September 29, 2025 • 24 mins
The Cost of Convenience: How Technology is Redefining Connection and Creativity
In this episode of PsyberSpace, host Leslie Poston digs into the impact of technological convenience on our emotional and cognitive lives. Inspired by a conversation with Jason Miller, Leslie explores how platforms like Facebook and generative AI tools are stripping away meaningful friction from our interactions, creativity, and mental tasks, leading to reduced emotional investment and cognitive development. The episode discusses concepts like emotional labor, effort justification, intermittent reinforcement, and the importance of cognitive friction for real connection and growth. Leslie also addresses the balance between accessibility and meaningful challenge, urging listeners to choose their frictions wisely and remain intentional about the technologies they adopt.
00:00 Introduction and Inspiration
00:38 The Impact of Social Media on Friendships
02:48 Emotional Labor and Effort Justification
08:38 The Role of Friction in Creativity
14:31 The Downside of Frictionless Technology
18:52 Balancing Accessibility and Meaningful Engagement
21:05 Conclusion: Embracing Productive Friction
References
Aaru, J. (2025) Artificial Intelligence and the Internal Processes of Creativity. The Journal of Creative Behavior. 59(2)
Al-Zahrani, A.M. (2024) Balancing Act: Exploring the Interplay Between Human Judgement and Artificial Intelligence in Problem-Solving, Creativity, and Decision-Making. IgMin Research. 2(3): 145-158
Alter, A. L., Oppenheimer, D. M., Epley, N., & Eyre, R. N. (2007). Overcoming intuition: Metacognitive difficulty activates analytic reasoning. Journal of Experimental Psychology: General, 136(4), 569–576.
Bjork, R. A. (1994). Memory and metamemory considerations in the training of human beings. In J. Metcalfe & A. P. Shimamura (Eds.), Metacognition: Knowing about knowing (pp. 185–205). MIT Press.
Csikszentmihalyi, M. (1990). Flow: The psychology of optimal experience. Harper & Row.
Dunbar, R. I. M. (1998). The social brain hypothesis. Evolutionary Anthropology, 6(5), 178–190.
Ellis, K., & Kent, M. (2011). Disability and new media. Routledge.
Festinger, L. (1957). A theory of cognitive dissonance. Stanford University Press.
Hochschild, A. R. (1983). The managed heart: Commercialization of human feeling. University of California Press.
Hochschild, A. R. (1983). The managed heart: Commercialization of human feeling.
Risko, E. F., & Gilbert, S. J. (2016). Cognitive offloading. Trends in Cognitive Sciences, 20(9), 676–688.
Norman, D. A. (2007). The design of future things. Basic Books.
Raichle, M. E., et al. (2001). A default mode of brain function. Proceedings of the National Academy of Sciences, 98(2), 676-682.
Seligman, M. E. P. (1972). Learned helplessness. Annual Review of Medicine, 23(1), 407-412.
Sweller, J. (1988). Cognitive load during problem solving: Effects on learning. Cognitive Science, 12(2), 257-285.
Skinner, B. F. (1953). Science and human behavior.
Article in New Yorker on AI and Culture: https://www.newyorker.com/magazine/2025/09/01/ai-is-coming-for-culture
Mark as Played
Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Leslie Poston (00:12):
Welcome back to PsyberSpace I'm your host,
Leslie Poston. Today's episodewas inspired by a real life
conversation I was having withfriend and colleague Jason
Miller on another socialnetwork. He runs a b to b
marketing and music podcastcalled b to b sides that you
should check out if that'ssomething you're interested in.
(00:35):
Without further ado, today'stopic.
Remember when you had toremember someone's birthday?
Maybe you wrote it on your wallcalendar or jotted it in your
day planner. You might havecalled your friend on the phone
or sent a card by mail. Theeffort, as small as it was,
actually helped keep thatfriendship a lot. It created a
(00:56):
thread of memory and emotionalinvestment.
Then along came Facebook.Suddenly, this app was telling
us when to say happy birthday,how to say happy birthday, what
emojis to use, or whether to usea generic post and telling us
who to do it for. And in theprocess, we all gradually
(01:17):
stopped doing the work offriendship. That's not just
nostalgia talking. That's theresult of platforms stripping
away something called emotionallabor and replacing it with
frictionless interaction thatfeels like connection and mimics
connection but isn't necessarilyreal connection.
(01:38):
And now generative AI is doingthe same thing to our
creativity. It gives usshortcuts that feel powerful,
but they come at a cost. Theyremove the messy, meaningful
cognitive friction where realinsight tends to be born. If
you've listened to my episode,your brain on easy mode, you
(01:59):
already know our brains arewired to choose comfort over
challenge, which makes thesefrictionless tools feel good
even when they're quietlydismantling the depth of our
thinking. This episode builds abit on that concept.
Today, we're talking about howtechnology's obsession with ease
may be unraveling everythingfrom friendships to our
(02:22):
imagination. Let's get into it.Now I'm not here to tell you
social media is evil or AI willdestroy us all. I've done
multiple episodes defendingmindful scrolling and showcasing
research on the benefits ofdigital connection. But there's
(02:42):
something specific happeningwith friction here that is worth
examining in this episode.
Emotional labor is the effortrequired to manage emotions in
social relationships. It's notjust about being nice. It's
about doing the work ofconnection. Before social media,
that labor was embedded in howwe navigated friendship. It was
(03:05):
frictional.
We actually had to try. Therewas no notification prompting
you to message your friend. Youhad to care enough to do it
yourself. You had to rememberbirthdays, plan get togethers,
navigate conflicts face to face.The effort mattered because it
was an investment of time,attention, and emotional energy.
(03:28):
And here's the thing. Thatinvestment created the value of
the friendship. When we workharder for something, we tend to
value it more. This is a welldocumented psychological
principle called effortjustification. The more we put
into a friendship, the moremeaningful it becomes.
But social platforms changedthat equation. They automated
(03:51):
the reminders, simplified theresponses, and started turning
friendship maintenance into aflattened series of low effort
clicks. What felt likeconvenience was actually
erosion, the slow wearing awayof the emotional scaffolding
that held real liferelationships together. To be
clear, digital connections canabsolutely become meaningful
(04:14):
real life relationships, butonly when we bring old school
emotional effort to onlineinteractions and eventually move
them beyond the confines of asocial media platform. The
medium isn't the problem.
It's the low effort, algorithmmediated way that we're trained
to use it. Facebook didn't justremove friction from friendship.
(04:41):
It replaced meaningfulinteraction with something more
insidious (04:44):
intermittent reinforcement. This is a concept
from behavioral psychology whererewards come unpredictably,
creating some of the strongestpatterns of repeated behavior
that we know. Think about slotmachines.
You don't win every time youpull the lever, but you might
(05:04):
win. And that possibility keepspeople playing. Social media
works much the same way. Youpost something, and maybe you'll
get a like, maybe you won't,maybe some comments, maybe
silence. The unpredictabilitymakes it a little addictive.
But here's the problem: intermittent reinforcement is (05:23):
undefined
designed to keep you engagingwith the platform, not the
actual people. You becomeaddicted to the possibility of
social validation, not to makinggenuine connections. The
dopamine hit comes from thenotification, not from deepening
a relationship. The neurosciencebehind this is pretty
(05:47):
interesting. Intermittentreinforcement hijacks our
brain's dopamine system, whichnormally helps us learn from
unexpected rewards.
But social media turns thislearning mechanism into an
addiction mechanism. Everyunpredictable like or comment
triggers a prediction error inour dopamine neurons, the same
(06:08):
system that's supposed to helpus adapt and grow. This creates
continuous partial attention.You're always somewhat engaged
with your phone, always checkingfor that next hit of social
feedback. Meanwhile, the personsitting across from you at
dinner gets your leftoverattention.
The friction of a realconversation, the pauses, the
(06:30):
misunderstandings, the need toreally listen, starts to feel
clunky and stressful compared tothe smooth dopamine delivery
system in your pocket. But thatfriction is exactly what builds
intimacy and understandingbetween people. What if the
problem isn't, Oh, humans arelazy, but that we're being
systematically trained to avoidthe very experiences that make
(06:53):
us human? There is a fascinatingconcept in psychology that we've
talked about in other episodescalled cognitive dissonance, the
mental discomfort that we feelwhen our actions don't align
with our beliefs. One way weresolve this discomfort is
through effort justification.
(07:14):
We convince ourselves thatthings we've worked hard for
must be valuable. This principleexplains why friendships that
survive challenges often feelstronger, why difficult
conversations can deepen bonds,and why relationships that
require effort can feel moremeaningful than relationships
that don't. Facebook and othersocial platforms disrupted this
(07:37):
psychology. They made socialinteraction so easy that it lost
its psychological weight. Sayinghappy birthday when a
notification reminds you isn'tjust more convenient.
It's somehow less meaningfulthan remembering on your own.
The platform turned genuineeffort into low effort signals.
Like a heart emoji, an autogenerated birthday message,
(08:00):
these gestures feel likeconnection, but they lack the
investment that makes theconnection real. By removing the
friction, we remove the value.And data backs this up.
Studies on social media useconsistently show that passive
engagement can be associatedwith decreased well-being, while
(08:22):
active engagement commenting,messaging, and creating can have
more positive effects. Thedifference is the effort.
Passive consumption requires noinvestment, so it tends to
create no emotional return. Thesame dynamic that's affecting
our friendships is transforminghow we create, and the stakes
(08:44):
might be even higher. Creativityisn't just about having good
ideas.
It's about developing themthrough process. That process
requires desirable difficulties,challenges that are harder in
the moment but lead to betterlong term learning and insight.
When you struggle to find theright word, when you get stuck
(09:06):
on a problem and have to thinkaround it to find a solution,
when you write that terriblefirst draft and revise it five
times, that struggle isn'twasted energy. It's where
originality happens. Research onlearning shows us that when
things come too easily, theydon't stick.
Easy learning feels good in themoment, but it creates shallow
(09:28):
understanding. Difficultlearning feels frustrating but
builds expertise and insight.There's also a neuroplasticity
angle here. Our brains operateon a use it or lose it
principle. When we consistentlyoutsource cognitive tasks to AI,
we're not just avoiding effort,we're potentially weakening the
(09:49):
neural pathways that supportindependent thinking.
The brain regions responsiblefor creativity, critical
analysis, and problem solvingneed regular challenge to
maintain their strength.Generative AI offers what looks
like creativity, essays, images,code, and music. But it skips
(10:10):
the cognitive friction wherereal creative development
happens. When AI writes yourfirst draft, you miss the
thinking that happens in thestruggle to articulate your
ideas. When it generates yourbrainstorm, you miss the mental
flexibility that comes frompushing through creative blocks.
This isn't just about outputquality, it's about cognitive
(10:33):
development. Every time weoutsource cognitive work to AI,
we lose an opportunity tostrengthen our own thinking
muscles. There's a concept inpsychology called flow, the
mental state where challengemeets skill level, creating deep
engagement and optimalperformance. Flow happens when a
(10:55):
task is hard enough to requireyour full attention, but not so
hard that it overwhelms you.Flow is where creativity
thrives.
It's where athletes performtheir best, where artists create
their most meaningful work,where programmers solve their
most complex problems. And flowrequires friction the right
(11:16):
amount of difficulty to keep youfully engaged. LLM and
Generative AI tools oftenpromise to get you into flow
faster by removing obstacles.But in practice, they might be
preventing flow altogether. Ifthe challenge is too low, if AI
is doing the hard thinking foryou, you never enter that state
(11:38):
of deep engagement.
This connects to somethingcalled the default mode network,
a brain network that activateswhen we're not focused on
specific tasks. As I'vediscussed in previous episodes,
this boredom network is crucialfor creativity, insight, and
memory consolidation. But whenAI provides instant stimulation
(12:00):
and answers, we rarely enter themental downtime where our best
ideas emerge. And here's a wildthought. What if boredom is
actually a feature, not a bug?
We're constantly consuminginstead of creating the space
for an original thought. Thinkabout the difference between
using a calculator for complexmath versus working through it
(12:23):
by hand. The calculator givesyou the right answer faster, but
working through it manuallyengages different cognitive
processes. You understand theproblem differently, you notice
patterns, and you developmathematical intuition. The same
thing happens with creativework.
When AI generates ideas for you,you're not developing your own
(12:45):
creative intuition. When itwrites for you, you're not
building your own voice. When itsolves problems for you, you're
not strengthening your ownproblem solving ability. Here's
something counterintuitive (12:58):
When something is slightly harder to
process, we often understand itbetter. This is called cognitive
disfluency, and it's beendemonstrated in numerous
studies.
Researchers have found that whentest materials are printed in
hard to read fonts, studentsperform better on comprehension
(13:20):
tests. When math problems arepresented in a way that requires
more effort to understand,students are actually more
likely to catch their ownerrors. The extra difficulty
forces deeper processing.Generative AI optimizes for the
opposite (13:36):
cognitive fluency. It makes everything smooth, easy to
understand, and polished.
But that smoothness might bepreventing the kind of deep
thinking that leads to insightand originality. This relates to
cognitive load theory fromneuroscience. There's productive
cognitive load that buildsexpertise, and there's
unproductive load that justcreates confusion. AI often
(14:00):
removes productive load themental effort that strengthens
our thinking while sometimesadding unproductive load through
choice overload. When AI offersendless creative options, we
might spend more energy choosingthan creating.
When your first draft looksfinished, do you bother
revising? When the AI generatedimage looks perfect, do you push
(14:23):
yourself to imagine somethingdifferent? When the answer comes
instantly, do you questionwhether it's the right question?
Friction isn't just aninconvenience to be optimized
away. It's often a signal thatreal thinking is happening.
Regular listeners will befamiliar with the psychological
(14:44):
phenomenon called learnedhelplessness. If you're new,
that's where repeated exposureto uncontrollable situations
leads people to stop trying,even when they actually do have
control. It was first studied inexperiments with dogs who
stopped trying to escapeelectric shocks, even when
escape became possible. I worrythat AI dependency might be
(15:08):
creating a similar effect withhuman creativity and problem
solving. When AI consistentlyoutperforms us at writing, image
generation, and ideadevelopment, people might
internalize the message thatthey're not good at those things
and that they should just letthe AI handle it.
This can be particularlydangerous because creativity and
(15:29):
critical thinking are skillsthat require practice and
failure. They're not fixedtalents. They're capabilities
that strengthen with use andatrophy without it. Every time
we default to AI, instead ofstruggling through a creative
challenge ourselves, we'repotentially weakening our own
creative confidence. Memoryresearch shows us another
(15:52):
concerning pattern.
When we offload memory tasks totechnology, we don't just lose
recall. We lose theconsolidation process where
memories become insights. Theact of remembering isn't just
storage and retrieval. It'sactive reconstruction that
creates new connections andunderstanding. AI that remembers
(16:13):
for us might be preventing thisdeeper learning process.
The risk isn't just that webecome dependent on AI. It's
that we lose faith in our owncognitive abilities, and we
develop learned helplessnessabout thinking itself. And
unlike the dogs and thepsychology experiments, we're
choosing this helplessness.We're opting into it because it
(16:36):
feels easier in the moment. Buteasy and helpful, they aren't
the same thing.
One of the most underappreciatedcasualties of frictionless
technology might be ourtolerance for ambiguity and
uncertainty. Both deeprelationships and creative work
require the ability to sit withnot knowing, to be comfortable
(17:00):
with questions that don't haveimmediate answers. Real
conversations are messy andunpredictable. You don't know
where they'll go, what you'lllearn about the other person, or
how your own thinking mightchange. That uncertainty is part
of what makes human connectionmeaningful, and it's exactly
what social media algorithms tryto eliminate.
(17:22):
Similarly, creative work beginswith uncertainty. You start with
a vague idea, a feeling, aquestion without an answer. The
creative process is aboutexploring that uncertainty,
following threads that mightlead nowhere, and being willing
to not know until knowingemerges. Generative AI tools
tend to collapse uncertaintyquickly. Ask a question, get an
(17:46):
answer.
Describe what you want, get aresult. This efficiency comes at
a cost. It trains us to expectquick resolution instead of
learning to work productivelywith ambiguity. There's also a
social comparison element here.When we see AI generated content
that looks perfect, weunconsciously compare our rough
(18:07):
human efforts to polishedalgorithmic outputs.
This is like comparing yourbehind the scenes struggle to
someone else's highlight reel,except now the highlight reel is
generated by machines trained onmillions of examples. This sets
an impossible standard for humancreativity. But ambiguity
tolerance is critical for bothrelationships and creativity.
(18:31):
It's what allows you to haveconversations where you might
change your mind, to exploreideas that might not work, and
to be curious instead ofcertain. When technology
consistently resolvesuncertainty for us, we might be
losing our capacity to navigatethe uncertain spaces where
growth happens.
Let's address something thatcomes up whenever we critique
(18:56):
frictionless technology, andthat's the Trojan horse of
accessibility. It is absolutelytrue that generative AI tools
help many people. Text tospeech, auto captioning,
predictive typing, grammarassistance, and more. These
features can be transformativefor people with disabilities,
(19:17):
people learning new languages,or people with limited time or
resources. But here's where weneed to be careful.
Accessibility is often used as arhetorical shield to deflect
criticism of broader designchoices. Tech companies wrap
things in the language ofinclusion to accelerate
adoption, And then further downthe road, they avoid deeper
(19:41):
questions about what their toolsare optimizing for. There is a
big difference between removingunjust barriers and removing
growth producing challenge.Accessibility should mean access
to meaningful engagement, notjust access to effortless
consumption. When a company usesaccessibility language to
(20:04):
justify AI features that reducecognitive effort for everyone,
they're often not servingdisabled users.
They're serving their ownbusiness models. True
accessibility would give peopletools to engage more deeply with
creative and social challenges,not to bypass them entirely.
We're also seeing hedonicadaptation in our relationship
(20:26):
with convenience. Just like weadapt to other pleasures and
need increasing amounts to feelsatisfied, we adapt to
frictionless technology andbecome less tolerant of any
difficulty. What felt convenientyesterday becomes baseline
today.
Anything requiring effort beginsto feel frustrating. This
(20:47):
adaptation cycle keeps pushingus toward more automation, more
convenience, and more frictionremoval. We can support
accessibility while stillquestioning whether frictionless
design serves human flourishing.These two ideas are not in
conflict. So where does thisleave us?
(21:08):
We can't uninvent social media,and the cash cow hype train of
artificial intelligence hascertainly left the station. And
maybe we shouldn't want to.These tools do have some real
benefits, but we can be moreintentional about how we design
and use them. We should ask,does this tool remove barriers
or remove meaning? Does itsupport human capacity or does
(21:32):
it replace it?
Does it enhance our ability toconnect and create, or does it
make us more passive consumersof automated connection and
creation? The goal is not tomake everything difficult. It's
just to preserve the type ofdifficulty that helps us grow.
We want to make and deploytechnology that scaffolds human
(21:53):
development, not technology thatshortcuts it. Attention research
is also relevant here.
When we switch between AIassistance and our own thinking,
we experience attention residuecognitive resources that remain
stuck on the previous task. Thismakes both our AI assisted work
and our independent work lesseffective. We're not fully
(22:16):
present for either mode ofthinking. This might mean
choosing AI tools that help youthink better, rather than tools
that think for you. It mightmean using our social platforms
to facilitate real worldconnections, rather than
replacing them.
It might mean embracinguncertainty and effort as
features, not bugs, in bothrelationships and creative work.
(22:39):
The pattern we've exploredtoday, the erosion of meaningful
friction, shows up everywhere inmodern life, from passive
politics to passive consumptionto passive creation. It's all
connected, and it all points tothe same question: What kind of
humans do we want to become? Welive in a world where ease is
(23:00):
everything. Tap to like,autofill this message, generate
the image, post the thoughts youdidn't really think.
But here's the truth (23:07):
what makes something meaningful is often
the struggle it took to getthere. Emotional labor isn't
wasted energy it's intimacy.Cognitive friction isn't a bug
it's how we grow. The dopaminehit from a like will fade. The
satisfaction from a conversationyou invested in will last.
(23:30):
The AI generated essay mightimpress people, but the ideas
you struggled to articulate willchange how you think. So this
week, start to notice where easeis replacing effort in your
life. Notice when technologyoffers to remove friction and
ask yourself, is this frictionserving me, and is the struggle
part of the point? Choose yourfrictions wisely. Some barriers
(23:54):
need to come down, but somedifficulties are worth
preserving because they're notobstacles to human flourishing.
They're the path to it. Thanksfor listening to PsyberSpace.
I'm your host, Leslie Poston,signing off and reminding you to
stay curious. Don't forget tolike and subscribe so you get an
episode every week, and send itto a friend if you think that
(24:15):
they'll enjoy it.
Welcome back to PsyberSpace I'm your host,
Leslie Poston. Today's episodewas inspired by a real life
conversation I was having withfriend and colleague Jason
Miller on another socialnetwork. He runs a b to b
marketing and music podcastcalled b to b sides that you
should check out if that'ssomething you're interested in.
(00:35):
Without further ado, today'stopic.
Remember when you had toremember someone's birthday?
Maybe you wrote it on your wallcalendar or jotted it in your
day planner. You might havecalled your friend on the phone
or sent a card by mail. Theeffort, as small as it was,
actually helped keep thatfriendship a lot. It created a
(00:56):
thread of memory and emotionalinvestment.
Then along came Facebook.Suddenly, this app was telling
us when to say happy birthday,how to say happy birthday, what
emojis to use, or whether to usea generic post and telling us
who to do it for. And in theprocess, we all gradually
(01:17):
stopped doing the work offriendship. That's not just
nostalgia talking. That's theresult of platforms stripping
away something called emotionallabor and replacing it with
frictionless interaction thatfeels like connection and mimics
connection but isn't necessarilyreal connection.
(01:38):
And now generative AI is doingthe same thing to our
creativity. It gives usshortcuts that feel powerful,
but they come at a cost. Theyremove the messy, meaningful
cognitive friction where realinsight tends to be born. If
you've listened to my episode,your brain on easy mode, you
(01:59):
already know our brains arewired to choose comfort over
challenge, which makes thesefrictionless tools feel good
even when they're quietlydismantling the depth of our
thinking. This episode builds abit on that concept.
Today, we're talking about howtechnology's obsession with ease
may be unraveling everythingfrom friendships to our
(02:22):
imagination. Let's get into it.Now I'm not here to tell you
social media is evil or AI willdestroy us all. I've done
multiple episodes defendingmindful scrolling and showcasing
research on the benefits ofdigital connection. But there's
(02:42):
something specific happeningwith friction here that is worth
examining in this episode.
Emotional labor is the effortrequired to manage emotions in
social relationships. It's notjust about being nice. It's
about doing the work ofconnection. Before social media,
that labor was embedded in howwe navigated friendship. It was
(03:05):
frictional.
We actually had to try. Therewas no notification prompting
you to message your friend. Youhad to care enough to do it
yourself. You had to rememberbirthdays, plan get togethers,
navigate conflicts face to face.The effort mattered because it
was an investment of time,attention, and emotional energy.
(03:28):
And here's the thing. Thatinvestment created the value of
the friendship. When we workharder for something, we tend to
value it more. This is a welldocumented psychological
principle called effortjustification. The more we put
into a friendship, the moremeaningful it becomes.
But social platforms changedthat equation. They automated
(03:51):
the reminders, simplified theresponses, and started turning
friendship maintenance into aflattened series of low effort
clicks. What felt likeconvenience was actually
erosion, the slow wearing awayof the emotional scaffolding
that held real liferelationships together. To be
clear, digital connections canabsolutely become meaningful
(04:14):
real life relationships, butonly when we bring old school
emotional effort to onlineinteractions and eventually move
them beyond the confines of asocial media platform. The
medium isn't the problem.
It's the low effort, algorithmmediated way that we're trained
to use it. Facebook didn't justremove friction from friendship.
(04:41):
It replaced meaningfulinteraction with something more
insidious (04:44):
intermittent reinforcement. This is a concept
from behavioral psychology whererewards come unpredictably,
creating some of the strongestpatterns of repeated behavior
that we know. Think about slotmachines.
You don't win every time youpull the lever, but you might
(05:04):
win. And that possibility keepspeople playing. Social media
works much the same way. Youpost something, and maybe you'll
get a like, maybe you won't,maybe some comments, maybe
silence. The unpredictabilitymakes it a little addictive.
But here's the problem: intermittent reinforcement is (05:23):
undefined
designed to keep you engagingwith the platform, not the
actual people. You becomeaddicted to the possibility of
social validation, not to makinggenuine connections. The
dopamine hit comes from thenotification, not from deepening
a relationship. The neurosciencebehind this is pretty
(05:47):
interesting. Intermittentreinforcement hijacks our
brain's dopamine system, whichnormally helps us learn from
unexpected rewards.
But social media turns thislearning mechanism into an
addiction mechanism. Everyunpredictable like or comment
triggers a prediction error inour dopamine neurons, the same
(06:08):
system that's supposed to helpus adapt and grow. This creates
continuous partial attention.You're always somewhat engaged
with your phone, always checkingfor that next hit of social
feedback. Meanwhile, the personsitting across from you at
dinner gets your leftoverattention.
The friction of a realconversation, the pauses, the
(06:30):
misunderstandings, the need toreally listen, starts to feel
clunky and stressful compared tothe smooth dopamine delivery
system in your pocket. But thatfriction is exactly what builds
intimacy and understandingbetween people. What if the
problem isn't, Oh, humans arelazy, but that we're being
systematically trained to avoidthe very experiences that make
(06:53):
us human? There is a fascinatingconcept in psychology that we've
talked about in other episodescalled cognitive dissonance, the
mental discomfort that we feelwhen our actions don't align
with our beliefs. One way weresolve this discomfort is
through effort justification.
(07:14):
We convince ourselves thatthings we've worked hard for
must be valuable. This principleexplains why friendships that
survive challenges often feelstronger, why difficult
conversations can deepen bonds,and why relationships that
require effort can feel moremeaningful than relationships
that don't. Facebook and othersocial platforms disrupted this
(07:37):
psychology. They made socialinteraction so easy that it lost
its psychological weight. Sayinghappy birthday when a
notification reminds you isn'tjust more convenient.
It's somehow less meaningfulthan remembering on your own.
The platform turned genuineeffort into low effort signals.
Like a heart emoji, an autogenerated birthday message,
(08:00):
these gestures feel likeconnection, but they lack the
investment that makes theconnection real. By removing the
friction, we remove the value.And data backs this up.
Studies on social media useconsistently show that passive
engagement can be associatedwith decreased well-being, while
(08:22):
active engagement commenting,messaging, and creating can have
more positive effects. Thedifference is the effort.
Passive consumption requires noinvestment, so it tends to
create no emotional return. Thesame dynamic that's affecting
our friendships is transforminghow we create, and the stakes
(08:44):
might be even higher. Creativityisn't just about having good
ideas.
It's about developing themthrough process. That process
requires desirable difficulties,challenges that are harder in
the moment but lead to betterlong term learning and insight.
When you struggle to find theright word, when you get stuck
(09:06):
on a problem and have to thinkaround it to find a solution,
when you write that terriblefirst draft and revise it five
times, that struggle isn'twasted energy. It's where
originality happens. Research onlearning shows us that when
things come too easily, theydon't stick.
Easy learning feels good in themoment, but it creates shallow
(09:28):
understanding. Difficultlearning feels frustrating but
builds expertise and insight.There's also a neuroplasticity
angle here. Our brains operateon a use it or lose it
principle. When we consistentlyoutsource cognitive tasks to AI,
we're not just avoiding effort,we're potentially weakening the
(09:49):
neural pathways that supportindependent thinking.
The brain regions responsiblefor creativity, critical
analysis, and problem solvingneed regular challenge to
maintain their strength.Generative AI offers what looks
like creativity, essays, images,code, and music. But it skips
(10:10):
the cognitive friction wherereal creative development
happens. When AI writes yourfirst draft, you miss the
thinking that happens in thestruggle to articulate your
ideas. When it generates yourbrainstorm, you miss the mental
flexibility that comes frompushing through creative blocks.
This isn't just about outputquality, it's about cognitive
(10:33):
development. Every time weoutsource cognitive work to AI,
we lose an opportunity tostrengthen our own thinking
muscles. There's a concept inpsychology called flow, the
mental state where challengemeets skill level, creating deep
engagement and optimalperformance. Flow happens when a
(10:55):
task is hard enough to requireyour full attention, but not so
hard that it overwhelms you.Flow is where creativity
thrives.
It's where athletes performtheir best, where artists create
their most meaningful work,where programmers solve their
most complex problems. And flowrequires friction the right
(11:16):
amount of difficulty to keep youfully engaged. LLM and
Generative AI tools oftenpromise to get you into flow
faster by removing obstacles.But in practice, they might be
preventing flow altogether. Ifthe challenge is too low, if AI
is doing the hard thinking foryou, you never enter that state
(11:38):
of deep engagement.
This connects to somethingcalled the default mode network,
a brain network that activateswhen we're not focused on
specific tasks. As I'vediscussed in previous episodes,
this boredom network is crucialfor creativity, insight, and
memory consolidation. But whenAI provides instant stimulation
(12:00):
and answers, we rarely enter themental downtime where our best
ideas emerge. And here's a wildthought. What if boredom is
actually a feature, not a bug?
We're constantly consuminginstead of creating the space
for an original thought. Thinkabout the difference between
using a calculator for complexmath versus working through it
(12:23):
by hand. The calculator givesyou the right answer faster, but
working through it manuallyengages different cognitive
processes. You understand theproblem differently, you notice
patterns, and you developmathematical intuition. The same
thing happens with creativework.
When AI generates ideas for you,you're not developing your own
(12:45):
creative intuition. When itwrites for you, you're not
building your own voice. When itsolves problems for you, you're
not strengthening your ownproblem solving ability. Here's
something counterintuitive (12:58):
When something is slightly harder to
process, we often understand itbetter. This is called cognitive
disfluency, and it's beendemonstrated in numerous
studies.
Researchers have found that whentest materials are printed in
hard to read fonts, studentsperform better on comprehension
(13:20):
tests. When math problems arepresented in a way that requires
more effort to understand,students are actually more
likely to catch their ownerrors. The extra difficulty
forces deeper processing.Generative AI optimizes for the
opposite (13:36):
cognitive fluency. It makes everything smooth, easy to
understand, and polished.
But that smoothness might bepreventing the kind of deep
thinking that leads to insightand originality. This relates to
cognitive load theory fromneuroscience. There's productive
cognitive load that buildsexpertise, and there's
unproductive load that justcreates confusion. AI often
(14:00):
removes productive load themental effort that strengthens
our thinking while sometimesadding unproductive load through
choice overload. When AI offersendless creative options, we
might spend more energy choosingthan creating.
When your first draft looksfinished, do you bother
revising? When the AI generatedimage looks perfect, do you push
(14:23):
yourself to imagine somethingdifferent? When the answer comes
instantly, do you questionwhether it's the right question?
Friction isn't just aninconvenience to be optimized
away. It's often a signal thatreal thinking is happening.
Regular listeners will befamiliar with the psychological
(14:44):
phenomenon called learnedhelplessness. If you're new,
that's where repeated exposureto uncontrollable situations
leads people to stop trying,even when they actually do have
control. It was first studied inexperiments with dogs who
stopped trying to escapeelectric shocks, even when
escape became possible. I worrythat AI dependency might be
(15:08):
creating a similar effect withhuman creativity and problem
solving. When AI consistentlyoutperforms us at writing, image
generation, and ideadevelopment, people might
internalize the message thatthey're not good at those things
and that they should just letthe AI handle it.
This can be particularlydangerous because creativity and
(15:29):
critical thinking are skillsthat require practice and
failure. They're not fixedtalents. They're capabilities
that strengthen with use andatrophy without it. Every time
we default to AI, instead ofstruggling through a creative
challenge ourselves, we'repotentially weakening our own
creative confidence. Memoryresearch shows us another
(15:52):
concerning pattern.
When we offload memory tasks totechnology, we don't just lose
recall. We lose theconsolidation process where
memories become insights. Theact of remembering isn't just
storage and retrieval. It'sactive reconstruction that
creates new connections andunderstanding. AI that remembers
(16:13):
for us might be preventing thisdeeper learning process.
The risk isn't just that webecome dependent on AI. It's
that we lose faith in our owncognitive abilities, and we
develop learned helplessnessabout thinking itself. And
unlike the dogs and thepsychology experiments, we're
choosing this helplessness.We're opting into it because it
(16:36):
feels easier in the moment. Buteasy and helpful, they aren't
the same thing.
One of the most underappreciatedcasualties of frictionless
technology might be ourtolerance for ambiguity and
uncertainty. Both deeprelationships and creative work
require the ability to sit withnot knowing, to be comfortable
(17:00):
with questions that don't haveimmediate answers. Real
conversations are messy andunpredictable. You don't know
where they'll go, what you'lllearn about the other person, or
how your own thinking mightchange. That uncertainty is part
of what makes human connectionmeaningful, and it's exactly
what social media algorithms tryto eliminate.
(17:22):
Similarly, creative work beginswith uncertainty. You start with
a vague idea, a feeling, aquestion without an answer. The
creative process is aboutexploring that uncertainty,
following threads that mightlead nowhere, and being willing
to not know until knowingemerges. Generative AI tools
tend to collapse uncertaintyquickly. Ask a question, get an
(17:46):
answer.
Describe what you want, get aresult. This efficiency comes at
a cost. It trains us to expectquick resolution instead of
learning to work productivelywith ambiguity. There's also a
social comparison element here.When we see AI generated content
that looks perfect, weunconsciously compare our rough
(18:07):
human efforts to polishedalgorithmic outputs.
This is like comparing yourbehind the scenes struggle to
someone else's highlight reel,except now the highlight reel is
generated by machines trained onmillions of examples. This sets
an impossible standard for humancreativity. But ambiguity
tolerance is critical for bothrelationships and creativity.
(18:31):
It's what allows you to haveconversations where you might
change your mind, to exploreideas that might not work, and
to be curious instead ofcertain. When technology
consistently resolvesuncertainty for us, we might be
losing our capacity to navigatethe uncertain spaces where
growth happens.
Let's address something thatcomes up whenever we critique
(18:56):
frictionless technology, andthat's the Trojan horse of
accessibility. It is absolutelytrue that generative AI tools
help many people. Text tospeech, auto captioning,
predictive typing, grammarassistance, and more. These
features can be transformativefor people with disabilities,
(19:17):
people learning new languages,or people with limited time or
resources. But here's where weneed to be careful.
Accessibility is often used as arhetorical shield to deflect
criticism of broader designchoices. Tech companies wrap
things in the language ofinclusion to accelerate
adoption, And then further downthe road, they avoid deeper
(19:41):
questions about what their toolsare optimizing for. There is a
big difference between removingunjust barriers and removing
growth producing challenge.Accessibility should mean access
to meaningful engagement, notjust access to effortless
consumption. When a company usesaccessibility language to
(20:04):
justify AI features that reducecognitive effort for everyone,
they're often not servingdisabled users.
They're serving their ownbusiness models. True
accessibility would give peopletools to engage more deeply with
creative and social challenges,not to bypass them entirely.
We're also seeing hedonicadaptation in our relationship
(20:26):
with convenience. Just like weadapt to other pleasures and
need increasing amounts to feelsatisfied, we adapt to
frictionless technology andbecome less tolerant of any
difficulty. What felt convenientyesterday becomes baseline
today.
Anything requiring effort beginsto feel frustrating. This
(20:47):
adaptation cycle keeps pushingus toward more automation, more
convenience, and more frictionremoval. We can support
accessibility while stillquestioning whether frictionless
design serves human flourishing.These two ideas are not in
conflict. So where does thisleave us?
(21:08):
We can't uninvent social media,and the cash cow hype train of
artificial intelligence hascertainly left the station. And
maybe we shouldn't want to.These tools do have some real
benefits, but we can be moreintentional about how we design
and use them. We should ask,does this tool remove barriers
or remove meaning? Does itsupport human capacity or does
(21:32):
it replace it?
Does it enhance our ability toconnect and create, or does it
make us more passive consumersof automated connection and
creation? The goal is not tomake everything difficult. It's
just to preserve the type ofdifficulty that helps us grow.
We want to make and deploytechnology that scaffolds human
(21:53):
development, not technology thatshortcuts it. Attention research
is also relevant here.
When we switch between AIassistance and our own thinking,
we experience attention residuecognitive resources that remain
stuck on the previous task. Thismakes both our AI assisted work
and our independent work lesseffective. We're not fully
(22:16):
present for either mode ofthinking. This might mean
choosing AI tools that help youthink better, rather than tools
that think for you. It mightmean using our social platforms
to facilitate real worldconnections, rather than
replacing them.
It might mean embracinguncertainty and effort as
features, not bugs, in bothrelationships and creative work.
(22:39):
The pattern we've exploredtoday, the erosion of meaningful
friction, shows up everywhere inmodern life, from passive
politics to passive consumptionto passive creation. It's all
connected, and it all points tothe same question: What kind of
humans do we want to become? Welive in a world where ease is
(23:00):
everything. Tap to like,autofill this message, generate
the image, post the thoughts youdidn't really think.
But here's the truth (23:07):
what makes something meaningful is often
the struggle it took to getthere. Emotional labor isn't
wasted energy it's intimacy.Cognitive friction isn't a bug
it's how we grow. The dopaminehit from a like will fade. The
satisfaction from a conversationyou invested in will last.
(23:30):
The AI generated essay mightimpress people, but the ideas
you struggled to articulate willchange how you think. So this
week, start to notice where easeis replacing effort in your
life. Notice when technologyoffers to remove friction and
ask yourself, is this frictionserving me, and is the struggle
part of the point? Choose yourfrictions wisely. Some barriers
(23:54):
need to come down, but somedifficulties are worth
preserving because they're notobstacles to human flourishing.
They're the path to it. Thanksfor listening to PsyberSpace.
I'm your host, Leslie Poston,signing off and reminding you to
stay curious. Don't forget tolike and subscribe so you get an
episode every week, and send itto a friend if you think that
(24:15):
they'll enjoy it.
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