Informed Practice and Superforecasting: Taking Your Forecasts to the Next Level

Informed Practice and Superforecasting: Taking Your Forecasts to the Next Level

“Not all practice improves skill. It needs to be informed practice.”
– Phil Tetlock & Dan Gardner in Superforecasting

In any area of decision-making where uncertainty looms large, accuracy is the gold standard. However, many decision makers often find themselves in a frustrating cycle—sometimes they make the right call, but other times they miss the mark entirely. Inconsistency can be costly. So, what separates those who occasionally succeed from those who reliably deliver top-notch forecasts? The answer lies in informed practice—one of the concepts at the heart of Superforecasting.

What Is Informed Practice?

Informed practice is not just repetition. It’s a deliberate and thoughtful process of learning from each forecast, refining techniques, and continuously updating one’s beliefs based on new information. It’s about approaching forecasting with a Superforecaster’s mindset—an outlook geared toward improvement, with a consistent effort to mitigate one’s cognitive biases.

What Can Forecasters Learn from Superforecasters?

Superforecasters, known for their uncanny forecasting accuracy, exemplify informed practice. They don’t pull numbers out of a hat or look into a crystal ball for answers. For every question they face, they engage in a rigorous process of analysis, reflection, and adjustment. Here’s how informed practice gives them the edge:

1. Learning from Feedback: Superforecasters thrive on feedback. They meticulously track their forecasts, comparing them against the outcomes to identify where they went right and where they missed the mark. This feedback loop is crucial. It allows them to recalibrate their approach and avoid making the same mistakes twice. Over time, this leads to more refined and accurate forecasts.

2. Understanding Probability: A key aspect of informed practice is the understanding and effective use of probability. Superforecasters don’t think in black-and-white, yes-or-no terms. They consider a range of possible outcomes and assign probabilities to each. They also update these probabilities as new information becomes available, a process known as Bayesian reasoning. This probabilistic thinking helps them navigate uncertainty with greater precision.

3. Continuous Learning: The world is constantly changing, and so too are the variables that influence forecasts. Superforecasters are voracious learners, continuously updating their knowledge base. They stay informed about the latest developments in multiple areas, thus grounding their forecasts in the most current data and insights.

4. Mitigating Cognitive Biases: Cognitive biases can cloud judgment and lead to poor forecasts. Superforecasters are keenly aware of these biases and actively work to mitigate their impact. Through informed practice, they develop strategies to counteract such biases as overconfidence, anchoring, confirmation bias, and more, to make well-calibrated forecasts.

What Is the Role of Collaboration in This?

Informed practice is not a solitary endeavor. Collaboration with other forecasters is a powerful tool for improving accuracy and keeping track. By engaging in discussions, comparing notes, and challenging each other’s assumptions, forecasters can gain new perspectives and insights. Good Judgment’s Superforecasters work in teams, leveraging the collective intelligence of the group to arrive at superior forecasts.

What Practical Steps Can I Take?

1. Keep Track: Keep a record of your forecasts and compare them with the outcomes. Analyze your hits and misses to identify patterns and areas for improvement.

2. Seek Feedback: Seek out feedback from peers or through forecasting platforms such as GJ Open, which provides performance metrics. Use this feedback to refine your approach.

3. Diversify Your Sources of Information: Regularly update your knowledge on the topics you forecast and seek out diverse sources. This includes staying current with news, research, and expert opinions, including those you disagree with.

4. Practice Probabilistic Thinking: Assign probabilities to your forecasts and be willing to adjust them as new information emerges. This helps you avoid the trap of binary thinking.

5. Challenge Your Assumptions: Regularly question your assumptions and be open to changing your mind. This flexibility is crucial in a rapidly changing world.

6. Get a Head Start with GJ Superforecasting Workshops: Consider enrolling in a Superforecasting workshop. Good Judgment’s workshops, led by Superforecasters and GJ data scientists, leverage our years of experience in the field of elite forecasting as well as new developments in the art and science of decision-making to provide you with structured guidance on improving your forecasting skills. Our practical exercises will boost your informed practice, offering you lifelong benefits.

Informed practice is the cornerstone of good forecasting and one of the secrets behind the success of Superforecasters. By diligently applying the above principles, you can enhance your forecasting skills and make better-informed decisions. See the workshops we offer to help you and your team take your forecasting success to the next level.

Common Questions about Good Judgment Inc and Superforecasters

A Primer on Good Judgment Inc and Superforecasters

At Good Judgment Inc (GJI), the official home of Superforecasting®, we pride ourselves on our ability to provide well-calibrated and insightful forecasts. As we continue to partner with clients and media worldwide, it is worthwhile to address some of the common questions we receive about our work. Here is a primer on our story, probabilistic forecasts, and our team of Superforecasters.

What’s in a Name? GJP, GJI, and GJ Open

The Good Judgment Project (GJP)
In 2011, the Intelligence Advanced Research Projects Activity (IARPA) launched a massive tournament to identify the most effective methods for forecasting geopolitical events. Four years, 500 questions, and over a million forecasts later, the Good Judgment Project (GJP), led by Philip Tetlock and Barbara Mellers at the University of Pennsylvania, emerged as the clear winner of the tournament. The research project concluded in 2015, but its legacy lives on. The GJP is credited with the discovery of Superforecasters, people who are exceptionally skilled at assigning realistic probabilities to possible outcomes even on topics outside their primary subject-matter training.

Good Judgment Inc (GJI)
GJI is the commercial successor to the GJP and the official home of Superforecasting® today. We leverage the lessons learned during the IARPA tournament and insights gained in our subsequent work with Phil Tetlock and his research colleagues as well as with leading companies, academic institutions, governments, and non-governmental organizations to provide the best and the latest in forecasting and training services. Our goal is to help organizations make better decisions by harnessing the power of accurate forecasts. GJI relies on a team of Superforecasters, as well as data and decision scientists, to provide forecasting and training to clients.

Good Judgment Open (GJ Open)
GJO, or GJ Open, is our public platform, open to anyone interested in making forecasts. Unlike GJI, which involves professional Superforecasters, GJO welcomes participation from the public. The “Open” in GJ Open not only signifies that it’s accessible to all but also draws a parallel to golf tournaments. Forecasting questions vary in their complexity, so there is no absolute score to indicate a “good” forecast. We use the median of participants’ scores as a benchmark, similar to par in golf, where lower scores indicate better performance.

A Note on Spelling
You may have noticed that “judgment” is spelled without an “e” on all our platforms. This is a consistent choice across GJP, GJI, and GJ Open, reflecting our preference for the parsimonious American spelling of the word.

Understanding Probabilistic Forecasts
Sample forecast on FutureFirst™, 12 July 2024

Our forecasts are not polls. They are aggregated probabilistic predictions about specific events. For instance, Superforecasters gave Joe Biden an 82% chance of winning the 2020 US presidential election. This means that if the election were held 100 times, Biden would win in 82 of those instances.

A common misconception is interpreting a probabilistic forecast as “X% of Superforecasters say a particular outcome will happen.” In reality, each Superforecaster provides their own probabilistic forecast, and we aggregate these individual predictions to reach a collective forecast. Therefore, an 82% forecast does not mean 82% of Superforecasters believe a certain outcome will occur. It is an aggregated probability of the outcome (an 82% probability of it occurring and an 18% probability of a different outcome) based on all individual forecasts.

Understanding Superforecasters’ Backgrounds

Good Judgment works with some 180 Superforecasters from around the world whose forecasting accuracy placed them in the top 1-2% of the more than 100,000 forecasters who took part in the GJP or qualified on GJ Open. Our Superforecasters come from a wide range of professional fields, including finance, IT, humanities, social sciences, engineering, and more. This allows them to approach forecasting questions in a well-rounded way, combining their exceptional forecasting skills with specialized knowledge in different areas.

Age and Geographic Diversity
Superforecasters range in age from their 20s to their 70s and hail from different parts of the world. This geographic and demographic diversity helps to ensure that our forecasts are informed by a broad spectrum of experiences and viewpoints.

The Wisdom of the Crowd
We emphasize the importance of the wisdom of the crowd. Our Superforecasters read different publications in various languages and bring diverse perspectives to the table. To borrow terminology from Tetlock’s training materials in the GJP, some are Intuitive Scientists, others are Intuitive Historians, while still others are Intuitive Data Scientists.

Collaborative Nature of Forecasting
Forecasting at GJI is a team effort. We focus on collective intelligence. It’s not about individual forecasting superheroes tackling challenges alone but about identifying people who bring unique strengths to the table as a team of Superforecasters.

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Superforecaster Tips: Dealing with Confirmation Bias in Election Forecasting

Superforecaster Tips: Dealing with Confirmation Bias in Election Forecasting

As the 2024 US election approaches, forecasters are faced with the daunting task of finding signal amid a cacophony of partisan noise, personal biases, and volatile public opinion. One significant challenge is confirmation bias—the tendency to search for, interpret, and recall information in a way that confirms one’s preconceptions. In this blog post, we draw on an internal discussion among seasoned Superforecasters to explore practical strategies forecasters can use to mitigate confirmation bias in election forecasting.

Diversifying Information Sources

“Assign yourself to spend some time reading (reasonably reputable) news sources that disagree with your general perspective on the question.”

Superforecasters highlight the importance of consuming a balanced diet of news sources, including those that challenge one’s beliefs. This approach was systematized by Good Judgment Project (GJP) superforecaster Doug Lorch, who wrote a program to randomize his news intake among a diverse set of sources.

“It certainly didn’t hurt,” recalls Terry Murray, CEO Emeritus of Good Judgment Inc and Project Manager for the GJP at UC–Berkeley. “He was the top forecaster in the whole IARPA tournament that year.”

Engaging in Scenario Analysis and Premortems

“I try to run through various scenarios where [the expected winner] could end up losing.”

Superforecasters routinely consider alternative outcomes by rigorously testing their own assumptions and logic. This involves running through various scenarios where expected outcomes might not materialize and thinking critically about the conditions that would lead to different results.

Embracing Epistemic Humility

“One thing I know is that I don’t know much.”

Acknowledging the limits of one’s knowledge and being open to new information is another tip the Superforecasters offer. This strategy is crucial for preventing overconfidence and being receptive to counterarguments.

Red Teaming

“One of the most important duties for me, as a Red Team member, is not to convince a forecaster that they are wrong… Rather, it’s to test the confidence of the Superforecaster in their own forecast.”

Having a red team to challenge forecasts helps forecasters to re-evaluate the confidence in their arguments and consider why they might be wrong. Red teaming is a standard practice in all Good Judgment’s forecasting.

Leveraging Collective Wisdom

“Sometimes, it pays to listen to the articulated reason of an outlier.”

Some Superforecasters use the median forecast of their group as a benchmark, particularly when their individual estimates deviate significantly from the consensus. This approach can provide a reality check against one’s own extremes. It is important, however, to pay attention to outlier opinions too, to resist conformity and groupthink.

As we dive into another election cycle, the discipline of forecasting reminds us that remaining actively open-minded is more crucial than ever. Combating confirmation bias in election forecasting is no small feat, given the complexity and the emotionally charged nature of politics. However, by employing strategies such as diversifying information sources, engaging in premortems, practicing epistemic humility, employing red teaming, and referencing the collective wisdom of peers, forecasters can enhance the accuracy and reliability of their predictions. Good Judgment’s exclusive forecast monitoring tool FutureFirst™ offers daily forecast updates on election results and trends and many other topics, brought to you by professional Superforecasters.

Learn More about FutureFirst™!