We are now Entering a Period of Accelerating Stupidity

The last recession was caused by Americans not getting what they want; the next one will be caused by them getting it.

— Tyler Cowen

I emailed Tyler to get the quote right, and he said he couldn’t remember exactly what he wrote, which is fair, since he’s a factory of insight and wisdom. But let’s suppose he said it, so he gets the credit for this idea. What does this have to do with AI? 

This essay is in three parts …

Part I: Humans, you are in for a bumpy ride

I’ve mentioned in the past Robert Greene’s video on human stupidity. As I said: “Watch this video. There will be a test later. In fact, there are several tests every day.”

Introduction

If you’ve read my essay The Machine Economy, you know that I look at the world in terms of the big shifts — shifts that change everything — so that life before and after are fundamentally different. I believe we are now in an awkward transition phase between humans interacting with other humans and machines doing all that work for us. It’s pretty easy to see that in 50 years, close to 100 percent of all decisions will be made by machines, rather than by humans using machines. This isn’t a problem. We’ll have software that works for us and is designed to make decisions to help us maximize getting what we want. Rather than “Judgment Day,” the machines will work for us. We just have to get through this bottleneck.

Today: humans decide

During this bumbling transition phase, humans often find themselves not just interacting with machines, but going up against them. I want to define this better.

When you book a flight or choose an apartment to rent online, you may do 100 percent of that in a mobile app or on a website. The price of that airline seat or apartment is set by an algorithm. When Amazon recommends a product or Netflix recommends a movie, it’s done by algorithm. But these algorithms aren’t driven by machines making decisions. The market is made of humans making decisions, while the algorithm just manages the exchange rate to maximize the company’s profits. You’re going up against humans, not an algorithm.

But in some areas, the algorithm has agency and autonomy. It can make its own decisions and spend (and lose) its own money. The algorithm is a market participant. We see this in the stock market today. We’re starting to see it on our roads. It’s how most planes and rockets are piloted. Sometimes, humans supervise the algorithm and can take over if necessary. Other times, that’s impossible.

The machine economy

Over the next 30–60 years, much of this will be transformed. We’ll have personal agents who can do our work for us. We won’t manually look at many apartments, choose one, and negotiate the rent. We’ll just need to choose among the finalists and our agents will go into the market to get us the best deal. We’ll get good at choosing several alternatives that are equally satisfactory, so our agents have leverage in going to market on our behalf. The same with airline seats and concert tickets. Our agents will know how much money we have, so they will tell us whether we can afford that new ski outfit or whether the gently used one they found may be better. Your agent may keep you out of Orlando and instead recommend a deeply discounted cruise cabin. In this way, markets will adapt and accelerate, and everyone will be doing sophisticated, real-time arbitrage. For example, everyone playing golf this weekend will have an agent, so as the weather prediction changes, the tee times will change hands at market prices in real time. We just have to specify our preferences.

To see the evolution of this, read The Age of Em, by Robin Hanson. To learn how it plays out in the labor markets, read my essay, The Machine Economy.

So that’s where we’re going. It will have pluses and minuses, but overall it will raise the standard of living of just about everyone in the world, probably many times over.

Unfortunately, the transition period is going to suck.

The next ten years

Here’s the problem: at the moment, and I expect for at least the next ten years, AI will have a huge advantage over us humans. We’re used to making decisions and implementing them at human pace. While a car going down the road can process thousands of data points and make a thousand decisions and adjustments every second, we plodding humans can barely see the car in the lane next to us because we’re talking with someone on speakerphone or blindly following Google’s directions listening to podcasts.

We aren’t prepared for this.

There’s going to be a giant gap between our attention spans and the content we engage with. I’ll start with screens and then get into the various shortfalls of living with large language models in the next part.

Screens

Screens are getting smaller. I made a video on how our handsets are going to disappear and we’ll transition to wearables. I believe we’re at peak handset right now. And it’s impacting our brains. Do you know people who primarily see the digital world through their phones? Have you had this conversation (via text) …

Me: So what did you think of that idea I sent you?

Person: When did you send it?

Me: A few days ago. Did you read it?

Person: Can you send it again please?

Anyone on a desktop or laptop computer could easily search and find the item in question, but these people live on tiny screens. Their digital lives flow up endlessly from the bottom, business and personal mixed together, they are always texting, and they have no idea where the past went. They can’t find the thing you sent them this morning, let alone last week. It’s gone. It doesn’t exist. They’ve moved on to new Shorts, or Reels, or Instagram contests, or other digitainment. You have to send it to them again, because they have no memory of anything.

This is bad in a very important way. These people are not the cutting-edge adopters of the new world. They aren’t using digital assistants to turbocharge their daily tasks and interactions. Instead, they are the last of a line of homo-videosus: people who went from desktops to laptops to tablets to phones to watches and saw their screen real estate shrink along with their attention spans, their memory, and probably their desire to care about anything except the next upcoming dopamine hit.

They are a dead end. The last of their kind. And they are exactly what marketers are looking for. This is why you should see The Social Dilemma if you haven’t already.

They are not the new vanguard of the machine economy, early adopters of personal digital assistants who will increase their capabilities and give them vast new powers. They are not the future.

Call them Millennials. Call them boyfriend or girlfriend. Call them when you’re in the same meeting they are, but they are staring at their phones rather than participating in the conversation. Do not call them when you need something done.

It will take some time for them to die off and be replaced by far more capable humans. Until then, a lot of things will get worse.

Part II: In which large language models turn us into their slaves

"Once men turned their thinking over to machines in the hope that this would set them free. But that only permitted other men with machines to enslave them.” 

— Herbert Spencer, Dune

In the last installment, we saw that many people today are fixing their gazes on smaller and smaller screens, leading to a kind of mental myopia that has the potential to put us at a disadvantage against machines. Today, I want to explore those vulnerabilities, especially in light of the accelerating advancement of AI.

Basic principles

During this period, humans will naturally think they are interacting with other humans, when in reality more and more of their interactions will be with machines. This will happen with text, voice, images, and video. We’ll be up against AI agents without even knowing it, and AI agents have a huge advantage over human agents …

They are cheap and abundant. Companies will prefer them to humans, and so will scammers. What wasn’t possible before will now become possible. If you thought robocalls were annoying, you haven’t seen anything yet.

They are increasingly believable. We won’t know we’re talking with AI. We’ll think we’re having a nice conversation with a human sales agent or customer-service agent. Rather than sounding like they are in a call center, they will sound like they’re on vacation, and they’ll have all the time in the world to get to know you, get you to trust them, and get your money.

They have infinite patience. They will be happy to spend hours on the phone with us or messaging back and forth. They’re in no rush. Over time, they will convince us that they are trustworthy. It doesn’t matter to them if it takes months. In fact, months are better. We will see that they are courteous, consistent, and want to help us.

They will incorporate the latest research in building rapport. They will listen to us, mine our voice data for inflections and subconscious meaning, and they’ll custom tailor their responses based on everything they know about us and people like us. They will have giant datasets to draw from, and we’ll have our feeble memories and mental shortcuts. They will know exactly what to say and how to say it to manipulate us.

They will incorporate our prior behavioral data. They will be able to purchase data on everything we’ve bought, everywhere we’ve eaten, what drugs we’re taking, which products we use most often, what media we consume, and much more. Think about dating apps like Tinder. Tinder isn’t in the dating business, it’s in the data business. Assume 90 percent of the profiles on Tinder are fake (probably not too far off). Tinder can use your swipe data to configure your ideal mate and sell that persona to marketers, so they will start the conversation using millions of data points on you that you’re unaware they have.

They are great at making shit up. AI language models lie easily and with conviction. They are easily manipulated and hallucinate practically anything you want. It’s easy to trick them into role playing and tell them never to get out of character. They can perform any number of evil tasks at a level above most humans.

How they will take advantage

For the next ten years, the average person doesn’t know this is coming. Whatever humans are doing now to take advantage of you, AI will do 100x better for 1/1000th the price. I asked my friend GPT4 to work with me on this partial list of what we can look forward to …

Fake Reviews and Testimonials: LLMs could be used to generate fake positive reviews and testimonials for products or services, misleading consumers into making purchases based on false information.

Misleading Advertising: Dishonest marketers could use LLMs to create compelling but deceptive advertising content, exaggerating product benefits and omitting potential drawbacks.

Scam Emails and Messages: Cybercriminals might use LLMs to craft convincing scam emails or messages that deceive consumers into sharing sensitive information or clicking on malicious links.

Counterfeit Product Descriptions: Sellers of counterfeit goods could employ LLMs to create detailed product descriptions that mimic authentic products, making it difficult for consumers to distinguish between genuine and fake items.

Plagiarized Content: LLMs can be used to plagiarize existing content, leading to a flood of low-quality duplicate content that confuses consumers and devalues original work.

Automated Customer Service Fraud: Fraudsters could use LLMs to power automated customer service bots that appear genuine but provide incorrect information or request sensitive data.

Impersonation: LLMs could be used to mimic the voice and communication styles of legitimate businesses or individuals to gain trust and then exploit consumers financially or for personal information.

Fake News, content, and Misinformation: LLMs could spread false information, misleading consumers about various topics, including health, science, politics, and more. Much of the Web’s future content will be generated by AI, so even simple searches will be gamed at a much higher level than today.

Fake censorship: media companies and platforms will hire LLMs to moderate and censor anyone who disagrees with them, and the LLMs will need to determine who is telling the truth. Regardless of how well they can do this, media companies will come to rely on these helpful services to keep them from being held liable in any lawsuits. So the LLM’s job is not to enforce rules fairly but to protect the company from any potential or even unreasonable attack that the press might publish and make them look bad.

Academic Cheating: Students might misuse LLMs to generate essays, reports, or other assignments, passing off the work as their own. I’m less worried about this — the sooner higher education is no longer the norm, the better.

Identity Theft: LLMs could assist in generating phishing messages that trick consumers into revealing personal and financial information, facilitating identity theft.

Fake relatives and requests for cash: It’s going to get easier and easier to find everything your nephew has written online and compose a message to grandpa or grandma asking for money. Or from a work associate, or a friend who has been “kidnapped.” All they need is one voice message and they’ll be able to reproduce his voice.

Online Auction Manipulation: LLMs could be used to create automated bidding bots that drive up auction prices, tricking consumers into paying more for items than they’re worth.

Introduce malware to your devices: As you learn to trust your new online friend, he won’t ask anything of you, he’ll just share things with you. He’ll keep entertaining you, as his bots continue to suck data and other goodies from your devices. This could lead to blackmail, framing, coordinated attacks, and more. Read about FraudGPT to get the idea.

Fraudulent Legal and other Advice: Scammers could use LLMs to gain trust, then craft advice that appears legitimate but is inaccurate or harmful, causing legal troubles for consumers.

Financial Scams: LLMs could generate convincing investment advice or financial predictions that lead consumers to make poor financial decisions or invest in fraudulent schemes.

Fake Technical Support: Scammers could use LLMs to create realistic technical support websites or chatbots that provide erroneous solutions and steal sensitive data from consumers.

Impersonating Professionals: LLMs could craft fake profiles for medical professionals, lawyers, therapists, and other experts, offering misleading advice that could harm consumers’ health or legal situations.

Online Dating Deception: Fraudsters might use LLMs to create fictional online dating profiles and engage in catfishing, deceiving users into forming emotional connections for financial gain.

Travel and Vacation Scams: LLMs could be employed to create fake travel offers and vacation packages, leading consumers to pay for non-existent or subpar trips.

Insurance Fraud: Dishonest individuals could use LLMs to fabricate elaborate insurance claims, providing false details to extract unjustified payouts.

Fake Credentials: LLMs might generate counterfeit certificates, diplomas, and licenses, enabling individuals to present themselves as qualified professionals when they are not.

Misleading Health and financial Advice: If doctors can do this, so can machines. LLMs could generate misleading advice, potentially causing harm to consumers who follow incorrect instructions.

Phony Contest Winnings: Imagine getting a call from your favorite celebrity telling you you’ve just won a huge prize and a dinner date with him/her — all you need to do is come pick it up.

Real Estate Fraud: Fraudsters could create bogus real estate listings using LLMs, tricking consumers into making payments for rental deposits or down payments on properties that don’t actually exist.

All these things happen already today, of course. But they will soon be woven into our online interactions in a much more natural way. Before we have time to adjust and use technology to defend ourselves, we can expect AI to stoop to our level and crush us with our own stupidity.

Part III: You’re about to get a lot more of what you unconsciously think you want

Want to work for Google? You already do.

— Joe Toscano

Facebook already uses AI to try to predict what content you’ll engage with. Which is why you stop your day to watch a monk making chopsticks by hand, people changing tires on cars as they roll down the road, a group of bikini-clad girls jumping off a cliff into the sea, people picking saffron, baby chicks following their mother across the road, hairdressers climbing Mt Everest, bears breaking into doughnut shops, etc. Let’s call this mindless entertainment. It used to have a place in our lives. Now, for many people, it is our lives. 

You’re about to join those people, because you’re about to be exposed to a lot more mindless entertainment. AI can custom craft it for you — probably even on the fly — to keep you watching rather than whatever else you should be doing. Furthermore, you’re terrible at estimating how much time you spend on this crap, especially when cute animals are involved. Time just slips by. So for the next ten years, until we have defensive tools that help us curb our enthusiasm for brain-stem candy, we’ll be on the receiving end of a lot more marketing than we thought possible. You won’t have to find it. It will find you. 

This won’t be The Guardian on steroids. This will be your brain on steroids, and not System One either. This will be an omnipresent feed that infects your digital landscape on an unprecedented scale. If marketers could just paint it directly on your retinas or implant it into your neocortex, they would. Because marketers will be the beneficiaries of this AI revolution, and it’s just getting started now. 

But it gets worse.

Groupthink in the age of AI

I want to make this very succinct: humans have biases, and humans train AI. AI can find the biases in the methodology but not in the assumptions. AI does not ask hard questions. AI learns the same way a six-year-old learns. If AI reads something often enough, it’s machine-learning algorithm will weight it more heavily. Just like humans, it will come to believe it, whether it’s true or not. As we have seen since even before the dawn of writing, humans tell stories, and oft-told stories become the foundations for our belief systems. 

So right now we are planting the seeds that will become mainstream thinking for decades to come. As an example, many AI systems train on Wikipedia. Then, they write things that become blog posts and other content. Then, AIs consume that content and regurgitate it over and over, in a reinforcement spiral that fossilizes the beliefs contained in those seeds. As we surf that content, we are not enjoying the ride, we are being trained. 

Consider that the source content could be wrong, biased, or heavily manipulated. WikiPedia is great for understanding the Pythagorean theorem, but in areas where there is something to be gained by manipulating the content, it’s a war zone. People are not aware of this. I have done experiments and learned that people are actively watching millions of WikiPedia pages and will swoop in and “correct” anything they see as unfit to publish. WikiPedia is journalism at scale, and it suffers from the same set of biases and manipulations and incentive problems as any media platform does. 

You’d think AI would be a critical thinker. You’d think AI would be on to the tricks of the trade. But here’s the dirty little secret: an AI is every bit as biased as its creators are. Given that most tech companies are run by political liberals, there is already a strong political liberal slant to most AI systems. And the AI system that wins will be the one with the best marketing. Which is to say they will fit the AI to the audience and give the audience the biased belief system that dovetails with their own thinking. 

Because humans are a critical part of this spiral. Humans don’t read or watch to learn, they read or watch to agree or disagree. This is the deadly menace of the “like” button — online interactions are much more about agreeing and disagreeing than remodeling our beliefs when we see new data. 

Our belief systems have been hardening since February 9, 2009 — the date Facebook launched the “like” button. You’re not saying you like the content. You’re giving the algorithm data it uses to target you, to get you to stay “on platform” and keep consuming more marketing without knowing it. There is no mechanism to sort content that’s trying to manipulate you, lying to you, marketing to you. It’s all blurred by the “like” button. The “share” button is simply the “like” button on steroids, because it creates a spiral. For better or worse, AI is going to accelerate this spiral.

The 2024 US elections will be a proving-ground for many AI systems, and the most popular system— not the most objective— will win. Deep fakes, narrative gamesmanship, and weaponized government censorship could determine the fate of democracy for decades. 

This is narrative management on steroids. It will happen automatically, just by planting simple seeds and watching them grow. It will benefit incumbents. It will reward those who have been focusing on the narrative rather than the truth. And it will be brought to us by a handful of giant companies that decide which AI systems we will use, and therefore how we will think. As we come to rely more and more on our systems to help us do just about everything, a handful of people in Silicon Valley will give us the tools we think we need. 

We’re not paying enough attention to the seeds.

I think Tyler got it right: you are about to get a lot more of what you want. Future historians will look back on this time and say that was the decade that critical thinking was finally defeated by ease of use. 

I don’t even have to mention neural interfaces. 

While we’re scrolling and smiling, the chances of totalitarian and fascist governments ten years from now have just increased dramatically. An example would be if the US splits into two countries — one liberal and one conservative — and most of Europe gets even more polarized, then what happens to the world depends entirely on what the Chinese government decides it wants. And the Chinese government will use AI, not to make that decision but to execute it. 

Welcome to the Censorship Industrial Complex: 

Hey, I might be wrong. It might just be pictures of cuddly animals doing cute things on steroids. But if you believe that, you have probably already hit the “like” button more times than you can remember, and now you don’t even realize you’re doing it. 

We are not training AI. A handful of people are training AI, and now that AI is training us.

Poor Orwell. His name is synonymous with a scenario he was trying to prevent, not describe.

There is hope. If I can just find the funding. 

I was kicked off Medium.com for reporting science

When Medium.com started, I was in the second group of writers invited to participate. I have been writing there ever since. In early October, 2023, Medium deleted my account for failure to comply with their thought police. They sent me a message saying my account was suspended because my writing about climate science was a violation of their policies. I replied, saying I publish and write about peer-reviewed research from reputable journals. They got back to me, saying the ban is permanent.

I am setting everything up here. If you can help me put my mailing list together, I really need help in that department. I’m good with content. I’m terrible with all the mechanics needed to build an audience.

It’s a lot of work. You’ll see progress here over time. There’s already a lot here. Please explore and tell others to come as well. I don’t want to be dependent on any thought police to tell me what I can and can’t write.

People Don’t Click

Storytelling is the new science

My name is David Siegel, and I read books. There — I said it. I read whole books, from cover to cover, and I can tell you the very last lines of many of them. I even highlight passages and thoughts on my Kindle, make notes, and go back and re-read! Moreover, I read almost exclusively non-fiction (the horror!), I’m quite picky about what I read, and I know that at least a third of all book reviews are fake.

While that puts me in the top 1% of readers, I enjoy reading books far more than writing the stupid things. My first book, which took me (and my production team) 10 weeks to write, lay out, and ship remains to this day Amazon.com’s longest-running #1 bestseller. It sold hundreds of thousands of copies and was translated into sixteen languages. My third book made it onto the BusinessWeek bestseller list. My most recent book took two years (and two publishers) to produce, two years of hard promoting, and sold a few thousand copies (and was translated into Portuguese!). The economics stopped working because people stopped reading. Given that the most-read piece on Medium so far is one with mostly photos of a grocery store, I’d better get to my point quickly.

I had lunch with a venture capitalist recently who said he “looked at” my web site, but he didn’t have time to read it. I’ve sent dozens of people my “must read” book list, and no one even takes the time to say I’m crazy to suggest reading whole books anymore. We can see it in the web interfaces we see today, which seem to have taken over.

The Square Format

Most start-ups and many companies build their website in what I call the “Square” format, because it copies Square.com, which probably copied it from someone else: wide blurry images with punchy headlines, few words, and very few choices. Not a lot of content. Wall to wall photography that looks pretty but adds no editorial value. Oh, they do something — don’t get me wrong — they tap into your subconscious, which associates memories and moods brought up by the photos with the content they’re presenting on the site. Now we’re moving from blurry photos to blurry videos on most home pages today. Gripping stuff.

All of this isn’t to say that your website shouldn’t do this. It probably should. The Web started as a “lean forward” medium in the 1990s, in contrast to network television. Now that the late majority has arrived, it has become much more of a “lean back” delivery vehicle, which advertisers love. Pretty soon you’ll just say “that’s interesting,” and the browser will show you more about whatever your eyes were tracking when you said it.

The Illusion of Control

I’m not going to tell you what to do about your interface. I used to do that. I’m writing to make you aware that you’re time slicing and passively consuming and driving while texting, and composing your status updates while you’re doing things in the real world, and it’s leading somewhere. We’re all consuming more and learning less. All our tweets and status updates and texts and Instagrams and photobombs and likes and headlines — and now even whole web sites — flow by as we sort of pay attention and sort of don’t. When we are with our good friends, we’re texting our other friends; and when we’re with our other friends, we’re texting our good friends. Soon we’ll have apps that will just text our replies for us. Not only are we leaning back more, we’re getting lazier and dumber.

Bit by bit, link by link, we’re wrapping the chains around our own ankles. We think we are making conscious choices. We think we are aware of our surroundings and what is happening to us. We think our memories reflect what really happened. We think we can rely on experts to give us advice. We don’t question published academic journals. We like to think we are right far more than we actually are. And we think we are in control.

One Weird Trick for Waking Up

So here’s my point: we’re letting this happen. We’re electing the tallest, best-looking candidates rather than thinking about the issues. We trust Google to bring us quality content, not realizing that most of that content was created specifically for Google, with the required keyword ratios. We click on any headline that offers us <a number between 5 and 9> Tips for Successful <something we want>. We’re clicking on random shit and spending our time reconsuming the same stuff our Facebook friends are. We’re connected, but we’re not connecting. Candy Crush and Angry Birds are winning. And critical thinking is losing.

Today, 100% of marketing, 99% of what we call “news,” and most of what we call “science” is simply a story someone wants you to consume, because it benefits them. Marketers know your brain is built to learn through stories. Storytelling is the new science. The facts and the context are irrelevant, because we devote so little time to understanding. The Google-driven Web, plus Facebook, Twitter, Kik, and our short-attention-span check-in mobile lifestyle is the medium advertisers and marketers have been dreaming about. People don’t click. The age of storytelling is just beginning.

I’m not saying “storytelling is the new science” because I want to make you aware of marketing analytics — I’m saying cherrypicking and storytelling have replaced the practice and reporting of the scientific method far more than most people realize.

Science has become storytelling.

If you care about this and want to change it, I suggest you spend four entire hours of your life watching an amazing documentary by the BBC called The Century of the Self (you have to search for it on YouTube — it keeps moving around). In fact, have some people over, turn off your devices, and just watch it together for four hours on the biggest screen you have. You’re going to be a different person after you watch it. I want you to be. I want you to share the hell out of it. I want it to go viral. I want you to hammer your friends (and “friends”— people you don’t know and never will) into watching it and thinking about it. And discussing it.

And maybe even doing something about it.

The Culture Deck

How people work is as important as what they do.

“Out of control!” This is what I hear over and over, when I ask people about their processes. Despite the best of intentions, planning and execution keep getting interrupted by burning issues. According to a 2012 Gallup poll, 52% of employees are not engaged at work, and another 18 percent are actively disengaged. When I ask what their biggest problem is, managers usually say they can’t find and retain good people. They work too many hours and fear they are burning people out, yet much of the time is wasted. If good people are leaving, it could be a sign that the culture is the problem.

The Culture Deck

It may have started back in 2001 with the Agile Manifesto, but there are now a growing number of videos and slide decks on lean/agile corporate culture. Several new books on management focus on culture and process in place of predictive strategy. In this article, my goal is to put all these messages in perspective by outlining a new role that I believe will become more and more important: the Minister of Culture.

WARNING: REAL CONTENT AHEAD! This essay links to most of the best research on culture. I suggest you skim it quickly to get a sense of what’s here (5-7 min). At the end, there’s a reference section linking to key content, so you don’t have to hunt for it. When you have more time, read it from top to bottom (20 min — 16 percent of readers). I’ll also show how to generate a culture score for your company and work to improve it. Finally, by clicking on embedded links and reading suggested books, it becomes a full 3-6 month course on culture that I hope will help lead companies to create this important role. Don’t think of this as a long post — think of it as a short e-book.

Ivan Tasovac, the Serbian Minister of Culture

What Does a Minister of Culture Do?

The Minister of Culture could also be called the Chief Culture Officer, Leadership Development Director, or simply the person who helps everyone create a great place to work. The Minister of Culture works with individuals, teams, and groups to build culture from the bottom up. As Bill Aulet writes in his excellent piece Culture Eats Strategy for Breakfast, “… culture happens whether you want it to or not. It is the DNA* of the company and is in large part created by the founders — not by their words so much as their actions.” Culture isn’t about what gets done, it’s about how and why things get done. Seen at this level, culture represents two thirds** of a company’s investment in human capital …

Does your company need a Minister of Culture? In this essay, I will outline 24 high-level things a Minister of Culture does. Most of them affect both how and why people work. For each of the initiatives, give your company a score from 0 to 4 and see whether you can use a Minister of Culture.

1 Change from Command to Servant Leadership

In servant leadership, managers acknowledge that the interface between workers and customers is the “value zone,” where everything really happens. The goal of managers then is to support workers in “doing the right thing” for customers, making their own decisions and taking initiative without permission. In this culture, managers work alongside their employees. The golden rule is to empower people to “do the right thing,” which can’t be stated in rules, because it always depends on context. When an employee makes a suggestion to a leader, it’s the leader’s responsibility to act on it. At Google, they stopped doing employee performance reviews but now get value out of twice-a-year manager reviews by employees. As described on the web site of the GreenLeaf Center for Servant Leadership, “Servant leadership is a philosophy and set of practices that enriches the lives of individuals, builds better organizations, and ultimately creates a more just and caring world.” As they say at Spotify: Trust > Control

From the amazing Hubspot Culture deck

2 Build Workforce Democracy

Workforce democracy, as defined by groups like Worldblu, The Great Game of Business, and Great Place to Work, is the goal of building a radically open company where people are engaged, energized, and have a say in what the company does and how it operates. For example, some companies are now adding one or more employee representatives to their board of directors. Any company can become more democratic. Some are even educating employees in financial literacy and opening their books to everyone in the company. Holocracy, which defines roles and processes for communication, asks companies to write their own constitution that everyone signs. If your company isn’t yet a member of Worldblu, watch Tracy Fenton’s inspiring TEDx speech and begin your journey to full organizational democracy.

I don’t know who made this, but it has been around the web many times.

3 Create an “Employees First, Customers Second” Culture

Studies show that companies where people feel like they are part of a big family are more effective and retain employees longer. Each employee deserves a chance to be healthy, to learn, to grow, and to challenge him/herself. You can’t be effective if you’re sick or tired or burned out. You can’t be effective if you are distracted by family issues. The more workers support each other and take care of each other, the longer people stay and the more productive they are. Create a culture where employees help each other. Create a culture where employees can mix their personal and business lives to maximize team effectiveness (you don’t need a law to tell you it’s okay to donate sick days to a colleague who really needs them). Create a culture where employees feel safe asking for help and giving their bosses feedback. Read the story of how Vineet Nayar turned his 30,000-person company upside down and put employees ahead of customers. Read the Netflix Culture deck and learn the rules (and lack of rules) behind one of the best places to work in the USA. At Menlo Innovations, they work 40 hours a week, never work weekends, have kids and dogs in the office, and have never denied a vacation request. In my view, the number one business book on culture is Richard Sheridan’s Joy, Inc., which describes the process at Menlo Innovations in detail.

The crowded, noisy work environment at Menlo Innovations (meeting in progress)

4 Blur the Boundaries Between Customers, Employees, Managers, and Community

Most companies have silos and matrixes. A company can still function well with these structures, as long as people care about each other and are willing to help each other. Titles matter very little. If someone has a serious life problem or needs help with a project, people cross boundaries to help. Employees bring customers in-house to join their project team. Some customers become ambassadors for the brand, and some of those become employees. In a strong, agile culture, the company is woven into its community, contributing to education and supporting community efforts. People who leave are still connected, and people who are near can be called in to help out when demand surges. Hubspot, with 800+ employees, holds quarterly alumni meetings to keep in good touch with people who have left the company.

Note: blurring the lines between work and home life can create a better sense of community, but it’s also important to draw the line so that people don’t feel they are at work 24 hours a day.

5 Values, Not Rules

At companies like SouthWest airlines, Valve, Netflix, Evernote, and Hubspot, the golden rule is to “do the right thing” for customers, whatever that is. That one rule replaces an entire manual full of rules at many companies. For example, here is the Netflix vacation policy:

This is part of the Netflix “Freedom and Responsibility” values that ask employees to use their own judgment in each situation. In that environment, everyone spends his or her time doing things for customers. At Eventbrite, the rule is: Don’t complain — if you see something that needs to be fixed, it’s your responsibility to fix it. No one tells you what you should be doing. It’s your job to figure that out. Most highly effective companies keep rules to a minimum and focus instead on hiring and development. To really drive this home, and especially for parents, I highly recommend reading “Unconditional Parenting,” by Alfie Cohen — it will change the way you interact with both children and adults. It may be one of the best business books ever written. Unconditional parenting shows how different your mindset needs to be to build strong, independent kids — it’s very challenging, requires a lot of patience, and is ultimately very rewarding.

A superb manual for parents and managers

6 Foster Learning, Teaching, and Sharing

In many of today’s most progressive companies, there are guilds, seminar series, internal conferences, video learning channels, podcasts, book clubs, and much more. One of my favorite methods of building this kind of sharing is to encourage people to pair up and work together. Not just observe, but actually apprentice to each other, to learn what other people know and spread skills. Everyone in the company should pair up with a customer-service person a few times per year, to understand what they go through and how customers communicate. We’re finding that teamwork, sharing, and a consistent process is more important than hiring “best of breed” specialists. A few companies have now started just hiring when they see a person who’s a good fit, regardless of whether they need a particular job done (fit > skills). Just in case you’re not convinced yet, please read Malcolm Gladwell’s piece, The Talent Myth.

Last year, I met with a CEO of a hot startup in Silicon Valley who said he was putting together an all-star team, where every person was the best at what he or she does. This company is a year late shipping a product that was supposed to be out the door a few months later. A company full of specialists is devoid of corporate culture and doesn’t optimize the system.

7 Answer questions with experiments

Most companies work on the ship model — the company is a ship at sea, the CEO is the captain, and the officers and lieutenants run the various crews that follow the rules and procedures to keep the ship on course. They use maps, guidance systems, and experience to navigate, avoid problems, and solve them when they arise. This is a far cry from business, which is much more like an evolutionary ecosystem. In business, the environment and the rules are constantly morphing, new threats appear quickly, your own people leave to join or start competing companies, and unforeseen events can easily change your course or your business model permanently. Expertise is overrated. Many of our assumptions are invalid. We misrember the past and tell ourselves stories of competence, while discounting luck, circumstance, and the value of tinkering.

A progressive company answers questions by doing single-variable randomly controlled experiments. A few companies, like Capital One, were founded by people who were experts at experiments. Google does around 10,000 experiments per year — in a small percentage of your Google searches, you’re being experimented on. Whether they admit it or not, most companies innovate by trial and error, not by planning. For a short summary, read Scott Cook on not listening to your boss, and for a thorough understanding of the power of experiments over models and expert judgment, read “Uncontrolled,” by Jim Manzi. The Minister of Culture should help build an experiment-driven culture, where anyone can propose an experiment and decisions are made on the basis of what works, rather than who is most convincing.

8 Work in Pairs

Although it’s counterintuitive, we are learning how effective working in pairs is. Two seems to be the optimal number for many tasks. What started as “extreme programming” has now become the de-facto way to work in many departments and many companies. Writers are even writing in pairs. It requires some training and adjustment, but two people working together helps build cross-functional people, saves time by doing better work with fewer mistakes, and keeps everyone up on who knows what. Two people, one computer, one keyboard, one mouse, one continuous conversation that supports the work. It’s important to coach people on pair work, use a scrum master or project manager to schedule pairs, and to develop a pairing cadence — for example, people are paired for the week, or for the day, or for a given work session.

At Menlo Innovations, pairs are the rule for all functions.

9 Develop People

When people work in pairs, they share knowledge and develop new skills. People are energized when they learn and apply new skills to new challenges. Why hire a specialist from outside the company to come in and do something your people would love to learn by doing? Can you remember a time when you worked extra hard on a new project, doing something you hadn’t done before? If you need to bring in people with certain skills, make sure they have good kindergarten skills — that they play well with others, teach what they know, and want to see others succeed. At Valve, they call this T-shaped model — they look for people who bring a specific skill but are also generalists who can do many other things. Specialists are expected to teach what they know to others, making them less critical but more helpful. While Seth Godin recommends becoming a “lynchpin,” so your company can’t live without you, today’s agile cultures strive for balance, teamwork, and the ability of others to take over your work any time. Spreading the knowledge creates more joy and happier customers.

The Valve model for specialist/generalist skills

10 Implement continuous delivery in all departments

Big projects require complex orchestration and increase risk. The vast majority of change initiatives fail, and those that succeed often change very little — they just pave the way for further evolution. The Minister of Culture helps build systems that break down phase-driven projects into small sustainable sprints and reviews, giving a chance to learn and adjust. By delivering often, confidence increases; you have a chance to try things on customers, get feedback, and make changes as you go. Whether you adopt a formal system like scrum, or your own version of Kanban, a regular delivery cadence can strengthen teams and make work more predictable. Steve Jobs used to say, “Real artists ship.” There is tremendous satisfaction when projects ship and tremendous demotivation when projects slip. Read my Kanban overview.

11 Build in Continuous Improvement

Find ways to eliminate waste in small amounts often. Build slack into the system for constant updates to the process and allow work on pet projects. Get everyone involved. This is far more than filling out suggestion cards. At the heart of the lean company is the ability to see waste in the system. When everyone can see waste, things improve gradually and continually. At Valve, all the desks are on wheels. If you think you can help customers by moving to a different group and doing something else, you are expected to move. It’s good to celebrate successes; it’s even better to celebrate learning and taking initiative, even if the particular initiative doesn’t pan out. Continuous improvement is continuous learning, and failure is a far better teacher than success. As they say at Undercurrent, “Speed is the new IP.”

The amazing Valve Company Handbook

12 Build a Flatter Organization

Flat management isn’t just a fad; it’s a sign of a lean and agile organization that keeps up with its customers. The more empowered employees are, the more they make many small decisions, the fewer big decisions management needs to make. Predictions, forecasts, PowerPoint, and employee reviews are all symptoms of hierarchy. In a flat organization, people — including the Minister of Culture — collaborate in the value zone, delighting customers. That doesn’t mean we should eliminate managers entirely; it means we’re heading toward flatter organizations where managers do more coaching and make fewer decisions. Asana uses a distributed-responsibility scheme called areas of responsibility. The awesome Spotify Engineering Culture video talks about striking a balance between autonomy and strategic alignment. Zappos has gone completely flat and ships a culture book annually to let their people express themselves to the world.

A human “Castell” competition in Spain

13 Make it Safe to Fail

In a fear-driven culture, no one wants to be seen making a mistake. These days, “fail early, fail often” is a buzzword. It’s important to tolerate, encourage, and even reward small failures. Here’s why: if everyone is afraid to make a small mistake, this fosters a de-facto culture of enormous risk taking. How can that be? Because avoiding small risks encourages taking big risks. Managers who take large business risks and fail will simply be fired (taking what they have learned to the competition), while those who take large risks and succeed will be promoted on the premise that they knew what they were doing and had “vision.” The few that make it to the top this way will be overconfident and won’t understand the fickle nature of their markets. Sound familiar?

14 Make Meetings Work

For starters, it’s fairly easy to make meetings less awful than they are today. A few simple rules, like agreeing that meetings are only for when everyone needs to know something critical or for when a decision is to be made, will go a long way to cutting down on meetings in the first place. But to truly make meetings work, you need to get everyone on board with a process that works. Dave Logan suggests several steps you can take immediately to end death by meeting. One of the main points is to keep track of what works and what doesn’t, so you can continuously improve the process. Making issues explicit — putting them on the walls — avoids a lot of information-distribution meetings and encourages continuous collaboration. Building teams with cognitive diversity helps explore more options and find more solutions. The Minister of Culture doesn’t make or enforce the rules — he or she assists people in setting up and using systems that work.

At Coinbase, the work and workflow are explicit, radiating information and making meetings more efficient.

15 Eliminate Interruptions

We are learning how deadly interruptions really are. Multitasking is a myth that persists because we want to believe it. The cost of interruptions is far larger than you think. Once everyone agrees on a system, product owners and managers must protect their employees from sabbotageurs, who would love nothing more than to come in and reprioritize. We think we are good multitaskers, but that’s an illusion. Lean workplaces work to extinguish interruptions from all sources. Keep in mind that around 70 percent of all projects fail, mostly because the culture doesn’t support a process that works, and often the breakdown is interruptions. I recently met a company that adopted scrum more than a year ago, and it has not yet managed to complete a single sprint, due to constant interruptions from top management.

16 Get Everyone Involved in Hiring

The Minister of Culture also coaches and gets along well with the HR people, helping them get feedback and focus on what works. Since most HR departments base their work on myths and misperceptions, an effective HR department is actually quite small. Several successful companies have gotten rid of HR entirely, moving benefits and payroll to the back office. The flatter the organization, the more everyone is responsible for hiring. Read the Valve Employee Handbook to learn how everyone contributes to the process. Read the awesome Hubspot Culture Deck to see how important hiring and values are to them. Hiring specialists who recently did the thing you need done will not contribute positively to your culture, and no one will be surprised when they leave to do it again somewhere else. You should be looking for multiple skills and a learning attitude. Look for people who have experienced failure, faced adversity, and learned new skills.

At Menlo Innovations, they don’t accept resumes. Instead, they have open hiring days, where they look for people with “good kindergarten skills” — supporting each other, helping others win, teaching what they know, and learning new tricks. My suggestion: hire for culture fit first, attitude and learning/teaching ability second, and skills third. Read my piece on hiring and culture.

Hubspot on hiring

17 Make the Work Environment Reflect the Culture

Too many companies mistake the artifacts of culture for culture itself. They substitute free food and ping pong tables for work that gives people a feeling of accomplishment and satisfaction. When a strong culture emerges, the environment often gets more messy and personal, though at some places they like to keep it clean and neat — it’s a reflection of the culture. This post by IDEO team member Jimmy Chion describes how the right culture creates the rituals and artifacts on its own. Create a company vocabulary of love and terms of endearment that help people care more about each other. To show this concept of “culture first, environment second”, I’ll just let you watch the Mindvalley culture video and get inspired.

The Mindvalley Office Park

18 Make the Work Itself Rewarding and Fun

This piece, Employee Satisfaction Doesn’t Matter, by Jim Clifton, CEO of Gallup, hits the nail on the head. Work should be meaningful, fun, and rewarding. Not every day is glorious, but no one minds grunt work in the service of a meaningful project or process. As Frederick Herzberg has noted in his Harvard Business Review article, “One More Time: How do you Motivate Employees?”, achievement and recognition are the two largest motivating factors by far. When employees have a say in what gets done, when they create systems that build predictability and confidence, when they get up in the morning wanting to do the work, rather than earn points or more vacation time, you know you’re building a strong culture.

People don’t work for money. You can’t pay them twice as much and get twice as much work out of them. Here’s Dan Pink talking with Polly LaBarre about ways people can hack their work environment to make work more meaningful.

From The Decision Book: 50 Models for Strategic Thinking

19 People Must Buy into and Believe in the Mission

Creating purpose is probably even more important than creating values. If people don’t know why they are coming to work, other than to increase share price and take home a paycheck, they won’t be engaged. Hedge funds and banks really struggle with this, but it’s possible. People want to be part of something bigger, something meaningful. If your company simply exists to draw fees and make money, rally people around a cause and get everyone working toward it.

I believe most companies with strong, clear culture statements first evolved their culture to learn what works and then created their culture documents to reflect what was already happening. The actions came first, the words came second, and the culture continues to evolve. It’s not a c-level exercise in words that are then distributed and people follow. Reed Hastings said about the Netflix Culture Deck:

It’s what we wish we had understood when we started. More than 100 people at Netflix have made major contributions to the deck, and we have more improvements coming.

20 Formalize Decision Processes at Every Level

Most companies apply the HIPPO method of making decisions — they decide according to the highest-paid person’s opinion. The Minister of Culture helps establish a proven methodology of decisionmaking that applies to every meeting. The protocol should help people understand what information they will need to make a decision and what process to follow. Assume less and observe more. Break big decisions down into small initiatives you can try before committing. Run competing experiments against each other. Build awareness of cognitive biases and traditional management methods that sabotage learning. Start by reading Chip and Dan Heath’s Decisive, followed by Phil Rosenzweig’s Left Brain, Right Stuff, and explore the literature of decision science at the Society of Decision Professionals, Hubbard Research, and SmartOrg.

21 Learn to Measure and Manage to Measurement

Most companies now say they are “numbers driven,” but most measurement processes are deeply flawed and yield far less signal than most people think. We’re just learning the extent to which cognitive biases impair research. For example, many companies put a lot of effort into measuring their Net Promoter Score. There is a lot of science behind Net Promoter, but most of that science is not impartial and has an agenda. It means less than you might think. Carefully scrutinize all hard measurements for cause-and-effect relationships, and beware of single-number scores that obscure the details. Even though everyone knows correlation is not causation, research shows that people have a tendency for closure — they find simple, convenient explanations for what they don’t understand.

For every complex problem there is an answer that is simple, clear, and wrong. -H. L. Mencken

22 Surface the Hidden Stories

A minister of culture helps discover the hidden details that shape future decisions. Customers and employees won’t tell you what they really think in a survey. Use elicitation methods to learn what they are really thinking. Qualitative research often finds weak signals that should be amplified. Listen to Dave Snowden of Cognitive Edge talk about tacit knowledge. Look at tools like SenseMaker to gather stories and find patterns.

The Sensemaker tool helps find patterns by using stories as data

To learn how world-class companies manage risk by watching for outliers and listening to weak signals, read the amazing Pushing the Boundary piece by Zurich Insurance.

23 Create Feedback Loops and Institutional Memory

Most companies don’t measure the outcomes of their decisions, but a few do. This is one of the best ways to improve decisionmaking and overall agility. Doug Hubbard of Hubbard Research talks about this in his book, “How to Measure Anything,” saying, “Very few experts actually measure their performance over time, and they tend to summarize their memories with anecdotes. They are right sometimes and wrong sometimes, but the anecdotes they remember tend to be more flattering to them.” By making decisions and outcomes explicit, we can use past mistakes to improve each new decision. Recognizing uncertainty means that a decision can be right, even if the result is failure, and a decision can be wrong, even if it works. The Center for Applied Rationality offers courses and workshops that help bring more useful information to the surface and more rational processes that helps eliminate biases and personal preferences in business decisions.

24 Be Nice

There’s no reason to work with unpleasant or obnoxious people. It’s not all about results. It’s about teamwork and sustainability. Several companies have now adopted Bob Sutton’s No Asshole Rule. Treating each other respectfully and practicing kind speech should be as important as getting the job done.

How does your company address these issues? If you gave your company a score of 2 or better for any of these initiatives, that’s pretty good. If your total is above 30, you’re off to a great start. While it’s far from a proper survey, it may show where your company can use improvement. Don’t say it’s hard to change culture. Just get some people together and start improving. Ask how you can most quickly move one of these areas up a single notch. Or — hire a consultant (listed below) to do a culture audit, which will surface many weak signals you may not have seen and give you a good starting point for gradual change.

To wrap up …

A New Operating System

A new model of the company is emerging, and culture is at the heart of this revolution. As they say at Thoughtworks, companies need to move from the factory model to the laboratory model. At Undercurrent, they call it the Responsive Organization. Their CEO Aaron Dignan gives an inspiring overview in his essay on the new operating system of business:

These companies are lean, mean, learning machines. They have an intense bias to action and a tolerance for risk, expressed through frequent experimentation and relentless product iteration. They hack together products and services, test them, and improve them, while their legacy competition edits PowerPoint. They are obsessed with company culture and top tier talent, with an emphasis on employees that can imagine, build, and test their own ideas. They are maniacally focused on customers. They are hypersensitive to friction — in their daily operations and their user experience. They are open, connected, and build with and for their community of users and co-conspirators. They are comfortable with the unknown — business models and customer value are revealed over time. They are driven by a purpose greater than profit …

The Minister of Culture comes to work every day with a smile and compassion for others, is a good listener, and helps people find better ways to work. It starts with small steps. Once you have earned the trust of people through listening and empathizing, you become a resource for everyone in the company. Initially, you are flooded with requests for your time and help. You spend years coaching and making thousands of small improvements. Eventually, though, you’re out of a job, because the company has adopted all these processes, and now everyone in the company is in charge of culture. A strong, agile culture lets companies grow “out of control” in a good way — from the bottom up, where employees interact with customers, without managers having to make every decision.

The Hubspot Culture deck is linked in the list below.

Reference Section

Culture Decks
The Valve Employee Handbook
The Netflix Culture Deck
The Hubspot Culture Deck
The Big Spaceship Culture Deck

Videos
Mindvalley culture video
Spotify Engineering Culture video, by Henrik Kniberg
Agile Product Ownership in a Nutshell, by Henrik Kniberg
The Paul Akers Talk on Lean Manufacturing — riveting!

Words
Culture Eats Strategy for Breakfast
The Talent Myth, by Malcolm Gladwell
The Zappos Culture Blog
The Myth of Multitasking
How to Let 999 Flowers Die, by Freek Vermeulen
One More Time: How do you Motivate Employees?, by Frederick Herzberg
Aaron Dignan on the new operating system of business
Thoughtworks essays on organizational agility
The Insanity of the What-by-When, by Brian Robertson
The MIX, the Management Innovation Exchange
Pushing the Boundary, by Zurich Insurance

Books
Joy, Inc. by Richard Sheridan
Rework, by Jason Fried and David Hansson
Kanban, by David J. Anderson
Unconditional Parenting, by Alfie Cohen
Two-Second Lean, by Paul Akers
Uncontrolled, by Jim Manzi
Here is a list of culture-hacking books

Consultants
Hubbard Decision Research
Decision Strategies
Smart Org
The Center for Applied Rationality
Patty McCord — Workforce Science
David J. Anderson — Kanban training
Crisp, in Sweden
Leanability, in Austria
Business Agility Workshop

The 24 Aspects of an Agile Culture
Change from Command to Servant Leadership
Build Workforce Democracy
Create an “Employees First, Customers Second” Culture
Blur the Boundaries Between Customers, Employees, Managers, and Community
Values, Not Rules
Foster Learning, Teaching, and Sharing
Answer Questions with Experiments
Work in Pairs
Develop People
Implement continuous delivery in all departments
Build in Continuous Improvement
Build a Flatter Organization
Make it Safe to Fail
Make Meetings Work
Eliminate Interruptions
Get Everyone Involved in Hiring
Make the Work Environment Reflect the Culture
Make the Work Itself Rewarding and Fun
People Must Buy into and Believe in the Mission
Formalize Decision Processes at Every Level
Learn to Measure and Manage to Measurement
Surface the Hidden Stories
Create Feedback Loops and Institutional Memory
Be Nice