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The Good Judgment Project

The Good Judgment Project is a science topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand The Good Judgment Project rather than just read about it. In short: The Good Judgment Project (GJP) is an organization dedicated to "harnessing the wisdom of the crowd to forecast world events". It was co-created by Philip E.

Key takeaways

  • The Good Judgment Project belongs to science; place it in that map before memorising details.
  • Learn the definition first, then one example that makes the definition concrete.
  • Connect The Good Judgment Project to a quantity you can measure, compute or draw — that is where exam questions come from.
  • Reproduce the core statement of The Good Judgment Project from memory before moving on to harder problems.

Reference excerpt

The Good Judgment Project (GJP) is an organization dedicated to "harnessing the wisdom of the crowd to forecast world events". It was co-created by Philip E. Tetlock (author of Superforecasting: The Art and Science of Prediction and Expert Political Judgment), decision scientist Barbara Mellers, and Don Moore, all professors at the University of Pennsylvania. The project began as a participant in the Aggregative Contingent Estimation (ACE) program of the Intelligence Advanced Research Projects Activity (IARPA). It then extended its crowd wisdom to commercial activities, recruiting forecasters and aggregating the predictions of the most historically accurate among them to forecast future events. Predictions are scored using Brier scores. The top forecasters in GJP are "reportedly 30% better than intelligence officers with access to actual classified information."

History The Good Judgment Project began in July 2011 in collaboration with the Aggregative Contingent Estimation (ACE) Program at IARPA (IARPA-ACE). The first contest began in September 2011. GJP was one of many entrants in the IARPA-ACE tournament, which posed around 100 to 150 questions each year on geopolitical events. The GJP research team gathered a large number of talented amateurs (rather than geopolitical subject matter experts), gave them basic tutorials on forecasting best practice and overcoming cognitive biases, and created an aggregation algorithm to combine the individual predictions of the forecasters. GJP won both seasons of the contest, and were 35% to 72% more accurate than any other research team. Starting with the summer of 2013, GJP were the only research team IARPA-ACE was still funding, and GJP participants had access to the Integrated Conflict Early Warning System.

People The co-leaders of the GJP include Philip Tetlock, Barbara Mellers and Don Moore. The website lists a total of about 30 team members, including the co-leaders as well as David Budescu, Lyle Ungar, Jonathan Baron, and prediction-markets entrepreneur Emile Servan-Schreiber. The advisory board included Daniel Kahneman, Robert Jervis, J. Scott Armstrong, Michael Mauboussin, Carl Spetzler and Justin Wolfers. The study employed several thousand people as volunteer forecasters. Using personality-trait tests, training methods and strategies the researchers at GJP were able to select forecasting participants with less cognitive bias than the average person; as the forecasting contest continued the researchers were able to further down select these individuals in groups of so-called superforecasters. The last season of the GJP enlisted a total of 260 superforecasters.

Research A significant amount of research has been conducted based on the Good Judgment Project by the people involved with it. The results show that harnessing a blend of statistics, psychology, training and various levels of interaction between individual forecasters, consistently produced the best forecast for several years in a row.

Good Judgment Inc. A commercial spin-off of the Good Judgment Project started to operate on the web in July 2015 under the name Good Judgment Inc. Their services include forecasts on questions of general interest, custom forecasts, and training in Good Judgment's forecasting techniques. Starting in September 2015, Good Judgment Inc has been running a public forecasting tournament at the Good Judgment Open site. Like the Good Judgment Project, Good Judgment Open has questions about geopolitical and financial events, although it also has questions about US politics, entertainment, and sports.

Media coverage GJP has repeatedly been discussed in The Economist. GJP has also been covered in The New York Times, The Washington Post, and Co.Exist. NPR aired a segment on The Good Judgment Project by the title "So You Think You're Smarter Than a CIA Agent", on April 2, 2014. The Financial Times published an article on the GJP on September 5, 2014. Washingtonian published an article that mentioned the GJP on January 8, 2015. The BBC and The Washington Post published articles on the GJP respectively on January 20, 21, and 29, 2015. The Almanac of Menlo Park published a story on the GJP on January 29, 2015. An article on the GJP appeared on the portal of the Philadelphia Inquirer, Philly.com, on February 4, 2015. The book Wiser: Getting Beyond Groupthink to Make Groups Smarter has a section detailing the involvement of the GJP in the tournament run by IARPA. Psychology Today published online a short article summarizing the paper by Mellers, et al., that wraps up the main findings of the GJP. The project spawned a 2015 book by Tetlock and coauthored by Dan Gardner, Superforecasting - The Art and Science of Prediction, which divulges the main findings of the research conducted with the data from the GJP. Co-author Gardner had already published a book in 2010, that quoted previous research by Tetlock that seeded the GJP effort. A book review in the September 26, 2015, print edition of the Economist discusses the main concepts. A Wall Street Journal article depicts it as: "The most important book on decision making since Daniel Kahneman’s Thinking, Fast and Slow." The Harvard Business Review paired it with the book How Not to Be Wrong: The Power of Mathematical Thinking by Jordan Ellenberg. On September 30, 2015, NPR aired an episode of the Colin McEnroe Show centering on the GJP and the book Superforecasting; guests on the show were Tetlock, IARPA Director Jason Matheny, and superforecaster Elaine Rich.

See also Wisdom of the crowd Aggregative Contingent Estimation Intelligence Advanced Research Projects Activity SciCast

References

External links Official website Good Judgment Open

Worked examples

Example 1 — a first encounter with The Good Judgment Project

Start with the simplest possible case. Write down what The Good Judgment Project claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In science, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to The Good Judgment Project before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about The Good Judgment Project ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of The Good Judgment Project

In research
The Good Judgment Project appears in science research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry
Engineering practice reuses The Good Judgment Project in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom
The Good Judgment Project is common in secondary-school and first-year university syllabi. It links to neighbouring topics Crowdsourcing, Government research, Prediction, so understanding it makes those chapters shorter.
In everyday life
Look for The Good Judgment Project outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.
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How to study The Good Judgment Project in 20 minutes

  1. Read the reference excerpt below once, without taking notes.
  2. Close the page and write down what The Good Judgment Project means in your own words.
  3. Compare your version with the excerpt and mark what you missed.
  4. Work through the three examples above with pen and paper.
  5. Explain The Good Judgment Project out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is The Good Judgment Project in simple terms?

The Good Judgment Project (GJP) is an organization dedicated to "harnessing the wisdom of the crowd to forecast world events". It was co-created by Philip E.

Why does The Good Judgment Project matter?

Because it connects several science ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study The Good Judgment Project?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on The Good Judgment Project.

Tags

  • Crowdsourcing
  • Government research
  • Prediction
  • Prediction markets

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