SiMPL #011 Decoding Everyday Decisions Part 2: Why We Make Them (and Justify ’Em After)
Unpacking the Biases and Rationalizations Behind Our Daily Choices
Last week, we explored decision hacks for everyday choices, whether you’re scrolling through Netflix or tackling a home remodel. This week, let’s dive into the “why” behind our decisions and how we skillfully justify them afterward. Spoiler alert: we all have biases, and we’re experts at rationalizing our choices to make them seem perfectly reasonable.
Quick question: how many decisions do you think you make in a day?
a) 35,000
b) 250
Option B sounds realistic, right? Well, that’s only the average number of times you decide on food! The actual average? A whopping 35,000 decisions a day. But more on that later…
What’s Behind This Reasoning?
A decision is usually a basic process. Stephen Carter, in Decision Making Deconstructed, describes it simply: we start, make a snap judgment, then rationalize that judgment.
It goes something like this:
Begin: I’m hungry.
Snap Judgment: Let’s get hot buffalo wings.
Rationalize: Clearly, it was the best choice! (Spoiler: it wasn’t.)
Step 1: The Beginning
So, how does it all begin? It depends on your level of engagement. Are you fully engaged, semi-engaged, or just indifferent? The way we approach decisions varies with our engagement.
Let’s test that theory: what’s my go-to comfort movie? (Hint: regular readers might already know.)
Today, in our hyper-connected world, people often hover between semi-engaged and unengaged. Take politics, for example. Here are three ways people might sum up the U.S. election:
A) Trump is pro-business, while Kamala is pro-freedom.
B) Trump is campaigning in unlikely Republican states, while Kamala sticks to strategic ones.
C) Kamala supports women and the LGBTQ+ community, while Trump mainly appeals to men.
D) Wait, when is the election again?
If you chose A, you might be unengaged. B is for the hyper-engaged (like me), C is semi-engaged, and D … well, I get it. Politics has made a lot of us numb.
It’s like my reaction to reggaeton or pop artists—people talk about it, but I barely notice. No stress, no mental fatigue; it doesn’t affect my decisions at all.
But when you’re hyper-engaged, you know exactly what you want. The decision is easy or even pre-made. For instance, if I’m shopping for a phone, I already know which model I’ll buy.
The problem lies with the semi-engaged crowd, where two options weigh equally, making the choice exhausting.
Imagine a Super Bowl BBQ at a friend’s place:
simplnews.com superbowl BBQ engagement
• Hyper-engaged: Knows all the stats, every team’s history.
• Engaged: Knows and enjoys the game, but isn’t a fanatic.
• Unengaged: Is more into the snacks and halftime show, asking questions like, “Who scored?” or “Is that your team?”
• Semi-engaged: Feels the pressure to know as much as the super-fans, wanting to cheer but unsure if Taylor Swift’s boyfriend’s team is the right choice!
Step 2: Judgment
This is where our biases and motivations come into play. Judgments rely on three factors (introduced in part 1):
• Frequency: How often have you done this?
• Complexity: Is it easy or difficult to accomplish?
• Novelty: How new or intriguing is it to you?
Take making pizza. Ever tried it? Kneading, stretching, shaping the dough, tossing it in the air, adding toppings, and then getting it in and out of the oven without burning it—it’s tough! But for a seasoned pizzaiolo, it’s second nature. They do it frequently, have mastered the complexity, and aren’t daunted by novelty.
Some call it “beginner’s luck,” but it’s actually the Dunning-Kruger Effect: confidence grows with experience. As beginners, we think we’re better than we are; as we gain expertise, we realize how much we still don’t know. Here’s a cool video that explains it better than I can.
Step 3: Reason (Bias & Rational)
Every decision has a “why.” Often, we’re unaware of it, but it’s there. The surrounding conditions shape our choices as much as our conscious reasoning. For example, the Netflix choice, explored in part 1, depends on factors like:
• Are you tired?
• Are you comfortable?
• How much time do you have?
• Who’s with you?
No choice is a cold calculation; it’s a mix of emotions, morality, and logic, creating biases we may not even notice. And when we finally make a choice, we use rationalization to justify it afterward.
A study by Cornell University found that we make an average of 35,000 decisions a day—226 of them about food alone! It’s no wonder decision fatigue kicks in. To keep from getting overwhelmed, we rationalize. Take my recent 3 p.m. coffee as an example—I convinced myself I needed it to finish this newsletter. Rationalizing helps us cope with reality without overthinking every tiny choice.
Gif by friends on Giphy
Picture yourself being consciously aware of all 35,000 choices you make each day, along with the ripple of consequences that follow. That would be overwhelming! Rationalization is a mental shortcut, letting us move forward without getting stuck.
And yes, consequences are a huge part of decision-making. Every choice we make has its own ripple effect, shaping our lives in ways big and small.
Giphy
Imagine a friend hands you a movie ticket, no details given, and you decide to go with it. You settle in, popcorn ready, and the movie begins. Suddenly, you’re watching a guy—a total maniac—wreaking havoc, tearing through the city based on things like ethnicity, car taste, career paths, even fashion choices. Public property is getting trashed, a hotel’s under siege, chaos everywhere. You’d probably leave thinking, “Well, that was one intense slasher flick!”
But now, add one small scene: those same people kill his puppy—the very one his late wife gave him. Suddenly, his rampage isn’t random; it’s personal. Now you’re not just watching—you’re rooting for him.
Gif by johnwick on Giphy
Yep, you guessed it: John Wick. All it took was one scene, and we empathize with his choices because we understand his motivation—grief, love, revenge. It’s a reminder that empathy and rationalization add layers to our decisions, whether it’s rooting for a fictional antihero or just picking what to watch on a Friday night.
In Power and Prediction, authors Ajay Agrawal, Avi Goldfarb, and Joshua Gans argue that during COVID-19, decisions led by AI might have resulted in fewer deaths and less economic impact. Our responses were heavily influenced by fear and the comfort of familiar solutions, even when the pandemic demanded new approaches.
Machines, however, lack this bias and just follow the data—another difference between AI and human decision-making, which I’ll explore in a future newsletter.
In Short: Reason and Rationalization
Every decision hinges on two moments:
Reason: Why we make the choice.
Rationalization: How we justify it afterward.
Now, Story Time: My Dunning-Kruger moment
Back in 2020, during the COVID-19 lockdown, I found myself coming off a high-intensity job. I hadn’t taken a real vacation in years, mostly filling my time with work-related tasks. Sure, I’d find moments to cook, BBQ, or bake bread, but I wasn’t truly present.
For years, I’d been living the entrepreneur’s life, and if you know any entrepreneurs, you’ll get this: it’s like a benign disease. The entrepreneurial bug changes your mindset, like taking the red pill in The Matrix. Once you’re in, you see problems and solutions everywhere and never quite go back to “normal.”
During that time, I had to prioritize like never before. I was responsible for taking care of my grandma and auntie, and their well-being was infinitely more important to me than gossip about tardiness or minor workplace drama. Getting my job done was way more important than fixing self-made problems that didn’t affect clients. In fact, understanding my clients’ needs became the best part of my day, and I still love that part.
Before this, my last big project—probably one of the largest I’ve ever taken on—was as a data consultant for a presidential campaign in Panama. I learned a lot about how political parties can move and convince hundreds of thousands through complex marketing strategies. But let me tell you: those people know how to create drama to feel useful. They practically thrive on it! I was behind the data, so I didn’t get a break. If someone needed urgent charts or uncovered new data to correlate, I was called in, no matter the hour. In hindsight, I think I did it for the passion for data, since I wasn’t exactly paid that well, haha.
(Here’s a little wisdom for you: Politician Drama Queens are the ultimate Drama Queens!)
When the campaign wrapped up in mid-2019, I jumped straight into a managerial role at a bank, leading the transformation department in banking processes and continuous improvement. There was no rest. I started the day after Election Day. Around 1 or 2 a.m., I got picked up from the campaign’s operational center. The president I’d supported won, so celebrations were kicking off, but I had to rest because my “real” job was starting in the morning. I was going after financial stability after years of underpaid consulting and entrepreneurial debt, with responsibilities weighing on me.
I felt lucky in that job. My boss is still a friend, my team was great, and we worked hard—typically more than 10 hours a day, juggling transformation committees, regional projects, audits, you name it. And I even got to “play” with robots! One of my supervisors had an automation project with RPA that I helped bring to life. Coming from my entrepreneurial run, working at the bank felt like a breeze. But it cost me a lot.
I’d become so immersed in my “job life” that I barely hung out with friends or saw my girlfriend, who, miraculously, I convinced to marry me! I was taking calls on the way to dinners, in the grocery store, and even working Sundays to nail that perfect presentation for the board of directors.
Then COVID-19 hit, and everything stopped. Work-from-home orders meant things slowed down. I finally had time to read the long sagas I’d been wanting to—The Lord of the Rings, all the Dune books (yes, all of them), Cien Años de Soledad (One Hundred Years of Solitude), and even binge-watch Friends and The Office with my wife and brother-in-law.
At that point I decided to learn a new language, but as I mentioned in a previous newsletter, procrastination did its play.
And this is when I had my Dunning-Kruger moment.
I was scrolling through the marketplace when I spotted it—a listing for a guitar. I’d always wanted to learn, so I thought, why not? Snap judgment made, I grabbed it. It was a cheap blue Squier, but to me, it might as well have been a Fender Stratocaster.
My First guitar, Blue Used Squier
Stage 1: The Confident Beginner (with 0 Experience)
I started out with YouTube tutorials, strumming along to Bob Marley and Tom Petty songs. They were slow enough that I had time to think about each chord, carefully placing my (very stiff) fingers in the right spots, one at a time. (Big thanks to Marty from YouTube—my first guitar teacher! If you’re learning guitar, seriously, check him out).
After just a couple of weeks, I was brimming with confidence. I even “learned” Iron Man by Black Sabbath. And by “learned,” I mean that in some distant universe, it sort of sounded like the song. But hey, I felt unstoppable!
Stage 2: Downfall to Reality—Confidence Breaks
Feeling like I had mastered the basics, I ambitiously took on One by Metallica and Fear of the Dark by Iron Maiden. I was convinced this was the next step in my journey. Months passed, and I played the same riffs on repeat, trying to nail them. My confidence? Through the roof.
Then, one day, my wife—out of love, or maybe just to get a break from hearing the same riffs over and over—surprised me with a guitar lesson voucher for our anniversary. So I went in, feeling pretty proud of myself. Ten minutes into my first lesson, though, my teacher took me down a few notches. As he started breaking down basic technique, timing, and theory, it hit me: I knew… nothing.
The Reality Check Moment
I was staring reality in the face, and, man, it was humbling. My tempo was shaky, my technique was raw, and let’s just say I wasn’t even tuning my guitar properly. But here’s the thing: that feedback was priceless. My teacher didn’t just tell me what I was doing wrong; he showed me the exercises I needed to strengthen my fingers, guided me through understanding the notes, and helped me find the right tempo.
Those small adjustments and consistent practice were eye-opening. With each lesson, I improved bit by bit, gaining just enough skill to see how far I still had to go. And with every improvement, I learned more about the true journey of becoming a musician—and how overconfident my beginner self had been.
Stage 3: The Hard, Long, Metronome-Based Road to Knowledge
Now, years later, I’m still on this journey, and it’s as challenging as ever—but in the best way. Every practice session brings fresh exercises and new feedback, keeping me on my toes. I’ve learned to rely on my metronome for almost every exercise, building consistency and control. Trying out different genres and pushing my dexterity has been the slow, steady climb that real growth requires.
Music is a humbling art. It reminds you that there’s always more to learn, no matter how far you think you’ve come. If you’re interested in guitar lessons, let me give a shoutout to my teacher, Carlos Owen, who was just named the Best Guitarist in Panama in 2024. You’ll be in great hands—here’s his instagram … and a video if you want to check out his!
The journey may be endless, but every note along the way makes it worth it.
So, How Do You Make Great Decisions?
Honestly, there’s no formula. We’re all different, with unique biases and environments. But if we learn from the Dunning-Kruger effect, we can be more intentional. Luck, after all, is just when preparation meets opportunity.
Or as Thomas Jefferson said:
❝
I’m a great believer in luck, and I find the harder I work, the more I have of it.
Thomas Jefferson
Wait a minute… then how do machines make decisions?
In our upcoming newsletters, we’ll dive into a new perspective: How do machines make decisions? Stick around as we unpack the fascinating world of AI decision-making and explore how it compares—and contrasts—with our own human processes.
Book Recommendation: Do Androids Dream of Electric Sheep?
You may know this book better by its cinematic title, Blade Runner. After finishing I, Robot, Amazon—the all-knowing AI nudging us towards our next purchase—recommended Blade Runner the book, and I thought, why not? This novel is a fantastic piece of sci-fi, going much deeper than the cyberpunk themes of the film. It dives into the twisted journey of Rick Deckard, a bounty hunter caught between his mission and his own humanity. Dick’s writing plants seeds of doubt not only in Rick’s mind but also in the reader’s: Is Deckard truly human? And just when you think you know, the story throws in new twists and side plots that make you question everything.
There’s a strange part where Rick tries to prove his humanity by, well, having a fling with an “andy.” Its a book about Rationalizing in a world where Androids are getting harder to distinguitsh from humans. Rick is attempting to convince himself he’s still human, which shows how messy our self-justifications can get! All the while, animals—rare and precious—are valued more than the androids he’s hunting, adding yet another layer of complexity.
So, what’s it all about? Same as the Movie?… well somehow…
Let’s dive into Philip K. Dick’s Do Androids Dream of Electric Sheep?, the novel that inspired Blade Runner—that iconic movie with Harrison Ford and directed by Ridley Scott (yes, the same visionary behind Alien and Gladiator). Scott’s take is undeniably cool and haunting, but Dick’s novel goes even deeper into the moral quagmire of identity and humanity. I’d say Dick, like Scott, was a true futurist, probing questions that still resonate today.
By Harry Sehring - http://www.betweenthecovers.com/btc/reference_library/title/1014273, Public Domain, https://commons.wikimedia.org/w/index.php?curid=153619752
The book takes readers on an intense exploration of what it means to be human—and the messy decisions we make to justify our existence. In his work as a bounty hunter, Rick Deckard begins to spiral into self-doubt after discovering that another hunter, whom he saw as an equal, is an android, yet doesn’t even realize it. This revelation plants a gnawing doubt in Rick, forcing him to question his own humanity and make impulsive choices in an attempt to convince himself he’s different from the “andys” he hunts.
In the story, Rick tries to justify his own humanity through a series of impulsive, sometimes absurd decisions—like buying a goat or even attempting a relationship with an android. This internal conflict, where he oscillates between self-doubt and self-rationalization, is one of the story’s most compelling aspects. As Dick writes, “Maybe he’s right, Rick thought as he watched the goat being unloaded from the truck. I’m buying my way into the human race, again.”
Do Androids Dream of Electric Sheep? is a gritty reminder that our identities are fragile as fuck—shaped as much by the choices we make as by the doubts we harbor. If you’re intrigued by what really makes us human, this book is a must-read.
SiMPL’s Weekly World Wrap-Up (Nov10th /24)
ChatGPT Goes Pop.. is now Chat.com
OpenAI just took a bold step in branding by acquiring Chat.com, redirecting users directly to ChatGPT. Originally registered in 1996, Chat.com is a rare gem in the domain world. HubSpot’s co-founder, Dharmesh Shah, reportedly bought it for $15.5 million last year, making it one of the biggest domain sales to date. Today, Shah confirmed on X that he sold the domain to OpenAI, possibly in exchange for OpenAI shares.
As of now, Chat.com serves as a redirect to ChatGPT rather than a full brand shift. But this acquisition highlights OpenAI’s strategic focus on prime digital real estate.
For full details here
The Bet of the Wealthiest
According to Bloomberg, the world’s top 10 wealthiest individuals saw a combined increase of $64 billion in their net worth recently, highlighting the ongoing concentration of wealth among a select few. This dramatic boost raises questions about the economic and social factors that enable such rapid financial growth, especially during times of global economic fluctuation.
Want to know who these individuals are? Check out our in-depth article at simplnews.com
Talking AI, I asked Chat (GPT is now Chat.com) about the election check out its answer:
In the 2024 U.S. presidential election, Donald Trump secured a second term, defeating Vice President Kamala Harris. This victory marked a significant political comeback, as Trump became the first president since Grover Cleveland to be re-elected after a previous electoral defeat. (USA Today)
Trump’s campaign resonated with voters concerned about economic issues and immigration policies. He achieved key victories in battleground states such as Pennsylvania, Georgia, and Wisconsin, surpassing the 270 electoral votes required to win the presidency. (USA Today)
Vice President Harris conceded the election, urging her supporters to accept the results and continue advocating for their values. (The Wall Street Journal)
This election also saw significant financial contributions from prominent figures. Notably, Elon Musk, CEO of Tesla and SpaceX, donated nearly $75 million in support of Trump’s campaign over a three-month period ending in September. Musk’s involvement extended beyond financial support; he actively participated in rallies and utilized his social media platform, X, to endorse Trump. (Business Insider)
Musk’s support for Trump aligns with his business interests, as his companies have substantial dealings with the federal government. For instance, SpaceX has secured contracts worth billions of dollars from NASA and the U.S. Space Force. Additionally, Tesla has benefited from federal subsidies aimed at promoting clean energy. (Business Insider)
The 2024 election underscores the intricate connections between political outcomes and business interests, highlighting how corporate leaders may influence and be influenced by electoral politics.
Not bad Chat…Not bad!
I Raise $130 Million on Trump
Elon Musk, the world’s richest person, has been making headlines for his high-stakes support of Donald Trump in the recent election. From rally appearances to a daily $1 million giveaway to registered voters, Musk’s America PAC took steps to influence battleground states. Musk’s alignment with Trump reflects more than shared political beliefs—it has significant implications for Musk’s businesses, including SpaceX and Tesla, which benefit from billions in government contracts and tax breaks.
Want to know what’s at stake for Musk now that Trump has won? Check our in-depth article at article.
Retailers Take Action on the Brink of Tariffs
With Donald Trump’s victory, U.S. companies are already making swift moves to avoid the looming tariffs on Chinese goods. Steve Madden, a major player in footwear, has taken steps to reduce its reliance on Chinese manufacturing. The brand plans to cut its Chinese production by nearly half and shift operations to other countries like Cambodia, Vietnam, and Mexico, anticipating that Trump’s new tariffs on Chinese imports could soar as high as 60%.
The potential impact on U.S. consumers? Higher prices across apparel and footwear as brands face increased costs. The National Retail Federation has estimated that these tariffs could add $24 billion to the annual cost of clothing in the U.S., pushing prices up even for everyday items like sneakers.
Interested in more on the strategic shifts retailers are making in response to tariffs? Check out our in-depth article at here.