Episode 162 — September 19th, 2024 — Available at read.fluxcollective.org/p/162
Contributors to this issue: Neel Mehta, Boris Smus, Erika Rice Scherpelz, Dimitri Glazkov, Wesley Beary, Ben Mathes, Dart Lindsley, MK
Additional insights from: Ade Oshineye, Justin Quimby, Alex Komoroske, Robinson Eaton, Spencer Pitman, Julka Almquist, Scott Schaffter, Lisie Lillianfeld, Samuel Arbesman, Jon Lebensold, Melanie Kahl, Kamran Hakiman, Chris Butler
We’re a ragtag band of systems thinkers who have been dedicating our early mornings to finding new lenses to help you make sense of the complex world we live in. This newsletter is a collection of patterns we’ve noticed in recent weeks.
“We commonly think of animals and plants as matter, but they are really systems through which matter is continually passing.”
— William Bateson
🌉💭 Bridging the belief gap
You think your relationship is thriving, and you're ready to propose. But the reality is different—your partner intends to break up with you. When a belief like this is so far off, the impact is profound, challenging your understanding of yourself and your connection with others. The lens through which you view your relationship suddenly cracks, forcing you to confront a new reality.
Every decision carries the potential of being right and the risk of being wrong. But some mistakes do more than set us back. They shake our entire worldview. While jarring, these moments offer opportunities to examine the lenses through which we see the world.
One lens is negativity bias, an instinct honed for survival. Because some mistakes have severe consequences, we tend to focus on potential dangers, often at the expense of seizing opportunities. While this bias can protect us, it can also lead to paralysis and missed chances.
Another lens is to see mistaken beliefs as opportunities to rethink, rebuild, and learn. Accepting the possibility of being wrong opens us to growth and innovation. This mindset doesn’t erase the pain of mistakes but can change our relationship with them, turning challenges into stepping stones toward resilience and insight.
Is there a middle ground between despair and pollyannaish optimism? Sometimes, we can consider the odds and consequences of being wrong to reach a more measured judgment. We refine our perspective, balancing caution with the courage to move forward.
What does that look like? Here’s a toy example. Suppose we believe there's no tiger in the kitchen. If there actually is, the consequences are severe—we become lunch instead of having lunch. However, the probability of that is low. Now consider the opposite belief: we think there is a tiger, but there isn’t. The direct consequences of being wrong are minor—we miss a meal. However, given that there is almost certainly not a tiger, the missed opportunity dominates the reduced risk of a tiger attack.
The critical question is how tightly we should hold our beliefs and how strongly we should consider alternatives. If being wrong is both likely and carries severe consequences, it’s wise to embrace some negativity bias. Otherwise, it’s time to lean into the potential for growth. Evaluating the likelihood and impact of each outcome helps us decide whether to hold onto our belief or adjust it, balancing risks and rewards.
Of course, the most disruptive, unproductive beliefs sneak up on us. Some beliefs go deep enough that we never question them. And even if we had, no amount of reflection can shield us from the pain of being wrong about such a core belief. However, by learning to hold our beliefs at a bit of a distance more frequently, we can build habits of resilience, allowing us to adapt more quickly when we find gaps in our beliefs.
So, as you make personal or professional decisions, remember that the risk of being wrong is also an opportunity to deepen your understanding. Balance caution with creativity, knowing that even when things don’t go as planned, there’s always a chance to learn and discover new paths.
🛣️🚩 Signposts
Clues that point to where our changing world might lead us.
🚏🇨🇳 China is raising its retirement age for the first time in 70 years
The Chinese government has passed a bill to raise the minimum retirement age from 60 to 63 for men, from 55 to 58 for women in white-collar jobs, and from 50 to 55 for women in blue-collar jobs. Policy analysts cited China’s shrinking, aging population and the deficits facing its pension funds as likely reasons for the move. (China’s population shrank for the first time in modern history in 2022, and in 2023, it lost an additional 2 million people.)
🚏📮 The USPS is launching a massive fleet of electric trucks with an all-new design
Thanks to a $3 billion grant, the US Postal Service is launching a fleet of 106,000 “next generation vehicles” with an unusual new ‘duckbill’ design. Sixty-six thousand of those trucks will be electric, making them “one of the largest electric fleets in the nation.” The new trucks come with air conditioning, airbags, 360º cameras, and a more convenient interior configuration — a big step up from the old 1987 fleet, which lacked AC and many basic safety features. (That’s not to mention their pitiful 9 miles per gallon and propensity to catch fire.)
🚏🧑💼 Amazon will make employees come to the office five days a week
Amazon’s CEO announced that employees must return to the office five days a week starting in January 2025, calling it a return to pre-COVID work styles. Amazon currently follows a hybrid ‘3 days in the office, 2 days remote’ model, which has become quite popular in the tech industry; other companies may follow Amazon’s lead in returning to a purely in-person model.
🚏🌬️ The EU now generates more power from wind and solar than fossil fuels
During the first half of 2024, the European Union generated 30% of its electricity from wind and solar combined, compared to just 27% for fossil fuels. Experts cited Russia’s invasion of Ukraine as a significant factor in the shift: many EU countries responded to the invasion by fast-tracking wind and solar projects and reducing natural gas imports (which largely came from Russia). Hydropower has also seen impressive results, further driving down demand for fossil fuels.
📖⏳ Worth your time
Some especially insightful pieces we’ve read, watched, and listened to recently.
Evidence of Fraud in an Influential Field Experiment About Dishonesty (Data Colada) — A deep analysis of one of the most famous cases of academic data falsification: when a superstar social psychology prof “found” that putting an honesty statement at the top of an auto insurance form (rather than at the bottom) reduced apparent lying in self-reported miles driven. This piece uses statistical distributions, mathematical simulations, and forensic document analysis to build a case where the study designers added random numbers to the original data to fabricate a satisfying result.
Nike Drops the Ball (Bloomberg Businessweek) — A podcast that explores how Nike’s CEO John Donahoe — a finance man by trade and just the second “outsider” CEO in Nike’s history — briefly juiced the company’s profits by over-focusing on older cash cow shoes while cutting R&D spending. But as new product development slowed and Donahoe’s decision to sell direct-to-consumer backfired (losing shelf space at key retail partners to rival brands), Nike started slashing revenue forecasts, cutting costs, and laying off employees — all amidst a stock price collapse.
Calculating Empires: A Genealogy of Technology and Power Since 1500 (Crawford & Joler) — A hugely detailed data visualization “exploring how technical and social structures co-evolved over five centuries,” with a focus on how technological advancements have been used to gain and wield power through imperialism, militarism, nation-building, and big business. It maps technologies, their evolution, and their impacts across time (the Y-axis) and theme (the X-axis).
Why Do We Crumble Under Pressure? Science Has the Answer (Nature) — Shares research on monkeys that found that the neurons responsible for motor skills will activate more as the size of a reward increases, but only up to a point: for huge rewards, neural activity actually decreases. That is, there’s a “sweet spot” for physical performance, and if the stakes get too high, we can “choke” under the pressure. As one scientist summarized it, “reward-outcome-mediated behavior is not linear.”
🔍📆 Lens of the week
Introducing new ways to see the world and new tools to add to your mental arsenal.
This week’s lens: scenario planning.
Scenario planning helps organizations navigate uncertainty by exploring multiple plausible futures. Rather than predicting a single outcome, scenario planning imagines a range of possibilities, enabling preparation for diverse developments and adapting strategies accordingly. One of our favorite variants, the two by two, takes two axes of change and explores the resulting scenarios. For example, we might combine possibilities for how much AI will improve (incrementally or with a leap forward) with whether it becomes more centralized or more open and commoditized, leading to four scenarios we can imagine, compare, and contrast. Each path has vastly different implications for business, society, and governance.
When scenario planning, we see uncertainty as a strength. Accepting the inherent unpredictability of the future awards us with a neat judo move: make the uncertainty work for us, help us uncover new opportunities, and build resilience. In the AI example, this might mean preparing for both centralized and commoditized uses of AI, ensuring the organization is poised to thrive regardless of which scenario unfolds.
Scenario planning is also a tool for building more robust shared mental models among the participants. Pierre Wack, credited with first using scenario planning in the private sector, argued that this was the most valuable part of the process. Similarly, scenario planning is excellent at mitigating confirmation bias: exploring multiple divergent possibilities increases our chances of seeing something the bias would have otherwise hidden.
Besides formal exercises, scenario planning is also helpful as an everyday mindset. As we make decisions, we can get into the habit of thinking about the dimensions of uncertainty and how our assumptions impact our choices. Sometimes, we might find our assumptions irrelevant: whatever happens in 3 years, what we build today can only use the capabilities gen AI has today. Other times, this sort of scenario thinking will help us uncover critical and incidental dimensions. As assumptions change — e.g., new models are released — regularly utilizing scenario planning will make it easier to update our thinking.
While scenario planning can help us keep our options more open, beware of using it as an excuse not to make decisions. Optionality has a cost, and taken to an extreme, if we never make decisions, then we’ll never reap any benefits. Let’s also avoid mistaking our explorations of different future scenarios for reliable predictions. Hold scenarios lightly, as a tool to inform our decision-making, not decide for us.
When facing an uncertain future, we can use scenario planning to see that there are more possibilities out there than initially come to mind, which is valuable no matter how our predictions turn out.
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Thanks for sharing. This post has lots of apropos lessons for the work I do in water data. Planning to share with a few folks :)