Introduction
Why are tech investors and founders are both poor at predicting success?
Why are political analysts are poor at predicting the results of elections?
How can we improve our predictions in tech startups and in politics?
Fake it or make it in tech
As Teemu Arina says “Most entrepreneurs and investors are traumatized”.
Perhaps this is why they are never satisfied with what they have or what they achieved in the past.
Startup events are mass audience participation theater of fake it or make it.
Startup events are swimsuit competitions where startups are up for sale and privileged white middle-aged men are buyers looking for fresh young meat.
Entrepreneurs lie about the state of their product, company, customers, team and themselves. Pitch decks distort underlying truth in order to impress investors.
Investors are not transparent about the amount of dry powder they have.
Coaches help founders with personal branding and pitching to get good at the process of lying to investors.
Investors increasingly leverage self-promotion, personal branding, and storytelling on social media to generate deal flow.
Then there is the networking scene at startup events.
Personal authenticity is replaced with synthetic sugar.
There is a lack of transparency by both founders and investors.
There are a lot of people talking about themselves and dropping elevator pitches.
The result is usually a “let’s stay in touch” and a smile.
Are personal branding and pitch coaches effective at predicting successful startups?
The empirical data says no - the global startup failure rate is 90%.
Source: DemandSage
Politicians fake it or make it
President Biden’s underwhelming debate performance against Donald Trump was a wake-up call for the Democratic party.
Should President Biden continue or should the Democrats choose another candidate who can defeat Trump and lead the United States?
Does prediction help the Democrats keep President Biden in the race?
According to fivethirtyeight - no.
Latest updates
It’s 120 days until Election Day, and our model thinks the presidential election could go either way. Right now, President Joe Biden is favored to win in 512 out of 1,000 of our model’s simulations of how the election could go, while former President Donald Trump wins in 484 of our simulations. There is still a small chance of the pure chaos scenario: In 4 simulations, no candidate wins a majority of Electoral College votes, which would throw the election to the House of Representatives.
It might not seem like it based on the panicked reaction to Biden’s poor debate performance nearly two weeks ago, but the election is still a considerable ways away. This means there is a lot of uncertainty about where the polls will end up on Nov. 5. In turn, the 538 election model puts a healthy amount of weight on non-polling factors such as economic growth and political indicators. Today these indicators suggest an outcome closer to a 3-point Biden win — clear in the opposite direction of national polls.
538’s focus on uncertainty partially explains why our election forecast has not moved much in reaction to new national polls showing Trump gaining on Biden. In effect, we are hedging our bets, putting more weight on the so-called “fundamentals” because we believe the campaign could be volatile or polls could be biased. The other big factor explaining our model’s relative stability is the flurry of swing-state polls that were published over the weekend, most good for Biden. The average swing-state poll published since July 6 has Trump leading Biden by 1 point, compared to his 2.2-point lead in national polls today.
https://projects.fivethirtyeight.com/2024-election-forecast/
How can we improve our predictions in tech and politics?
In his book, “Expert Political Judgment: How Good Is It? How Can We Know?” Philip Tetlock investigated why expert political analysis is so bad. Tetlock looked at a range of predictions from the collapse of the Soviet Union to political elections.
Tetlock shows that expert political analysis is often worse than random chance and inferior to statistical methods in predicting political events.
Tetlock discovered that "foxes" tend to make better predictors than "hedgehogs."
Tetlock borrowed the metaphor from the ancient Greek poet Archilochus, who said, "The fox knows many things, but the hedgehog knows one big thing." In this context:
Hedgehogs are people who view the world through the lens of a single, overarching theory or ideology. They are more likely to be confident in their predictions but less likely to be accurate because they are overly focused on a single perspective. This is often a political or philosophical ideology.
Hedgehogs use new data to confirm but almost never to challenge their existing ideology.
Foxes are people who draw on a wide variety of experiences and perspectives. They are more adaptable and open to changing their minds based on new data. Foxes tend to be less confident in their predictions but more accurate because they integrate multiple viewpoints and are more aware of the complexity and unpredictability of the world.
Tetlock's extensive study on expert political judgment showed that foxes, with their more flexible and eclectic approach, generally outperformed hedgehogs in terms of predictive accuracy. Foxes’ willingness to adjust their views and consider different angles made them better suited to handle the complexity and uncertainty inherent in making predictions about political and economic events.
On November 16, 1988, Estonia announced their independence from the USSR.
Political experts had difficulty anticipating the USSR's collapse, Tetlock found, because a prediction that not only forecast the regime's demise but also understood the reasons for it required different strands of argument to be woven together. There was nothing inherently contradictory about these ideas, but they tended to emanate from people on different sides of the political spectrum, and scholars firmly entrenched in one ideological camp were unlikely to have embraced them both.
Conservatives, on the other hand, were more instinctually critical of communism.
They were quicker to understand that the USSR's economy was failing and that life was becoming increasingly difficult for the average citizen.
As late as 1990, the CIA estimated quite wrongly -that the Soviet Union's GDP was about half that of the United States 3 (on a per capita basis, tantamount to where stable democracies like South Korea and Portugal are today). In fact, more recent evidence has found that the Soviet economy-weakened by its long war with Afghanistan and the central government's inattention to a variety of social problems was roughly $1 trillion poorer than the CIA had thought and was shrinking by as much as 5 percent annually, with inflation well into the double digits.
Take these two factors together, and the Soviet Union's collapse is fairly easy to envision.
The Signal and the Noise - Why so many predictions fail, Nate Silver
Are investors hedgehogs? Are entrepreneurs foxes?
Using Nate Silver’s model of hedgehogs and foxes, we see that investors are primarily hedgehogs.
Hedgehogs are weak forecasters who rely on mental shortcuts to evaluate investment opportunities.
Investors are specialized, often dedicating most of their careers to one or two significant problems, and they view outsiders' opinions skeptically.
Investors are steadfast. They follow a specific investment thesis, such as focusing on seed and early-stage crypto startups rather than late-stage foodtech.
Many investors can be stubborn, influenced by cognitive biases and emotional factors. For example, herd behavior leads them to follow trends in agentic AI even when it's not the best decision.
Investors seek order, expecting the world to follow relatively simple relationships once a signal is identified through the noise. For example, they expect a successful startup to return the entire fund.
Confidence is a hallmark of venture capitalists.
Investors are ideological, reflecting trends such as AI, SaaS, cloud computing, and mobile technology, expecting technology to solve many day-to-day problems.
These generalizations may not apply to all investors. One example of a fund that exhibits flexible, fox-like characteristics is Andreessen Horowitz (a16z). Andreessen Horowitz is known for its broad and adaptive investment strategies across various sectors, including technology, healthcare, and crypto.
In comparison, entrepreneurs possess fox-like qualities but, due to their inherent optimism, often prove to be weaker forecasters than investors.
Multidisciplinary: Entrepreneurs draw from diverse disciplines, integrating various ideas to innovate and solve problems.
Adaptable: They are highly adaptable, often pivoting their strategies and approaches when initial plans do not work out.
Self-critical: While some entrepreneurs can admit their mistakes, it is not universal. Notable examples, such as Adam Neumann, illustrate this variability.
Tolerant of Complexity: Entrepreneurs are sometimes able to navigate and appreciate the complexity of the business environment and the broader universe.
Cautious: Rarely do they frame their predictions in probabilistic terms, preferring a more definitive approach.
Empirical: Entrepreneurs tend to rely more on observation and practical experience rather than purely theoretical frameworks.
When are founders good forecasters?
Second-time founders, having experienced the ups and downs of their initial ventures, often possess a deep appreciation for the role of luck in their success and a keen awareness of their strengths and weaknesses.
These entrepreneurs exhibit strong fox-like characteristics, making them more adaptable, multidisciplinary, and empirical. As a result, they are generally better forecasters of their next success and capable of attracting fox-like investors who value their experience and versatility.
But, your mileage may vary.
Not all second-time founders have fox-like qualities, and their success still depends on luck, market conditions, team dynamics, and execution.
If you take one thing away from this essay, let it be this:
Integrity, ethics, virtues, and values are more important than ever. You can achieve greatness without turning to darkness yourself.
Maintain your moral principles and ethical standards in the pursuit of success
True greatness does not require compromising your integrity.