This post may feel random for my developing body of work, but I guarantee you it's not. AI is everywhere, some of us it, some of don't. Some of us don't know where to begin. But as a leader, it's developing in our orbit when it comes to work. As someone who loves it, believe in ethical use, here's what I have to say about its current state and how it can harm or help your own cognition.

In the past year, I've watched AI seep into every corner of content creation with the quiet persistence of water finding cracks. LinkedIn newsletters, influencer posts, corporate reports that cost a quarter million dollars—the infiltration is total, hallucinations and all. The tells reveal themselves once you know where to look, patterns repeating across industries and platforms like a signature no one meant to leave.

Parallel constructions pile up as if the writer found one hammer and declared everything a nail. Sentences fragment into two-word declarations, then bloat into explanations because the fragment couldn't stand alone. The sameness accumulates until it itches somewhere behind your eyes, and a question surfaces: who actually wrote this? The answer, increasingly, is no one—or rather, someone who pressed a button and accepted what emerged.

This morning, the final nail landed in a place I wasn't expecting. My favorite thought leader, someone I've followed for fifteen years and delusionally believe was my husband in another life, sent his Substack newsletter. It wasn't him—not his depth, not his brilliance, not his rhythms. The hollowness was unmistakable, and that was the moment this became personal enough to write about.

But first, I want to take you somewhere strange. What's happening with AI-generated content isn't merely a style problem or quality crisis that better prompts might solve. This hollowness spreading across the internet opens a window into something far more fascinating about humans and their complicated relationship with thinking itself, and following that thread leads somewhere the people selling these tools would very much prefer we didn't go.

The Miracle Solution They Sold Us

The conventional narrative has a satisfying simplicity that should make you suspicious. Lazy professionals cutting corners, frauds passing off machine output as human thought, a moral failure belonging to people who should have known better and chose convenience anyway. It's a tidy story with clear villains, and it lets the actual architects walk away without anyone noticing they've left the room.

Tilt your head and look at it sideways, though, and something else comes into focus. Consider what AI tools were marketed as from the very beginning—not thinking partners, not collaborators in the messy work of generating ideas, but replacement engines promising liberation from the burden of thought itself. The pitch decks and product demos positioned speed-to-output front and center while quality-of-thought never made it past the lobby, and the financial architecture tells its own story if you bother to trace it.

McKinsey cited $4.4 trillion in productivity gains while conveniently offering consulting services to capture those gains. Harvard's Ash Center tracked how AI keeps getting crowned as inevitable advancement despite persistent problems—built-in biases, hallucinated facts, intellectual property violations—because the narrative serves financial interests whether or not the product serves human ones.

The most revealing part is that tech insiders themselves quietly sing a different tune than their CEOs when the microphones aren't pointed at them, and even OpenAI's cofounder admitted that AI agents "just don't work" with current capabilities—a confession that would tank stock prices if anyone were paying attention to what the people actually building these systems believe about them.

So people used the product exactly as advertised, asked the machine to skip thinking, and it obliged with cheerful efficiency. The malpractice preceded the misuse, which means the crime wasn't user laziness but something far more calculated, baked into the pitch deck from day one by people who understood something about human cognition that most of us would prefer not to know about ourselves.

Why did this bargain work so well, this trade of your thinking for the relief of completion?

The answer lives in territory mapped by cognitive scientists long before anyone dreamed of ChatGPT, and what they found there isn't flattering to anyone involved.

When Exhausted Brains Meet Confident Machines

Tired brains defer to confident machines—not sometimes, not as a character flaw, but always, across every field where someone bothered to look. Automation bias research started tracking this phenomenon in aviation, then healthcare, then pretty much everywhere humans work alongside systems making recommendations. The pattern never varies, and the consistency is what makes it so unsettling once you see it clearly.

The more complex the task and the higher the workload, the more people accept whatever the machine suggests. Pilots ignore their instruments when the autopilot disagrees, and doctors defer to diagnostic software even when their clinical judgment raises flags.

One study on human-AI interaction discovered something particularly vicious in this dynamic—people doubt themselves specifically because the technology has been positioned as so advanced. Your judgment conflicts with what the system suggests, and instead of trusting your own assessment, you assume the machine knows something you don't. The algorithm didn't just replace your thinking; it undermined your confidence in your capacity to think at all.

Now layer in decision fatigue, which operates on its own brutal logic. Every choice depletes a finite cognitive resource, and when that resource runs low, humans default to whatever requires least effort. Psychologists have documented this thoroughly—when presented with a default option, a fatigued brain will take it because choosing requires active deliberation that the depleted system can no longer sustain.

Now situate this in the modern professional context, where you're expected to produce constantly, maintain presence across platforms, and demonstrate thought leadership whether or not your job involves having public thoughts. You're already running on cognitive fumes when the AI offers to carry the load, and the relief of completion overrides any recognition of mediocrity. You needed a post, and now you have a post, and the fact that it sounds like every other post registers only vaguely if at all. This is the exploitation at the center of the whole thing—systems designed to think for you, marketed to people too exhausted to notice they'd stopped thinking at all.

AI – The Oracle or the Workbench

This is where the path forks, and the terrain gets more interesting for those willing to stay on it. For those who find the sameness unbearable, who recognize themselves in the exhaustion but refuse to accept the bargain, there's a distinction worth understanding that changes how you relate to these tools entirely. The question isn't whether to use AI but how you position yourself in relation to it, and the difference between the two primary modes determines everything that follows.

Oracle mode is the default, the path of least resistance that the tools were designed to encourage. You pose a question, accept the answer, publish the result, and judgment gets outsourced along with production while the machine decides what's worth saying and how to say it. You become a relay station between algorithm and audience, your role reduced to quality control you're not actually performing because quality control requires the cognitive engagement you've already surrendered.

Workbench mode requires something fundamentally different, a posture that runs against the grain of how these tools were marketed. You bring raw materials to the table—a perspective even if it's only half-formed, a question you're genuinely trying to answer, context about what you're attempting and why it matters to you specifically. 

Workbench mode requires something fundamentally different, a posture that runs against the grain of how these tools were marketed. You bring raw materials to the table—a perspective even if it's only half-formed, a question you're genuinely trying to answer, context about what you're attempting and why it matters to you specifically. You use the machine to pressure-test your thinking, to surface angles you hadn't considered, to generate variations you can react against and argue with.

The tool remains the same in either case, and the difference is whether you show up to think or merely show up to publish, whether you treat the machine as a collaborator in your own intellectual work or as a replacement for having intellectual work in the first place.

Building Your Workbench

The question that surfaces once you understand the fork is practical and immediate — what does workbench mode actually look like when you're sitting in front of a blank prompt with a deadline breathing down your neck? The concept makes sense in theory, but theory dissolves quickly when exhaustion arrives and the machine is right there, ready to carry the load you're too tired to lift.

I've been using AI throughout the development of this piece, which means I've had to answer that question for myself in real time. Using Claude not as replacement for thinking but as a surface to think against requires deliberate structure that the speed-to-output marketing trained everyone to skip. What I've found actually matters comes down to architecture—the deliberate structures that keep you in the work rather than floating above it, and each one runs against the grain of how these tools trained us to interact with them.

Context means providing enough information for genuine usefulness, which most people skip entirely. Dumping a prompt into a blank space expecting magic resembles asking a new hire to write a quarterly strategy on day one without company history, audience information, or examples of what good looks like. Generic input yields generic output, and this is structural rather than mysterious—the machine can only work with what you give it.

Voice means protecting your sound from the machine's defaults, which requires active and ongoing resistance. Every AI has stylistic tendencies—preferred sentence patterns, vocabulary reaches, structural habits that emerge across millions of outputs. Without deliberate counterpressure, your writing drifts toward the mean, toward everyone else using the same tool, toward those tell-tale patterns we started with.

Boundaries mean defining what the AI should and shouldn't do, and this is where most people fail entirely. Boundaries require knowing what you want before you ask for it. You can instruct the machine to offer options instead of answers, push back on your thinking instead of validating it, identify argument weaknesses instead of just polishing prose. It means structuring your projects with guardrails so precise that Claude will say "I can't do this because you've told me not to write for you," which is exactly the kind of friction that keeps thinking active.

All of this might sound like a lot of effort for what amounts to writing a newsletter or finishing a report, and if output quality were the only thing at stake, you'd be right to wonder whether the friction is worth it. But there's something else happening when you defer to the machine without resistance, something that extends far beyond the mediocrity of any single piece of content.

The workbench isn't just about producing better work—it's about protecting something you might not notice losing until the loss is already significant.

From User to Used

Here's the part that should genuinely unsettle you, the part that moves beyond productivity concerns into something that touches on who you're becoming. If you approach AI as a way to avoid thinking, you will produce mediocre work regardless of how sophisticated your setup becomes — but the deeper risk isn't the quality of your output. The deeper risk is the slow atrophy of your capacity for original thought, happening so gradually you won't notice until it's already far along.

Each acceptance without critical engagement trains the pattern of deference a little deeper into your cognitive habits. Each time you take the output without pushing back, without arguing, without asking whether this is actually what you meant, you weaken the muscle that generates distinctive ideas. Recent research found that heavy AI use correlates with elevated cognitive miserliness — the more you defer, the more you train yourself to avoid cognitive effort entirely, not just in AI interactions but across everything you do.

The feedback loop closes so elegantly it would be beautiful if it weren't so troubling. Exhaustion drives reliance on the machine, reliance weakens your cognitive capacity over time, and weakened capacity increases the exhaustion that drove you to rely on the machine in the first place.

You're not just outsourcing production anymore—you're outsourcing the very judgment that would tell you the production isn't good enough.

The machines will keep improving at sounding human, at mimicking the patterns and rhythms that used to signal a mind at work, and that trajectory isn't going to reverse. What remains in your control is whether you keep the work of thought close even when systems offer to carry it for you.

This means treating AI output as raw material rather than finished product, as something to react against rather than passively accept, and it means slowing down in an environment that relentlessly punishes slowness. The alternative is watching your own thinking flatten into the same sameness, one accepted output at a time.

I'm taking a break from our deep content, to look at something in analytical, but more practical way. Lately, many women have been asking about the use of LinkedIn as through leadership and business development tool. Most of them are trying to understand the best practices for developing the channel for professional growth. Here's the thing, LinkedIn may or may not be the best investment of your time, here's a look at how to assess the channel, and determine if it's right for you.

I've gone down the rabbit holes of AI and algorithms for years, working in secret, tinkering and testing to discover how I make products, services, events, and content continually visible in the ever shifting landscape of discovery. What I'm finding are the surface-level shifts that your favorite experts and influencers write about are just that – surface level.

There's something deeper brewing in the depths, and I'll pop in here and there to this newsletter to drop knowledge on something that I think is worth your time (and I promise, it's not written by AI). I've been on LinkedIn for over a decade. I never really started using it until a few years ago, my use was sporadic. Even now, I'm a seasonally regular poster at best.

But in the last year, I've been using LinkedIn pages and paid ads for clients because I saw a new shimmer of hope when it came to meaningful engagement and return on ad spend. So I put consistent effort into studying the platform for their use. But what was once brilliant I never published because brilliance once discovered leads to mediocrity (cue LinkedIn Thought Leadership ads from a dude you've never heard of from a company or product you have no interest in).

Now, I'm seeing seismic shifts again. And it's left me asking, "What exactly is the best use case for LinkedIn?" And moreover, is it a place I want to be as a female leader (yep, there's gender dynamics attached).

Before You Look at Mechanics, Look at Your Goals

Before I dive specifically into Linkedin, I want to frame that it's important to assess every channel you invest energy, money or time into as every channel decision is an allocation decision. And every channel you’re investing you’re allocating your precious resources is in developing and deepening in ways that you may not realize. So let’s start with LinkedIn. 

In recent years, LinkedIn is where I’ve seen many women flock to because it was more manageable than having a 24/7 presence on Facebook, Instagram, or TikTok. Linkedin offered a more balanced approach to business and personal brand development, and didn’t appear to require as much mental labor. But that’s shifting, and now many women, including myself, find them asking, “What does LinkedIn actually do for my business?” 

When I’m asked this, I find myself asking many traditional business questions and directing women to ask themselves the following questions:

1. Who is your buyer, and where do they actually make decisions? Presence on a platform and conversion from it are different things, especially when it comes to Linkedin. 
2. What does success here look like in revenue terms? Not impressions, not follower counts. I ask them can you draw a direct line from LinkedIn activity to a client conversation, a speaking inquiry, a retained engagement?
3. What is your natural communication mode? How do you actually speak? Translating yourself into a format that doesn't fit costs energy that compounds over time. 
4. How do you learn, and how does your buyer learn? This piggybacks off question #3. I ask, them Do you watch, do you listen, do you look, or do you read? Do you do all four? That says a lot how to show up
5. How many channels can you realistically sustain at depth? Is the channel something something you can and want to use long term? Your Channel strategy has to reflect that.

Overall, I don’t think women should strive to use more than two channels very well unless they have an extremely well-dialed team supporting them who can carry the social load. So now let’s look at LinkedIn in the context of this analysis. 

What LinkedIn Actually Is in 2026

In typical Macala fashion, I fell down the rabbit hole of researching what was happening with LinkedIn. And I found three things that any woman using the platforms need to consider when making a decision how to use the platform, if at all. 

Reach is Down Across the Board

According to research by LinkedIn analyst Richard van der Blom, who analyzed 1.8 million posts for his Algorithm InSights 2025 report, organic performance has dropped measurably platform-wide: views down 50%, engagement down 25%, follower growth down 59% year-over-year. LinkedIn attributes the shift to increased content volume — more posts competing for a shrinking feed. For anyone building from scratch, discoverability and visibility are more challenging. 

Don't Question the Link, Question the Strategy

All of the linkedin experts seem to get hung up on the mechanics of posts, honing in on what influences post reach and visibility. None is more hotly talked about than links. The conventional wisdom is that links kill reach. LinkedIn's own Sr. Director of Product has stated on record — documented by media reporter Matt Navarra — that there is no intentional algorithmic penalty for posts containing links, provided the content leads with value.

What practitioners observe in testing often contradicts that. Rand Fishkin of SparkToro documented in January 2026 that LinkedIn is actively collapsing linked comments on mobile and desktop — hiding them from view unless users actively seek them out. His conclusion is that LinkedIn structurally disincentivizes posts that point traffic elsewhere, regardless of whether that's an official policy. The gap between what LinkedIn says and what creators measure is worth knowing before you build a strategy around either position.

LinkedIn's Content Ecosystem is a Closed System

LinkedIn newsletters and Pulse articles have no SEO value and cannot be distributed or referenced outside the platform. Content published there lives under LinkedIn's distribution rules, surfaced to who LinkedIn decides, when LinkedIn decides. The implications go further than most creators realize. LinkedIn actively blocks external crawling of its content — including by AI tools and search engines. 

That means your articles won't surface in Google search, won't be cited by AI discovery tools, and won't be found by anyone who isn't already on LinkedIn. Compare that to content you own — a Substack, a blog on your own domain, a published article on an indexable platform. If building a body of work you own — one that grows in discoverability over time — is part of your goal, LinkedIn's content tools are the wrong infrastructure for that. You're not building an archive. You're renting space in a closed system.

For me this changes the entire use case of LinkedIn. Having to create specific content, to perform in-platform, in order to build an audience becomes very unincentivized. I’m building a rented house on rented land, where the landlord can change the rules anytime. 

And Then There’s The Gender Variable

In November 2025, mental health professional Megan Cornish published findings from an experiment in which she posted to LinkedIn under a male-presenting profile and compared performance against her own established account. The male-presenting posts measurably outperformed her own. Her research went viral. 

LinkedIn responded. Cornish spoke directly with Laura Lorenzetti Soper, who leads LinkedIn's Global Editorial team. Soper confirmed that gender is not an explicit ranking signal. She also confirmed that early engagement carries significant weight in how the algorithm distributes content.

Cornish's sharper argument is that those two facts don't cancel each other out. Equal treatment and equal outcomes are not the same thing. If early engagement is the primary distribution signal, and a professional culture historically grants more authority to male-coded business voices, then women don't lose at the algorithm level — they lose at the cultural level that feeds it. The machine inherits the bias, scales it, and calls it neutral.

This appears to be a specific consequence for women in relational fields — coaching, consulting, advisory work, healthcare, mental health, education — is that the natural professional voice in those fields is collaborative, nuanced, and relational rather than declarative. That voice tends to generate less early engagement in LinkedIn's current environment. Less early engagement means less distribution. There is no switch to fix this.

Cornish was careful not to overstate it: "I don't think there's a secret 'hide the women' switch buried somewhere at LinkedIn HQ." What she documented is subtler and harder to solve — a system that treats engagement as a neutral signal while operating inside a culture where engagement is not neutral at all.

I’ve seen Cornish’s findings come into play first hand. I dig to surface voices and visionaries that are doing deep work on LinkedIn. And I have to wade through false signals in order to find it. There are many women on LinkedIn working in very nuanced ways within their fields, it doesn’t fit the algorithmic formula, thus making it much harder for their work to be seen and discovered. 

The Situationship with LinkedIn

Where I feel this leaves us as women is that we find ourselves in a situationship with LinkedIn. Honestly, for some the platform is a fit, for others, it is not. 

LinkedIn makes strategic sense when:

• Your buyers are B2B, corporate, or professional services clients who actively use the platform and make or influence purchasing decisions there;
• You're building toward speaking, board positions, or thought leadership in a field where; LinkedIn authority translates to those opportunities;
• Your natural communication register is analytical and declarative — the voice the platform's engagement culture rewards;
• You have an existing warm network that can seed early engagement;
• You can post 3-5 times weekly with genuine substance.

LinkedIn is a harder fit when:

• Your buyers don't make purchasing decisions based on LinkedIn presence, even if they have profiles;
• Your field requires relational, nuanced language that will consistently underperform against current platform engagement patterns;
• You're starting from zero with no existing network to generate early engagement;
• You have channels already working, and LinkedIn would come at their expense;
• You value discoverability that comes from search and AI engines;
• The platform's format and culture are misaligned with how you actually think and communicate;
• And you simply don’t like it (let’s face it – the news feed is a constant nervous system dysregulator).  

My Thoughts on Relational Fields 

For women in mental health, physical health, coaching, grief work, somatic practice, and similar fields — the calculus deserves further scrutiny. These fields depend on trust built through voice, relationship, and language that doesn't perform well against authority-signaling content in a professional feed. 

There are women generating significant income in these fields with no LinkedIn presence. There are others for whom it works specifically because they've positioned their practice around B2B referrals or organizational consulting. The field alone doesn't answer the question. The buyer does. It’s why channel presence and use has to be intentional. 

If You Decide You Can’t Live Without LinkedIn

If you've worked through the goals questions and LinkedIn fits, a few principles hold regardless of algorithm changes:

1. The value has to live in the post. Given the contested and shifting link situation, building content that delivers its full value inside the post — without requiring a click elsewhere — is the most durable approach. This is also, not coincidentally, where the web broadly is heading. Zero-click content isn't a workaround. It's a strategic shift in how you think about what you're publishing and where.
2. Consistency over volume. Posting consistently about 2-3 focused themes over time builds topical recognition — with the algorithm and with your audience. Posting frequently about unrelated topics undermines it. One focused post per week with real substance outperforms daily posts that are scattered or thin.
3. Comments are underused. Substantive engagement on relevant posts in your niche does more for visibility and relationship-building than most people's posting schedule. This is also the most direct way to address the early engagement problem — getting into conversations early builds the network that will show up for your content.
4. Profile and content should tell the same story. If your posts are about one thing and your profile reads like a generic resume, both the algorithm and humans see the disconnect.
5. Measure what actually matters to you. Not impressions. Whether the right people are finding you and the right conversations are happening.

An Example of This In Use

Most of my favorite women I follow on LinkedIn – Jasmine Bina, Amy Daroukokis,  Ida Persson, Emma Grede – have podcasts, Substacks newsletters or YouTube channels. For podcasters or YouTube hosts, LinkedIn posting requires a specific reframe. Podcasts and video episodes live off-platform — that's not changing. So how do you promote these within the context of Linkedin?

First, the LinkedIn post about that episode cannot be a promotional announcement with a link. It has to be its own thing. What you would do is pull the sharpest insight from the conversation and write it as a standalone post and add a video cut to that sound bite (similar a YouTube short) and add it to that post.

Take the argument you made in the episode and make it on LinkedIn in full, in your words, without the listener needing to go anywhere. Let the post be complete. If someone finds the podcast afterward because the post made them want more — that's the right order of operations. LinkedIn surfaces the thinking. The podcast deepens the relationship.

What doesn't work: "New episode out today — link in comments." 

What does work: the post is the episode's best idea, fully expressed, and the podcast is where people go when they want to sit with you for an hour.

The same principle applies to any external content — Substack, blog, YouTube. LinkedIn is not a distribution channel for work that lives elsewhere. It's where the work itself shows up, in a form native to the platform. Everything else is a destination for people who already trust you enough to follow you there. Make sure your critical links are found in your contact info. 

Choose a Relationship Over The Situationship

Here's what I know about situationships: they persist because leaving requires a decision, and decisions require clarity about what you actually want.

So let me be clear about mine:

My LinkedIn presence is fading this quarter — not dramatically, not with a farewell post, just quietly redirecting toward the places where my thinking comes alive. Substack, where I own what I build. Pinterest, which rewards the long game. And real rooms with real people, which no algorithm has managed to replicate yet.

The deeper question this whole rabbit hole opened up isn't really about LinkedIn. It's about what you're building, who you're building it for, and whether the infrastructure you're pouring time into is actually designed to serve that — or designed to serve the platform.

Every channel has a contract buried in the fine print. LinkedIn's says: create here, perform here, stay here. The audience you build is ours. The content you publish is ours to distribute or not. The rules can change on a Tuesday.

Some women will read all of this and decide LinkedIn is exactly right for what they're doing. Good. Go do it with full intention and none of the guilt about not being somewhere else.

Others will read it and feel something loosen — permission to stop translating themselves into a format that was never quite built for them.

Both are valid exits from the situationship.

The only wrong move is staying by default — showing up out of obligation, posting because you feel like you should, building on rented land without ever asking why you chose this neighborhood in the first place.

You get to choose your channels. Choose ones that want you back.

How to Be Human, Part III — A Three-Part Series on How Women have Lost Connection with Our Humanity and How We Get It Back

We are living in an age where crisis is no longer an occasional rupture in the fabric of daily life — crisis is the fabric. But here the thing, the "crisis" is largely manufactured, curated, sold, and resold across every media platform, political narrative, and economic model.

The reason for this is unsophisticated, simply put — crisis captures attention. From there, it hijacks the nervous system, short-circuits reflective thought, and propels immediate reaction. In an attention economy, immediate reaction is the most monetizable human state there is.

Outrage, fear, indignation — these are high-yield emotions. They generate clicks, shares, engagement metrics that translate directly into revenue.

In a world built to capitalize on emotional flooding, emotional regulation is not taught, encouraged, or rewarded. It is quietly, systematically eroded.

The Biology of Being Overwhelmed

The biological reality is blunt, when we are constantly flooded with emotionally charged stimuli, the brain’s architecture changes. Chronic stress elevates cortisol, shrinks the hippocampus — the center for memory and emotional regulation — and amplifies amygdala reactivity, the fight-or-flight machinery that evolved for occasional acute threats followed by periods of recovery.

Today, that recovery never comes. Before one crisis is metabolized, another demands response. The nervous system stays locked in a state of perpetual emergency that was never meant to be permanent. In this landscape, being emotionally reactive is not a character flaw. It is a conditioned state, and a profitable one.

Every platform, every algorithm, every media channel is engineered to trigger responses that bypass reflection.

When I understood that — really understood it, not as an intellectual concept but as something I could feel happening in my own body in real time — the shame I’d been carrying about my own reactivity began to dissolve. I wasn’t broken. I was responding exactly as designed.

The Illiteracy We Inherited

From an early age, most of us were conditioned to view emotional expression through the lens of reward and punishment. Children who express anger get shamed. Those who show vulnerability get labeled weak. Schools, workplaces, families — they teach that managing emotion means suppressing it or performing it for social approval.

The result is emotional illiteracy dressed up as maturity. We recognize the loud emotions — anger, excitement, despair — but we can’t name the subtler ones underneath. Disappointment. Longing. Shame. The feelings that actually drive the behavior we can’t seem to change. Without that literacy, emotional life becomes reactive by default:

A criticism becomes a personal attack. A disagreement becomes a betrayal. A moment of uncertainty spirals into an existential crisis that the body cannot distinguish from physical danger.

I lived inside that cycle for years, convinced that my intensity was the problem, that if I could just contain it better I’d stop causing damage. What I didn’t understand was that containment and regulation are entirely different things. One is a cage, the other is capacity.

Steadiness as Subversion

True emotional regulation is the capacity to feel fully without being overtaken. It is the slow strengthening of internal architecture that can hold complexity without collapse. This doesn’t look like calm. Sometimes it looks like sitting in a car for twenty minutes after a conversation because the feeling needs somewhere to land before you act on it. Sometimes it looks like saying I need to come back to this instead of detonating in the moment.

It is unsexy, undramatic work that no one will applaud. But here is what I’ve found — regulation doesn’t dampen the richness of emotional life. It deepens it. When you are not constantly overwhelmed by manufactured intensity, you become capable of more nuanced, textured feeling. Beneath the loud emotions that dominate reactive culture lie subtler, more complex ones that connect you more honestly to yourself and to other people. The emotions you were never allowed to feel become accessible once you stop drowning in the ones you were engineered to perform.

In a culture that profits from emotional reactivity, calm is subversive. In a political landscape fueled by outrage, steady presence is radical. In a market economy driven by anxiety, a regulated nervous system is a quiet refusal to be turned into a product of someone else’s crisis architecture. It is one of the core capacities we must rebuild if we are going to remember how to be human — not the optimized, algorithmic version, but the messy, contradictory, fully alive one.

What would shift if you stopped treating your emotional responses as verdicts and started treating them as information?

How to Be Human, Part II — A Three-Part Series on How Women Have Lost Our Humanity

In our society today, self-awareness has never been widespread. Human beings have always struggled to confront their internal contradictions, their fears, the grief they’d rather not name. That work requires space, time, and a tolerance for discomfort that most of us were never taught. But the forces working against it now are more organized, more sophisticated, and more relentless than anything previous generations faced.

The attention economy doesn’t simply distract; it repurposes human cognition, fragmenting inner coherence into consumable reactions. Every notification, every curated feed, every algorithm is designed to intercept the small moments where reflection might arise and replace them with the next immediate stimulus. The average person checks their phone 96 times a day — once every ten minutes of waking life.

Each interruption isn’t a momentary break in concentration. It’s a reset of attentional capacity, a fracture in the cognitive continuity required to know yourself at all. But technology alone can’t explain what’s happened. There is something deeper, something that was already broken before the first smartphone lit up.

The Fear Underneath

As women, self-awareness is frightening because it forces confrontation. Not just with our aspirations but with our failures. Not just with our pain but with the ways we’ve contributed to other people’s suffering. It demands honesty without brutality, tenderness without indulgence, responsibility without self-destruction.

Most systems — religious, educational, corporate — never equipped us for that work. They trained obedience, productivity, and certainty. Very few trained the resilient capacity to sit inside ambiguity and contradiction and feeling without fleeing. So we developed sophisticated imitations instead.

The language of personal growth and emotional intelligence is everywhere now — personality tests, self-help programs, online quizzes that promise to reveal who we really are. Most of it produces categorical identities rather than complex understanding, simplified narratives rather than ongoing inquiry. Performative self-knowledge. The appearance of introspection without its substance. It treats symptoms rather than identifying root causes.

What the Horse Saw

I learned what fragmented attention actually costs when I began working closely with horses. Horses respond to what’s invisible to most humans — the tension running beneath the surface, the incoherence between the body and whatever performance the mind is projecting. During one session, I was trying to guide a nervous gelding through a ground exercise and I could feel my frustration building, my impatience tightening everything. Nothing was working.

Only when I stopped — truly stopped, not the performed version of stopping where your body stills but your mind keeps grinding — did I feel what was actually there. Simmering shame and exhaustion from earlier failures that week, running underneath every interaction like a current I’d refused to acknowledge. The horse felt it before I did. He’d been responding to the truth of me while I was busy responding to the story of me.

Self-awareness is not surface noticing. It’s the willingness to encounter the raw material inside yourself, unfiltered and unedited, and to let it inform the present without drowning it. Most of us are trained to skip that step entirely. We perform calm, while the undercurrents of fear and grief and anger run unattended. And everything — relationships, decisions, the way we move through a room — suffers for it.

Small Acts of Reclamation

Rebuilding self-awareness begins with reclaiming attention, and not just from technology. From our own conditioned avoidance, we must learn to once again sit through the discomfort of a "waiting room" without reaching for the phone. We must learn to name an emotional state before reacting to it; noticing when a habitual narrative is running and choosing to pause rather than repeat it unconsciously. These sound small, but in a world engineered to capture and monetize every flicker of attention, they are acts of resistance.

Self-awareness is not self-obsession. It’s self-stewardship — the ability to notice what’s true inside without immediately fleeing, fixing, or performing.

It’s slow work, often invisible, and it happens over a series of years. But it’s the foundation without which nothing else holds. Without it, emotional regulation becomes suppression. Communication becomes manipulation. Purpose becomes performance. The entire architecture of a human life depends on this one capacity — the willingness to turn toward rather than away from your own internal landscape.

In a world designed to fragment and capture attention, there is nothing more countercultural than sustained, curious awareness of your own inner being. There's truly nothing more radical than the choice to notice, stay, and witness your own experience without judgment or the compulsive need to make it content.

When did you last stop long enough to hear something inside you that wasn’t curated for anyone else’s consumption?

How to Be Human — A Three-Part Series on How Women are Losing Their Humanity

There is a kind of violence that never announces itself. No gunfire, no banners, no moment where someone can point and say — "There. That’s where it happened." Instead, it moves surgically through daily life, rewiring what we expect from each other and ourselves until what was once unthinkable becomes invisible. How do I know? Because, I watched it happen to me for years before I could name it.

It feels as if everywhere I look today, I feel I'm bearing firsthand witness to the collapse of civil dialogue, the monetization of outrage, the replacement of genuine connection with curated content. And truth be told, I don't think any of this arrived by accident. These are the logical outcomes of systems built for scale, designed to extract rather than nourish.

What looks like cultural decline is actually cultural reconfiguration, a deliberate restructuring of human experience to serve algorithmic parameters and market imperatives. Technology didn’t invent the hunger for control over other people’s attention, but it supercharged it beyond anything we were equipped to metabolize.

Today, the algorithms we dance with on a daily basis don’t just recommend entertainment. They shape emotional baselines and weaponize identity. Behavioral tracking isn’t an occasional breach of privacy — it’s the engine of modern economics. On TikTok alone, content related to “trauma” saw a 248% increase in views between 2020 and 2023. What was once a deeply personal, unwieldy process of healing is now public spectacle, trending aesthetic, algorithmic currency. The inner world — once private, tender, impossible to flatten — has been turned inside out for consumption.

The Fracture, Up Close

In January of 2025, I witnessed demonstrators at Texas State University stood holding signs that read:

“Types of Property: Women, Slaves, Animals, Land, Etc.”

They weren’t misquoted. They weren’t taken out of context. They were making a deliberate claim that hierarchy and ownership are ordained, righteous even. I sat with that image for days, not because it shocked me but because of how quickly the cycle moved on. Outrage, screenshot, share, forget. The machinery of attention consumed it and produced nothing.

It would be comforting to call that an outlier. But it’s the visible edge of something we’ve all been swimming in — a culture that has normalized domination at every level. Of bodies, of attention, of emotions, of truth itself. The extremism on that campus is a louder version of the same logic running quietly through the rest of our lives, the logic that says efficiency matters more than empathy, performance more than presence, extraction more than understanding.

The Part We Don’t Want to Say

Here is the uncomfortable truth I keep returning to:

Systems didn’t do this to us alone. We participated. We let it happen. Sometimes we chose it.

I realized, that even for me, I chose it — I spent years optimizing myself into someone the algorithm could recognize, measuring my worth in metrics that had nothing to do with being alive. I confused being productive with being present, being visible with being known.

I also recognize that, as women, we traded the messy, mysterious work of being human for the false promise that our suffering could be engineered away if we just hacked ourselves properly. We stopped asking what it means to be in right relationship with ourselves, with each other, with the world. Instead we started asking how to survive the system without losing everything — or worse, how to win inside it. And somewhere in that shift, we forgot that being human was never supposed to be something we had to remember.

The Quiet Rebellion

Being human now is an act of rebellion, which is a sentence that should embarrass all of us. But here we are. The rebellion isn’t loud. It looks like noticing when your attention has been hijacked. It looks like refusing the belief that you must constantly upgrade yourself to remain worthy. It looks like rebuilding the muscle memory of empathy and curiosity and self-awareness — capacities that have atrophied in a world that rewards their absence.

This is not nostalgia for some imagined golden age. And I’m not interested in performing change while the real work goes undone. What I’m describing is the urgent, unglamorous process of remembering who and what we were before the noise and the extraction. The project ahead is not technological. It’s psychological. It’s the reclamation of capacities that make a fully human life possible — capacities we will need more than ever as the systems accelerate.

What did you trade away so slowly you didn’t notice it was gone?