: Oversight is reactive.
42:15
SPEAKER_01: It's not proactive.
42:17
SPEAKER_01: And so we won't know until there's been some big leak or error or mistake that gets caught.
42:25
SPEAKER_01: Is Deloitte just reworking internal systems that have nothing to do
42:29
SPEAKER_01: with citizen data or are they directly engaging with citizen data?
42:35
SPEAKER_01: It's not just Deloitte.
42:36
SPEAKER_01: We have contracts with Palantir.
42:37
SPEAKER_01: We have huge contracts with Palantir.
42:40
SPEAKER_01: Canadian government, another big controversy.
42:43
SPEAKER_01: We spent 44 million bucks on Gotham this year.
42:46
SPEAKER_01: And then data sovereignty becomes a huge concern in that context because even
42:52
SPEAKER_01: though Palantir has a Canadian subsidiary,
42:54
SPEAKER_01: it's still subject to the US Cloud Act,
42:58
SPEAKER_01: meaning potentially at any point in time,
43:01
SPEAKER_01: the American government could compel access to our data.
43:04
SPEAKER_01: So now it's not just personal data potentially being accessed and used
43:09
SPEAKER_01: by AI companies and put into AI systems.
43:14
SPEAKER_01: It becomes a geopolitical issue.
43:17
SPEAKER_01: There's other things I could talk about.
43:19
SPEAKER_01: I'll pause there instead of continuing on,
43:21
SPEAKER_01: but I think not so much that I am aware of a specific instance where I know
43:26
SPEAKER_01: for sure my data was given over.
43:29
SPEAKER_01: I just think it's functionally impossible to participate in a digital society
43:34
SPEAKER_01: without our personal data being harvested and exploited.
43:37
SPEAKER_01: And I think AI just supercharges that process in a way that is discomforting
43:42
SPEAKER_01: when you think about democracy.
43:44
SPEAKER_01: Yeah.
43:46
SPEAKER_00: Yeah.
43:47
SPEAKER_00: And it's one thing if we have a choice about whether or not you use an AI tool
43:51
SPEAKER_00: for this or for that,
43:52
SPEAKER_00: but when it comes to something like government services or tax administration,
43:57
SPEAKER_00: We can't avoid it.
43:59
SPEAKER_00: We can't opt out of it.
44:00
SPEAKER_00: And so it's really extra important there that they behave ethically.
44:04
SPEAKER_00: Actually, one of our chapters in volume two was about tax administration.
44:07
SPEAKER_00: We have a writer in Argentina who works in that area
44:10
SPEAKER_00: and she has some great perspectives on that.
44:12
SPEAKER_00: But yeah, the government use of our data is really concerning for a lot of reasons.
44:18
SPEAKER_00: Do you know of any companies that you gave your data or content to
44:22
SPEAKER_00: that actually told you that they might use your information for training
44:27
SPEAKER_00: in AI systems?
44:28
SPEAKER_01: I mean, for sure, Substack, Anthropic.
44:33
SPEAKER_01: I admit that my,
44:35
SPEAKER_01: what should I call it,
44:35
SPEAKER_01: my AI hygiene is a work in progress and I do definitely fall into the seduction of
44:42
SPEAKER_01: the E's and especially with rebuilding my cognitive capacity over the last couple
44:47
SPEAKER_01: of years.
44:49
SPEAKER_01: I have absolutely given Claude bank statements to help me organize my financials
44:55
SPEAKER_01: or health data and so It's also interesting to stop and think about the times
45:00
SPEAKER_01: that I've just willingly given these systems my data,
45:04
SPEAKER_01: knowing that it could be used for training,
45:07
SPEAKER_01: but also not necessarily knowing how to stop that.
45:11
SPEAKER_01: The companies opt in as a default setting, and then opting out is opaque.
45:18
SPEAKER_01: How do you do that?
45:19
SPEAKER_01: In Substack,
45:20
SPEAKER_01: it's very deep in the settings I personally didn't find it easy to find
45:24
SPEAKER_01: and I only stumbled across it when I was setting up my publication for
45:28
SPEAKER_01: the very first time so yeah I think it's more just the overall practice of software
45:35
SPEAKER_01: as a service in general has become pretty predatory and pretty anti-user
45:40
SPEAKER_01: and these practices are not a mistake opting us into things because we signed
45:45
SPEAKER_01: a terms and conditions that we didn't read because it's in legalese and it's,
45:49
SPEAKER_01: you know,
45:49
SPEAKER_01: 10,000 words long and purposely obfuscates what they're actually trying to do.
45:56
SPEAKER_01: That's asymmetric power that is really problematic.
46:02
SPEAKER_01: And so do I know of any company that I gave my data or content to
46:06
SPEAKER_01: that made me aware they might use it for trading?
46:08
SPEAKER_01: Like all of them, you know, I just assumed.
46:12
SPEAKER_00: Yeah, Substack is interesting because the opt-out that we have in the newsletter,
46:16
SPEAKER_00: it's actually for whether or not they try to block third-party crawlers
46:22
SPEAKER_00: from getting your data.
46:23
SPEAKER_00: It's not, can they use our data?
46:26
SPEAKER_00: It's, do you want to block third-party bots, AI bots from accessing your data or not?
46:33
SPEAKER_00: And yeah, a lot of people don't notice that the setting is there.
46:35
SPEAKER_00: I've had a few people say they were surprised to find out about it when I asked them
46:39
SPEAKER_00: if they had it enabled on their newsletter.
46:41
SPEAKER_00: Yeah.
46:42
SPEAKER_00: So I'm curious, do you have it enabled on your newsletter or do you have it disabled?
46:47
SPEAKER_01: I am almost certain that I disabled it and I didn't go back and check,
46:51
SPEAKER_01: but I remember that it actually kind of stopped me and I sat at a computer
46:57
SPEAKER_01: and thought about it for a while.
46:58
SPEAKER_01: And at the time I was feeling a lot more optimistic about AI.
47:02
SPEAKER_01: Honestly, maybe even a little bit Pollyanna about the ethical side of it.
47:06
SPEAKER_01: And I remember thinking like, oh,
47:09
SPEAKER_01: I should make a contribution to developing this monumentally important technology.
47:14
SPEAKER_00: You know, who cares?
47:16
SPEAKER_00: The internet is scraped all the time, AI
47:17
SPEAKER_01: or no AI.
47:19
SPEAKER_01: What am I trying to prevent?
47:20
SPEAKER_01: Why not contribute to making this technology better?
47:25
SPEAKER_01: And I don't know that I would still stand by that position today.
47:30
SPEAKER_01: And I don't remember what I did with that toggle.
47:34
SPEAKER_00: And I'm just curious,
47:35
SPEAKER_00: but like you said, companies have been using and scraping our data for a long time.
47:40
SPEAKER_00: Do you know of any cases where a company's use
47:43
SPEAKER_00: of your data has created privacy issues,
47:45
SPEAKER_00: phishing, loss of income, junk mails, texts, anything like that?
47:50
SPEAKER_01: I get spam calls all the time because my phone number is listed in a lot
47:56
SPEAKER_01: of different places,
47:58
SPEAKER_01: but no, I can't really think of a really specific instance, honestly.
48:04
SPEAKER_01: Again, I just kind of assume that it's happening.
48:07
SPEAKER_00: Okay.
48:09
SPEAKER_00: Last question and then we can talk about anything else that you want.
48:12
SPEAKER_00: Thinking about these AI and tech companies and whether or not we can trust them with our data.
48:20
SPEAKER_00: Some people say that trust is impossible and unrealistic.
48:24
SPEAKER_00: Other people say that there are cases under
48:26
SPEAKER_00: which they could feel like they could trust a company.
48:30
SPEAKER_00: And I'm wondering what your thoughts are on that.
48:33
SPEAKER_01: I think I go back to that much longer answer I gave about there's no ethical participation.
48:38
SPEAKER_01: And because of that,
48:38
SPEAKER_01: I think that sows immediate distrust just from the incentive structure
48:43
SPEAKER_01: that these companies are operating under.
48:45
SPEAKER_01: Tristan Harris has really excellent analysis and commentary.
48:49
SPEAKER_01: He makes very accessible this idea of what are the impacts of incentives
48:55
SPEAKER_01: and how incentives are the whole game.
48:59
SPEAKER_01: As long as companies are incentivized toward profit and the investment model
49:04
SPEAKER_01: and this type of thing,
49:05
SPEAKER_01: we'll continue to see actions that betray trust if
49:09
SPEAKER_01: the choice point is do something ethical and trustworthy or do something
49:15
SPEAKER_01: that will make the product more profitable you know
49:19
SPEAKER_01: and we've watched our trust get betrayed so it's so routine
49:26
SPEAKER_01: that I think people we've lost our sense of agency to do anything
49:31
SPEAKER_01: about it we've become quite defeated by how routine the betrayal of
49:35
SPEAKER_01: trust is so I don't really know I do admit that I feel trusting generally toward anthropic
49:44
SPEAKER_01: and I kind of feel like it's a similar feeling as you know if there's been a pattern
49:50
SPEAKER_01: of a type of relationship that has harmed me over and over again and I'm kind
49:53
SPEAKER_01: of like oh you know you remind me of the last person I dated and they really hurt me
49:58
SPEAKER_01: and I really want to believe in you you're really presenting as
50:01
SPEAKER_01: a trustworthy person You're giving me a lot of signals that I should trust you,
50:06
SPEAKER_01: but there's just this, oh, something that I don't know.
50:09
SPEAKER_01: I really, I think you'll probably disappoint me again, you know?
50:12
SPEAKER_01: So that's sort of how I feel about Anthropik.
50:14
SPEAKER_01: I'm like, oh, I really want to date you, but I don't think I should.
50:19
SPEAKER_00: It's probably a fair analogy.
50:21
SPEAKER_01: Yeah.
50:22
SPEAKER_00: Yeah.
50:23
SPEAKER_01: Yeah.
50:23
SPEAKER_01: And I don't think it's the people.
50:26
SPEAKER_01: I think the people in the company are really good.
50:28
SPEAKER_01: I think the structures they're working in are very untrustworthy and very unethical.
50:32
SPEAKER_01: I was really impressed by their decision,
50:36
SPEAKER_01: for example,
50:37
SPEAKER_01: to decline that government contract a while back that got them first into problems
50:42
SPEAKER_01: with administration and seeing all these different OpenAI employees
50:46
SPEAKER_01: and other really heavy hitting,
50:48
SPEAKER_01: highly regarded,
50:49
SPEAKER_01: talented engineers and really high level folks leave places like OpenAI and
50:55
SPEAKER_01: in their tweets and letters and whatnot,
50:58
SPEAKER_01: they will almost always mention ethics and principles and trustworthiness
51:06
SPEAKER_01: and these types of things.
51:07
SPEAKER_01: They'll do it sort of slyly,
51:09
SPEAKER_01: but if you read it word for word,
51:11
SPEAKER_01: you're like, oh,
51:12
SPEAKER_01: you basically just said you don't trust,
51:14
SPEAKER_01: open AI and the ethics of that organization.
51:17
SPEAKER_01: And so you're leaving for a more trustworthy ethical organization to go to Anthropic.
51:21
SPEAKER_00: And I don't know if I'm actually answering your question,
51:23
SPEAKER_00: Karen, do you feel like you need to redirect me?
51:25
SPEAKER_00: No, I think it's good.
51:26
SPEAKER_00: I don't know, as you said, if there's any company that really can be trusted.
51:30
SPEAKER_00: I hear a lot of positive things about Anthropic,
51:33
SPEAKER_00: but then I also just read earlier this week on LinkedIn actually,
51:36
SPEAKER_00: and it turned out it was an old story,
51:38
SPEAKER_00: but with Claude Desktop,
51:40
SPEAKER_00: they installed hook that would automatically give Claude access to any tab
51:48
SPEAKER_00: that you happen to be logged in this browser extension,
51:50
SPEAKER_00: even though they don't have any of those such things right now.
51:53
SPEAKER_00: And people would have no way of knowing that they were opting
51:56
SPEAKER_00: into not just what they put into it in the browser,
52:00
SPEAKER_00: but every other tab they have open, their bank accounts or anything, health data.
52:06
SPEAKER_00: And the fact that they deliberately released the extension with
52:11
SPEAKER_00: that built-in This feels like, okay, come on YouTube.
52:16
SPEAKER_00: Yeah.
52:17
SPEAKER_00: So I don't know if there's any company that really can be fully trusted.
52:21
SPEAKER_00: There are some, I know the founders, this is with a lot of startups.
52:25
SPEAKER_00: In fact, I just interviewed Hodman Murad and she was talking about her company, Asara.
52:29
SPEAKER_00: She doesn't collect data.
52:31
SPEAKER_00: From customers and she's very upfront about telling them what she will
52:34
SPEAKER_00: and will not collect or do with their data.
52:37
SPEAKER_00: She doesn't even take a credit card for the free accounts.
52:39
SPEAKER_00: And so I think founders values show up, but they can also be degraded by corporate pressures.
52:46
SPEAKER_00: As you're saying, it's the environment, it's the capitalist ecosystem that they all operate in.
52:51
SPEAKER_00: Yeah.
52:53
SPEAKER_01: Yeah.
52:54
SPEAKER_01: Yeah.
52:55
SPEAKER_00: Well, this is a great conversation, Jen.
52:56
SPEAKER_00: Thank you so much for joining me.
52:58
SPEAKER_00: Is there anything else that you would like to say?
52:59
SPEAKER_00: I'd like to hear a little bit more about your retreats actually.
53:02
SPEAKER_00: How do you help people recover from this?
53:06
SPEAKER_01: Yeah, I certainly do not have all my answers at all.
53:09
SPEAKER_01: And first, I want to say thank you so much, Karen.
53:11
SPEAKER_01: Again, I really admire what you're doing.
53:13
SPEAKER_00: I've done a lot of community work and community building work.
53:17
SPEAKER_00: It's really big load relationally
53:20
SPEAKER_01: and time and energy, all of it.
53:24
SPEAKER_01: And you do it with tons of grace and care and I think I told you once,
53:28
SPEAKER_01: I feel like you're the fairy godmother of Substack and you actually tend to us.
53:32
SPEAKER_01: And you notice that if we haven't been around in a while or what's happening,
53:36
SPEAKER_01: you are to me, the definition and embodiment of relational practice.
53:39
SPEAKER_01: And I just appreciate it, admire, respect it a lot.
53:42
SPEAKER_01: And what you're doing, she writes is so cool.
53:45
SPEAKER_01: It's so cool.
53:46
SPEAKER_01: It's a real privilege to be part of it and be with you in the conversation.
53:50
SPEAKER_00: Well, thank you.
53:51
SPEAKER_00: That's very kind.
53:53
SPEAKER_00: Yeah.
53:53
SPEAKER_00: Yeah.
53:54
SPEAKER_00: You're welcome.
53:54
SPEAKER_00: It's just true.
53:55
SPEAKER_01: I will say about the retreats, but may I also ask you, what drives you to do this?
54:00
SPEAKER_01: Like, why did you want to found She Writes AI?
54:03
SPEAKER_01: What's your founder's story for this work?
54:05
SPEAKER_00: Oh, yeah.
54:06
SPEAKER_00: Actually, I've been interviewed a couple of times about this.
54:08
SPEAKER_00: I'll drop you the links to those rather than taking up the time in your interview with it.
54:13
SPEAKER_00: But just starting from a very young age,
54:16
SPEAKER_00: I was always conscious of the fact that it was harder for girls and women to make
54:22
SPEAKER_00: a difference, to be recognized.
54:24
SPEAKER_00: And we're half the world.
54:25
SPEAKER_00: Our perspectives, our opinions, our experiences matter.
54:29
SPEAKER_00: The impetus for SheWrites AI in particular was right before Christmas in December 2024.
54:35
SPEAKER_00: I had finished my shopping and I was just browsing Substack
54:37
SPEAKER_00: and I found this article.
54:38
SPEAKER_00: Here's 10 people you should be following about AI and Substack.
54:42
SPEAKER_00: And how many women do you think were on the list?
54:46
SPEAKER_01: Exactly.
54:46
SPEAKER_00: Zero.
54:48
SPEAKER_00: None.
54:49
SPEAKER_00: And that was kind of a last straw for me.
54:51
SPEAKER_00: I messaged the guy and he said, oh, I just didn't know of any women writing about AI.
54:57
SPEAKER_00: It's nice to meet you.
55:00
SPEAKER_00: You've got to be kidding.
55:01
SPEAKER_00: I mean, I was already following like 34 women.
55:04
SPEAKER_00: I looked for them, but I didn't look that hard.
55:06
SPEAKER_00: They weren't hard to find.
55:08
SPEAKER_00: And I thought, okay, no excuses.
55:10
SPEAKER_00: You want to write a list?
55:11
SPEAKER_00: Here's 34 to start you with.
55:13
SPEAKER_00: And then the list just kind of took off from there.
55:16
SPEAKER_00: The list started growing by leaps and bounds.
55:18
SPEAKER_00: But the other thing was I started hearing from women like,
55:21
SPEAKER_00: oh, I mean, I'm not an only, you know?
55:24
SPEAKER_00: And that whole sense of we don't need just a directory,
55:27
SPEAKER_00: we need a community where people can support each other.
55:30
SPEAKER_00: And so that's how the directory kind of evolved into the community that we have now,
55:34
SPEAKER_00: which is one year old a week ago.
55:39
SPEAKER_00: And it's been really gratifying to see people connect and blossom.
55:43
SPEAKER_00: It's really been exciting.
55:44
SPEAKER_00: And I'm really happy about the books.
55:46
SPEAKER_00: It's giving people an experience that they would have probably found out of reach otherwise.
55:52
SPEAKER_00: And it's really cool to see people with their book selfies.
55:56
SPEAKER_00: The pride is just so cool to see that.
55:59
SPEAKER_01: Yeah.
56:00
SPEAKER_01: Being published is a dream come true for any writer and the way you've done it.
56:04
SPEAKER_01: There's a lot to feel proud about, I think, in that particular project.
56:08
SPEAKER_00: Yeah.
56:09
SPEAKER_00: And one thing that I really feel strongly about,
56:10
SPEAKER_00: there are a lot of communities out there that have a fee
56:14
SPEAKER_00: and I understand needing money to try to provide some of the features,
56:18
SPEAKER_00: but I just don't want there to be any financial barriers for anybody.
56:23
SPEAKER_00: People between jobs or people in other countries where even $100 is a lot of money.
56:29
SPEAKER_00: So trying to find ways to do it and keep it free is one of the bigger challenges,
56:33
SPEAKER_00: but I think it's worth it.
56:34
SPEAKER_00: We're making some good headway on that.
56:36
SPEAKER_00: I want to get back to your retreats.
56:39
SPEAKER_01: I can't remember how deep I went at the beginning,
56:41
SPEAKER_01: but it's,
56:42
SPEAKER_01: I guess, an experience that, in a sense, has been living in me for a long time.
56:46
SPEAKER_01: It's one of those things that I have found myself dreaming on versions of for
56:50
SPEAKER_01: a couple years now, and I feel that that's a strong signal to pay attention to.
56:55
SPEAKER_01: I remember,
56:55
SPEAKER_01: I don't know if it was Elizabeth Gilbert,
56:57
SPEAKER_01: I always credit her,
56:58
SPEAKER_01: I don't know if this is true,
56:59
SPEAKER_01: but I believe I was listening to her to speak and she was talking
57:02
SPEAKER_01: about how ideas are sentient and they'll keep knocking on your door
57:06
SPEAKER_01: until you pay attention.
57:07
SPEAKER_01: And if you don't pay attention, they'll leave and go knock on someone else's door.
57:10
SPEAKER_01: And I feel like this is very emergent through me and just really cool.
57:17
SPEAKER_01: I've been convening and designing experiences for a very long time.
57:22
SPEAKER_01: And this feels like taking 20 years of doing that and channeling it
57:27
SPEAKER_01: into what I hope will be a very intimate experience.
57:30
SPEAKER_01: So the premise is this I think I said this in the intro,
57:34
SPEAKER_01: but the design of our environment impacts us very significantly.
57:39
SPEAKER_01: And a lot of us don't have autonomy over the design of that environment.
57:46
SPEAKER_01: And there's all of these very quickly and rapidly advancing fields
57:50
SPEAKER_01: of practice like neuro-inclusive design,
57:52
SPEAKER_01: for example,
57:54
SPEAKER_01: that really show us that these micro and macro interventions in
57:59
SPEAKER_01: the environment are very impactful on our actual physiological state.
58:05
SPEAKER_01: And what we also know from research is that our physiological state,
58:09
SPEAKER_01: it essentially determines the outcomes that we're capable of.
58:12
SPEAKER_01: That's what Cal Newport's entire deep workbook was about.
58:15
SPEAKER_01: And the culture of work right now,
58:18
SPEAKER_01: at least speaking to knowledge work,
58:20
SPEAKER_01: and I think a lot of other economic domains,
58:23
SPEAKER_01: but for sure knowledge work, it's frenetic, right?
58:25
SPEAKER_01: It's the 275 interruptions a day.
58:28
SPEAKER_01: And the longer you stay in that type of environment,
58:32
SPEAKER_01: you're training yourself to operate that way.
58:35
SPEAKER_01: And it can make it harder to get to creative work,
58:40
SPEAKER_01: to long form thinking, long form writing strategy.
58:45
SPEAKER_01: There's so many different needs and applications for doing deep work and what comes from it.
58:53
SPEAKER_01: So we just really want to take all these learning.
58:56
SPEAKER_01: Anna, my partner in this, she's also about 20 years deep in convening and experience design.
59:03
SPEAKER_01: And so together we're taking all this interest in neuro-inclusive design
59:07
SPEAKER_01: and state shifting and creating intimate and trusting spaces where you are both
59:16
SPEAKER_01: in connection with a group but also have autonomy to rediscover your way
59:22
SPEAKER_01: of doing your best and deepest work and creating a container for that to happen.
59:29
SPEAKER_01: We're currently designing it as five days on the West Coast so it'll be here
59:33
SPEAKER_01: where we live on Vancouver Island near Victoria,
59:37
SPEAKER_01: BC and we found an absolutely gorgeous property.
59:41
SPEAKER_01: We're thinking it's going to be anywhere from 8 to 16 people and bring you together
59:48
SPEAKER_01: to create a space where you can go really deep on something that really matters
59:52
SPEAKER_01: to you.
59:53
SPEAKER_01: And our only rule for the experience is you can't have meetings.
59:57
SPEAKER_01: I don't really like rules.
59:58
SPEAKER_01: I don't like to over-program people.
1:00:00
SPEAKER_01: That's really important to me.
1:00:01
SPEAKER_01: So with summer retreat experiences and trainings and whatnot,
1:00:05
SPEAKER_01: you're scheduled from the minute you get up to the minute you go to bed.
1:00:08
SPEAKER_01: And our intent is to create enough structure to sort of hold people so
1:00:14
SPEAKER_01: that you do feel like there's things you can rely on and also to balance that
1:00:20
SPEAKER_01: with enough autonomy that we all work differently,
1:00:23
SPEAKER_01: we all create differently and some of us get in our deepest flow at 1am and some
1:00:28
SPEAKER_01: of us are morning people and so designing for that to allow for variation
1:00:33
SPEAKER_01: and how people access those parts of themselves because
1:00:36
SPEAKER_01: of creativity I don't think it means painting
1:00:38
SPEAKER_01: a picture every single human being is creative and creativity is,
1:00:45
SPEAKER_01: in my opinion, largely state dependent.
1:00:47
SPEAKER_01: So yeah, we're creating this container for that
1:00:50
SPEAKER_00: to happen.
1:00:51
SPEAKER_00: That sounds awesome.
1:00:52
SPEAKER_00: So the site is, I think, deependretreats.com?
1:00:56
SPEAKER_00: Yeah, thank you.
1:00:57
SPEAKER_00: Thank you.
1:00:57
SPEAKER_00: You also mentioned earlier that you are spinning back up into some consulting work.
1:01:03
SPEAKER_00: What would be the best way for someone to get in touch with you if they wanted
1:01:05
SPEAKER_00: to learn more about what you do there?
1:01:08
SPEAKER_00: Thank you, Karen.
1:01:09
SPEAKER_01: You're so excellent at directing and doing the general specific question.
1:01:12
SPEAKER_01: DM me on Substack would be one way to do that.
1:01:16
SPEAKER_01: I don't have a website up yet, but you could email me, jen at jenniferangelamcray.com.
1:01:24
SPEAKER_01: Yeah, I think those are probably
1:01:26
SPEAKER_00: the two best ways.
1:01:27
SPEAKER_00: Okay.
1:01:28
SPEAKER_00: That sounds great.
1:01:29
SPEAKER_00: Well, thank you so much, Jen.
1:01:30
SPEAKER_00: It was really great talking with you and I appreciate you making time for
1:01:33
SPEAKER_00: the interview and for sharing your thoughts about AI with us.
1:01:38
SPEAKER_01: Oh, so exciting to do it.
1:01:39
SPEAKER_01: Thank you, Karen.
1:01:39
SPEAKER_01: Thank you for inviting me.
1:01:40
SPEAKER_01: It's been very cool.
1:01:41
SPEAKER_01: I really appreciate it.
1:01:42
SPEAKER_01: I appreciate your time.
1:01:44
SPEAKER_01: Great.
1:01:44
SPEAKER_01: Thanks, Jen.
1:01:46
SPEAKER_01: Thank you.
1:01:47
SPEAKER_00: About this interview series and newsletter,
1:01:51
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