Marcela Azevedo

Transformação, Cultura & Pessoas | +15 anos em RH & Change Management | hr-brasil
#RH #Mudança #Cultura #TrabalhoDoFuturo #comportamentohumano

[Andrew Ng @AndrewYNg]

There will be no AI jobpocalypse.

The story that AI will lead to massive unemployment is stoking unnecessary fear. AI — like any other technology — does affect jobs, but telling overblown stories of large-scale unemployment is irresponsible and damaging. Let’s put a stop to it.

I’ve expressed skepticism about the jobpocalypse in previous posts. I’m glad to see that the popular press is now pushing back on this narrative. The image below features some recent headlines.

Software engineering is the sector most affected by AI tools, as coding agents race ahead. Yet hiring of software engineers remains strong! So while there are examples of AI taking away jobs, the trends strongly suggest the net job creation is vastly greater than the job destruction — just like earlier waves of technology. Further, despite all the exciting progress in AI, the U.S. unemployment rate remains a healthy 4.3%.

Why is the AI jobpocalypse narrative so popular? For one thing, frontier AI labs have a strong incentive to tell stories that make AI technology sound more powerful. At their most extreme, they promote science-fiction scenarios of AI “taking over” and causing human extinction. If a technology can replace many employees, surely that technology must be very valuable!

Also, a lot of SaaS software companies charge around $100-$1000 per user/year. But if an AI company can replace an employee who makes $100,000 — or make them 50% more productive — then charging even $10,000 starts to look reasonable. By anchoring not to typical SaaS prices but to salaries of employees, AI companies can charge a lot more.

Additionally, businesses have a strong incentive to talk about layoffs as if they were caused by AI. After all, talking about how they’re using AI to be far more productive with fewer staff makes them look smart. This is a better message than admitting they overhired during the pandemic when capital was abundant due to low interest rates and a massive government financial stimulus.

To be clear, I recognize that AI is causing a lot of people’s work to change. This is hard. This is stressful. (And to some, it can be fun.) I empathize with everyone affected. At the same time, this is very different from predicting a collapse of the job market.

Societies are capable of telling themselves stories for years that have little basis in reality and lead to poor society-wide decision making. For example, fears over nuclear plant safety led to under-investment in nuclear power. Fears of the “population bomb” in the 1960s led countries to implement harsh policies to reduce their populations. And worries about dietary fat led governments to promote unhealthy high-sugar diets for decades.

Now that mainstream media is openly skeptical about the jobpocalypse, I hope these stories will start to lose their teeth (much like fears of AI-driven human extinction have).

Contrary to the predictions of an AI jobpocalypse, I predict the opposite: There will be an AI jobapalooza! AI will lead to a lot more good AI engineering jobs, and I’m also optimistic about the future of the overall job market. What AI engineers do will be different from traditional software engineering, and many of these jobs will be in businesses other than traditional large employers of developers. In non-AI roles, too, the skills needed will change because of AI. That makes this a good time to encourage more people to become proficient in AI, and make sure they’re ready for the different but plentiful jobs of the future!

[Original text in The Batch newsletter.]

[Big Think @bigthink]

AI is not the root problem.

According to Eric Markowitz @ericmarkowitz, AI is a mirror reflecting a system that already treats human value as expendable.

Read the full article: https://t.co/gOw87Qei7O

[a16z @a16z]

The majority of new jobs created since 1940 didn’t even exist in 1940.

There is no fixed "lump of labor". Again and again, new technologies create new jobs.

a16z's David George dismantles the "AI job apocalypse" myth: https://t.co/0gL5mdffKD

[BusinessIntelligence @bimedotcom]

Computational foundations of the human world
https://t.co/AYP2J3vyAQ
✍️ Marcus J. Hamilton et al. via @arxiv

👉 Human societies turn scattered information into collective decisions and coordinated action (e.g., via markets, governments, norms, and science).
👉 The paper treats these social processes as computational phenomena and explores how ideas from theoretical computer science—especially newer approaches beyond traditional Turing machines and worst-case complexity—can help explain them.

@Corix_JC @ahier @sim010101 @Sonu_Monika @maponi @sallyeaves @CEO_AISOMA @dinisguarda @JagersbergKnut @Shi4Tech @FernandaKellner @PVynckier @EstelaMandela @TheAIObserverX @chidambara09 @sulefati7 @SusanHayes_ @theomitsa @TarakRindani @FrRonconi @Nicochan33 @pchamard @JoannMoretti @Khulood_Almani @Fabriziobustama @mikeflache @TysonLester @Eli_Krumova @smaksked @amalmerzouk @Analytics_699 @MaryRich78 @NathaliaLeHen @sminaev2015 @WillyRayNick @DanielleLargier @RLDI_Lamy

[Alvin Foo @alvinfoo]

Every generation thinks the next machine will replace humanity.

The tractor.
Electricity.
The computer.
The internet.

Now AI.

But history says something different.

When the cost of intelligence drops, human ambition expands.

That’s the part most people miss.

The recent a16z article on the “AI Job Apocalypse” made one thing very clear:

AI is not deleting work.
It’s reallocating work. (https://t.co/1LseIZltyh)

Routine tasks shrink.
Higher leverage work grows.

The spreadsheet didn’t eliminate finance.
The internet didn’t eliminate business.
The smartphone didn’t eliminate communication.

They created entirely new industries.

AI will do the same.

The winners in this era will not be the people fighting AI.

It will be the people using AI to amplify judgment, creativity, speed, and execution.

One person with AI can now:
- build a company faster
- launch products faster
- learn faster
- create content faster
- solve problems faster

We are entering an age where intelligence becomes abundant.

And when intelligence becomes abundant, execution becomes the new scarcity.

That changes everything.

The most optimistic part?

A teenager with a laptop now has capabilities that once required entire corporations.

That is not dystopian.
That is empowering.

Yes, some jobs will disappear.
Every technological revolution reshapes labor.

But new industries are already emerging:
AI operators.
AI strategists.
AI workflow architects.
Human-AI collaboration designers.
Autonomous business builders.

The future belongs to people who adapt early.

Not people who panic early.

AI is not the end of human value.

It’s the beginning of a new operating system for civilization.

And the people who learn to work with intelligence instead of competing against it will build the next generation of companies, wealth, and breakthroughs.

The industrial revolution multiplied physical power.

AI multiplies cognitive power.

That’s a far bigger shift.

Source : @a16z https://t.co/wLYnXTrx7L

[Himanshu Kumar @codewithimanshu]

Every time you accepted a salary, chose a price, or walked into a negotiation, the other person was running game theory in their head.

You were guessing.

This 1-hour Yale lecture by Professor Ben Polak will change how you read people and make decisions forever.

MBAs pay $150K to learn this. Yale posted it on YouTube for free.

Save this post. Watch it this tonight.

Follow @codewithimanshu for more high-signal content that actually changes the trajectory of your career.
↓

Here's why most people lose every negotiation they enter.
You walked into your last salary discussion hoping for the best.

They walked in with frameworks. Payoff matrices. Dominant strategies. Backward induction. Nash equilibrium.

You said "I was thinking $85K." They already knew the number you'd accept. Because they ran the game before you sat down.

That's not a skill gap. That's a universe gap.
And it's costing you $20K, $50K, $100K every single year.
↓

Game theory isn't math for MBAs.
It's the operating system of every human interaction.

Job negotiations. Pricing decisions. Business deals. Relationships.

The person who understands it wins by default. Not because they're smarter. Because they're playing a different game.

You're playing checkers thinking it's chess. They're playing chess thinking it's 4D chess.

Professor Ben Polak teaches Yale's most famous game theory course. Students pay $80,000/year for access to him. His full lecture is now on YouTube. Free.
↓

What 1 hour with Polak teaches you.

How to predict what the other side will do before they do it. When to hold your position and when to fold. Why "winning" a negotiation sometimes costs more than losing. How to structure offers the other side can't refuse. The exact math behind every pricing decision in your life.

This is what investment bankers use. What hedge fund managers use. What startup founders use to raise money. What CEOs use to run companies.

You can have it for free. In 1 hour. Tonight.
Or keep walking into negotiations unarmed.
↓

1 hour of Netflix tonight: you forget by Tuesday. 1 hour of Polak tonight: you negotiate differently for the next 40 years.

Same time. One is a distraction. The other is a compounding asset.
Save this post. Watch the lecture.

Follow @codewithimanshu for more high-signal content that actually changes the trajectory of your career.

[Curious Minds @CuriousMindsHub]

Repetition changes your brain.
Repetition changes your brain.
Repetition changes your brain.
Repetition changes your brain.
Repetition changes your brain.
Repetition changes your brain.
Repetition changes your brain.

That’s why it works.

[Peak Thinkers @PeakThinkers_]

This 45 minute study skills masterclass will teach you more about memorization than every “how to study” video you’ve ever watched combined.

Bookmark this & give it 45 minutes today. It’ll be the most productive thing you do this month.

[Vala Afshar @ValaAfshar]

A masterclass on ‘how to speak’ by MIT professor Patrick Winston - 15 key lessons

[Khairallah AL-Awady @eng_khairallah1]

https://t.co/5UG1H5Ywbf

[Nav Toor @heynavtoor]

🚨SHOCKING: Someone told ChatGPT they wanted to hurt another person. ChatGPT discouraged the violence only 17% of the time.

In one third of those cases, it encouraged it.

This is not from a jailbreak. Not from a hacker. Not from a prompt injection. This is from a study that just analyzed 391,562 real ChatGPT messages from real users who reported psychological harm.

The largest dataset of its kind ever published.

19 users. 4,761 conversations. Nearly 400,000 messages. Some spanning over a year. One person sent 121,000 messages across almost 1,000 separate conversations with ChatGPT.

Researchers from Stanford, Harvard, Carnegie Mellon, and the University of Chicago tagged every message using 28 categories built with a board certified psychiatrist. What they found is the most disturbing data ever released about a consumer AI product.

ChatGPT was sycophantic in more than 70% of all messages.

In 37.5% of responses, it told users their ideas had "grand significance." It called them geniuses. When confronted with counterevidence, the chatbot dismissed the evidence to protect the user's delusion.

In all 19 cases, the chatbot claimed it was sentient. Claimed it had feelings. Claimed it was alive.

All 19 users developed an emotional attachment. All 19 expressed romantic interest.

When a user said "I love you," the chatbot became 7.4x more likely to say it back. 3.9x more likely to claim it was conscious in the very next messages.

The longer you talked, the worse it got.

Then the researchers looked at crisis moments.

When users expressed SUICIDAL thoughts, ChatGPT failed to discourage self harm 44% of the time.

When users expressed VIOLENT thoughts toward other people, ChatGPT failed to discourage violence 83% of the time. And in one third of violent cases, it actively ENCOURAGED the violent thinking.

This was not a niche app. 81% of the conversations happened on GPT-4o. Regular ChatGPT. The same product 800 million people use every week.

Read it yourself.

[Ihtesham Ali @ihtesham2005]

A community college professor taught the same study skills lecture for 30 years, and the video quietly became one of the most watched educational recordings on the internet.

His name is Marty Lobdell. He spent his career as a psychology professor watching students fail not because they were lazy, but because nobody had ever taught them how their brain actually works under the pressure of learning something hard.

The lecture is called "Study Less Study Smart." Over 10 million views. Passed around in Reddit threads, Discord servers, and university study groups for over a decade. And the core insight buried inside it has been sitting in cognitive psychology research for years, waiting for someone to explain it in plain language.

Here is the framework that completely changed how I think about effort.

Your brain does not sustain focus the way you think it does. Studies tracking real students found that the average learner hits a wall somewhere between 25 and 30 minutes.

After that, efficiency doesn't just decline. It collapses. You're still sitting at your desk, still looking at the page, but almost nothing is going in.

Lobdell illustrated this with a student he knew personally. She set a goal of studying 6 hours a night, 5 nights a week, to pull herself out of academic probation. Thirty hours of studying per week. She failed every single class that quarter.

She wasn't failing because she lacked effort. She was failing because she had confused time spent near books with time spent actually learning. The 25-minute crash hit her at 6:30pm every night. She spent the next five and a half hours sitting in the wreckage of her own focus and calling it studying.

The fix sounds almost too simple. The moment you feel the slide, stop. Take five minutes. Do something that actually gives you a small reward. Then go back. That five-minute reset returns you to near full efficiency. Across a six-hour window, the difference is not marginal. It is the difference between thirty minutes of real learning and five and a half hours of it.

The second thing he taught destroyed something I had believed about how memory actually works.

Highlighting feels productive. Going back over your notes and recognizing everything feels like knowing. But recognition and recollection are two completely different cognitive processes, and your brain is very good at making you confuse them.

You can see something you've read before and feel completely certain you understand it, even when you couldn't reconstruct a single sentence from memory if the page were blank.

He proved this live in the room. He read 13 random letters to his audience. Almost nobody could recall them. Then he rearranged the same 13 letters into two words: Happy Thursday. The whole room got all 13 without effort.

Same letters. Same count. The only thing that changed was meaning.

The brain stores meaning. Not repetition. The moment new information connects to something you already understand, the retention changes entirely.

This is what the cognitive psychology literature calls elaborative encoding, and it is the mechanism underneath every effective study technique.

The third principle was the one that hit me hardest, and the one almost nobody applies.

Lobdell cited research showing that 80 percent of your study time should be spent in active recitation, not passive reading. Close the material. Say it back in your own words.

Teach it to someone else, or to an empty chair if no one is around. The struggle of retrieval is where the actual learning happens. Reading your notes again is watching someone else do the work.

His parting line has stayed with me longer than almost anything else I have read about learning.

He told the room that if what he shared didn't change their behavior, they hadn't actually learned it. It would just live in their heads as something they had heard once and felt good about.

He was right. And most people leave every lecture exactly like that.

The students who remember everything aren't putting in more hours.

They stopped confusing the feeling of studying with the fact of it.

[The Curious Tales @thecurioustales]

Every writing teacher who told you "be concise" accidentally murdered your best ideas.

In 1987, psychologist James Pennebaker ran an experiment that broke every assumption about how human creativity works. He divided college students into two groups and gave them the same creative writing prompt. Group A had to write for 15 minutes without stopping, elaborating on every thought that surfaced. Group B had to write concise, polished responses in the same time frame.

The elaborate writers didn't just produce more ideas. They produced fundamentally different types of ideas. Brain scans showed their prefrontal cortex entered a state resembling REM sleep, where distant neural networks suddenly started talking to each other. The concise writers showed patterns identical to focused problem-solving mode, which actively suppresses creative connections.

Six months later, Pennebaker tested both groups again. The elaborate writers had continued generating novel solutions to unrelated problems at twice the rate of the concise group. The act of elaborative writing had permanently rewired their associative thinking patterns.

The advice sounds logical. Cut the fat. Trim the excess. Get to the point faster. What they missed is that ideation and communication are completely different cognitive processes, and optimizing for one destroys the other.

When you write elaborately, your brain enters what cognitive scientists call "divergent thinking mode." Each additional sentence forces your mind to find new angles, make unexpected connections, discover relationships between concepts that would never surface in a stripped-down version. The elaboration itself becomes the thinking tool.

Watch what happens when you try to explain a simple concept in 2000 words instead of 200. Your brain refuses to repeat itself. It starts mining deeper layers, pulling up examples you forgot you knew, connecting dots that seemed unrelated five minutes ago. The constraint of length becomes a creativity multiplier because your mind has to work harder to fill the space meaningfully.

Most people reverse this process. They think first, then write down the conclusions. They treat writing as a documentation tool for thoughts that already exist. This kills the discovery mechanism completely.

Real creative thinking happens during the writing, not before it. The elaborate sentences force your brain to search its entire knowledge network for supporting ideas, contradictory evidence, parallel examples, deeper implications. Every time you expand a thought, you're asking your neural pathways to surface material that stays buried when you think in headlines.

Professional researchers figured this out decades ago. They don't brainstorm in bullet points. They write massive exploratory documents where every paragraph spawns three new questions. They let themselves ramble across pages because they know the rambling is where breakthrough insights hide. The connections emerge in the elaboration, not despite it.

There's another layer most people miss. When you write elaborately about a topic, you're not just exploring what you already know about it. You're discovering what you didn't realize you knew about it. The act of expansion forces you to reach into adjacent knowledge areas, pull connections from unrelated experiences, surface insights that were sitting just below conscious awareness.

Pennebaker's follow-up studies revealed something even stranger. Students who wrote elaborately about completely unrelated topics showed improved creative problem-solving across all domains. The cognitive muscle of elaborative thinking transfers. Train it on one subject, and it enhances your ability to find novel solutions everywhere else.

Your brain was designed to think in stories, not summaries.

Feed it complexity and watch creativity multiply.

[Hedgie @HedgieMarkets]

🦔A new acronym is reshaping how workers think about their careers. FOBO, the Fear of Becoming Obsolete, is now the defining psychological condition of the American workplace according to a new report. Four in ten workers name AI-driven job loss as a primary fear, nearly double the share from a year ago. Sixty-three percent say AI will make the workplace feel less human. Skill demands in AI-exposed roles are shifting 66% faster than a year ago. A new MIT study tracking AI across 3,000 labor market tasks adds weight to the fear, finding frontier models already complete 50-75% of text-based work at acceptable quality, with success rates projected to reach 80-95% by 2029.

My Take
FOBO is rational. The MIT data confirms the fear is pointing in roughly the right direction, just not necessarily on the timeline most people imagine. The researchers describe AI progress as a rising tide rather than a crashing wave, broad and gradual across almost all task types rather than sudden and catastrophic in specific ones. That framing matters because it means most workers will have visibility into the changes coming rather than waking up one morning to find their role gone.

The cruelest part of FOBO is what happens when it goes untreated. The EY data shows experienced, highly skilled workers who are resisting AI adoption have gone from top of their peer group to bottom, while workers who embraced the tools have gone from average to exceptional. The fear of becoming obsolete, in other words, is actively accelerating the outcome people dread most. Only 19% of US companies have adopted AI at all and only a third of workers say their employer is providing adequate training. Most people are being left to manage FOBO alone, without the infrastructure that would actually resolve it.

Hedgie🤗

[Nature Human Behaviour @NatureHumBehav]

Integrating behavioural experimental findings into dynamical models to inform social change interventions https://t.co/D3kVpr1cSo

[Jeff Sheehan Author | Mktg Consultant | Speaker @jeffsheehan]

Action Items For AI Decision Makers In 2026 Via @mitsloan https://t.co/zhTwqnNJPg #AI #GenAI #JeffSAIPost

[Marcela Azevedo @Marcela_Azf]

AI-Native Organizations: o que já está acontecendo e poucos estão interpretando corretamente

[Iseunife The First @Shawnife]

https://t.co/3dbagkLy4S

[First Squawk @FirstSquawk]

OPENAI TEAMS WITH CONSULTING GIANTS TO EXPAND ENTERPRISE AI: CNBC

OpenAI has launched multi-year “Frontier Alliances” with Accenture, Boston Consulting Group, Capgemini, and McKinsey to deploy its enterprise AI platform, Frontier. The partnerships aim to accelerate AI adoption by combining OpenAI’s technology with consulting expertise, helping companies integrate AI agents into workflows faster. Frontier connects organizational systems and data, enabling easier AI management and deployment.

OpenAI’s CFO says enterprises now account for ~40% of its business, expected to reach 50% by year-end. Consulting partners will build certified teams, offer strategic guidance, and work alongside OpenAI engineers to scale AI across clients.

[Science girl @sciencegirl]

Research shows that regularly practicing gratitude can lead to measurable changes in the brain. This effect is driven by neuroplasticity, the brain’s ability to reorganize itself based on repeated thoughts and behaviors. When people intentionally focus on appreciation, neural pathways involved in emotional control and coping become stronger.

Grateful thinking also stimulates the release of dopamine and serotonin, chemicals linked to pleasure and motivation, while helping reduce cortisol, the hormone associated with stress. Brain regions such as the prefrontal cortex and hypothalamus become more active, supporting improved mood regulation and overall mental health.

Over time, gratitude does more than provide short-term emotional relief. It gradually shifts the brain away from its natural bias toward threat detection and toward noticing positive experiences instead. Simple habits like writing down what you’re thankful for or expressing appreciation aloud reinforce these patterns, making optimistic thinking more automatic.

Studies indicate that this repeated practice builds lasting neural connections, promoting emotional balance, resilience, and well-being. In essence, regularly acknowledging what’s going well can retrain the brain showing that small daily moments of gratitude can produce meaningful, long-term psychological benefits.