University of Pennsylvania — Research on Mammalian Reproduction (Kotaro Sasaki) (2020)


Grant investigators: Chris Somerville and Heather Youngs

This page was reviewed but not written by the grant investigators. University of Pennsylvania staff also reviewed this page prior to publication.


Open Philanthropy recommended a grant of $1,000,000 over four years to the University of Pennsylvania to support research by Professor Kotaro Sasaki on mammalian reproduction. Professor Sasaki’s research is focused on the development of gametes from stem cells.

Progress in this area could eventually enable people with fertility challenges to have children and could eventually help reduce the incidence of a wide variety of congenital diseases and promote other positive outcomes. Professor Sasaki’s research is among the most promising our science team has encountered so far in this field.

This follows our February 2019 support and falls within our work on scientific research, specifically within our interest in advancing transformative basic science.

University of Pennsylvania — Geopolitical Forecasting Research (2021)

Grant investigator: Luke Muehlhauser

This page was reviewed but not written by the grant investigator. University of Pennsylvania staff also reviewed this page prior to publication.

Open Philanthropy recommended a grant of $132,181 to the University of Pennsylvania to support follow-up activities related to Professor Michael Horowitz’s research on potential geopolitical applications of quantified forecasting methods. Following our August 2020 support, Professor Horowitz completed a report identifying means for quantified forecasting to enhance the decision-making capabilities of the U.S. government.

University of Pennsylvania — Geopolitical Forecasting Research (2020)


Grant investigator: Luke Muehlhauser

This page was reviewed but not written by the grant investigator. University of Pennsylvania staff also reviewed this page prior to publication.


Open Philanthropy recommended a grant of $29,432 to the University of Pennsylvania to support research led by Professor Michael Horowitz on potential geopolitical applications of quantified forecasting methods. Professor Horowitz intends for the research to identify means for quantified forecasting to enhance the decision-making capabilities of the U.S. government.

University of Pennsylvania — Research on Mammalian Reproduction (Kotaro Sasaki) (2019)


Grant investigators: Chris Somerville and Heather Youngs

This page was reviewed but not written by the grant investigator. UPenn staff also reviewed this page prior to publication.


The Open Philanthropy Project recommended a grant of $660,000 over three years to the University of Pennsylvania to support research by Professor Kotaro Sasaki on mammalian reproduction. Dr. Sasaki’s proposed research would be specifically focused on development of gametes from stem cells.

Progress in this area could eventually enable people with fertility challenges to have children and could eventually help reduce the incidence of a wide variety of congenital diseases and promote other positive outcomes. Dr. Sasaki’s research is amongst the most promising our science team has encountered so far in this field.

This falls within our work on scientific research, specifically within our interest in advancing transformative basic science.

University of Pennsylvania — Philip Tetlock’s “Making Conversations Smarter, Faster” Forecasting Project

Grant investigator: Luke Muehlhauser
This page was reviewed but not written by the grant investigator. University of Pennsylvania staff also reviewed this page prior to publication.

The Open Philanthropy Project recommended a grant of $1,550,000 to the University of Pennsylvania to support work on a collaborative reasoning system called “Making Conversations Smarter, Faster” (MCSF). This system will be designed to incentivize high epistemic quality in participants’ contributions to a collaborative reasoning process, for example a policy debate or a forecasting exercise. Another goal of MCSF is to identify and cultivate “super analysts” (who are significantly better than average at distinguishing between strong and weak ideas, arguments, and evidence) in much the same way that recent forecasting tournaments have identified and cultivated “superforecasters” (who are significantly better than average at producing accurate forecasts).

See Philip Tetlock and Dan Gardner’s 2015 book: “Superforecasting: The Art and Science of Prediction”. @Superforecasting, Tetlock and Gardner, [email protected]

The funds are intended to support the initial development and pre-testing of MCSF, laying the groundwork for future confirmatory studies. This work will be led by Professors Philip Tetlock and Barbara Mellers of University of Pennsylvania, and Professor Emeritus Daniel Kahneman of Princeton University.

Update: In February 2019, we added $250,000 to the original award amount. The “grant amount” above has been updated to reflect this.

Sources

Document Source
Superforecasting, Tetlock and Gardner, 2015 Source (archive)

University of Pennsylvania — Philip Tetlock on Forecasting

University of Pennsylvania staff reviewed this page prior to publication.


The Open Philanthropy Project recommended a grant of $500,000 to Professor Philip Tetlock of the University of Pennsylvania to support his work on forecasting.

It is our impression that Professor Tetlock is among the leading researchers working on improving methods used for forecasting. Several Open Philanthropy Project staff members follow his research on expert judgment and geopolitical forecasting and, based on this familiarity with his work, we believe that he has a compelling track record in this area.

Professor Tetlock wrapped up a previous project, the Good Judgment Project, in the middle of last year. Subsequently, we learned that he was seeking funding for two new projects, currently called “Adversarial Collaboration Tournaments” and the “Alpha Pundit Challenge.” Professor Tetlock believes that these projects might contribute to making forecasting a more prominent component of policy discussions and debates; he describes the projects’ goal as depolarizing unnecessarily polarized debates.

1. Background

1.1 The cause

This grant does not fall within any of our previously defined focus areas. Although we are in the early stages of investigating the social sciences as a potential cause category, at present we consider this to be a one-off grant.

1.2 About Philip Tetlock

Professor Tetlock has extensive experience running and evaluating political forecasting tournaments. Beginning in the mid-1980s and continuing through the early 2000s, he organized forecasting tournaments for experts drawn from many different areas of expertise. His analysis of the performance of these experts found that they did not consistently make accurate predictions. Their results were frequently only slightly better than what one would expect from random chance and were often worse than the performance of basic extrapolation algorithms.1

It is our understanding that, after Professor Tetlock published these results, figures in the U.S. intelligence community learned of his research and were alarmed by its implications. In order to improve its forecasting, Intelligence Advanced Research Projects Activity (IARPA), the intelligence equivalent of the better known DARPA, created the Aggregative Contingent Estimation (ACE) program, which ran geopolitical forecasting tournaments. Professor Tetlock entered the ACE tournament with a team known as the Good Judgment Project (GJP). GJP easily outperformed all other tournament entrants, including U.S. intelligence analysts with access to classified data.2

1.3 About the Good Judgment Project

GJP’s method was relatively simple – aggregating predictions from many sources – but its process was also adaptive. During the course of the tournaments GJP ran randomized controlled trials on its own program and used the results to improve its forecasting model in future years. The principal findings included:

  • Creating teams of forecasters that share information among themselves and collaborate improves the accuracy of their predictions relative to simply aggregating the predictions of the same people.3
  • Providing forecasters with one hour of training on topics such as base rates, belief updating, and mathematical modeling improves accuracy.4
  • Forecasting contains a component of skill, and is not based entirely on luck. Some forecasters were consistently more accurate and did not regress to the mean as would be expected if their success were due only to chance.5
  • When grouped together into teams, the most accurate 2% of predictors, dubbed “superforecasters,” outperformed teams of other predictors by a greater margin than any had prior to being placed on a team with other top performers. One news article claims that predictions made by teams of superforecasters were 30% more accurate than predictions made by professional intelligence analysts with access to classified information.6

After the conclusion of the tournament, Professor Tetlock wrote a book, Superforecasting: The Art and Science of Prediction, about lessons learned from GJP.7 Subsequently, GJP was changed into a for-profit entity known as Good Judgment, Inc.8

2. About the grant

2.1 Proposed activities

This funding is structured to be unrestricted within Professor Tetlock’s work on forecasting. At this stage, the main potential uses we have discussed with him revolve around two projects that he characterized to us as “public goods” projects. Both proposed projects aim to depolarize unnecessarily polarized debates.

The first project, “Adversarial Collaboration Tournaments,” would involve experts on both sides of a polarized issue (e.g., the Patient Protection and Affordable Care Act) proposing and answering forecasting-style questions about that issue. The second project, the “Alpha Pundit Challenge,” would systematically convert vague predictions made by prominent pundits into explicit numerical forecasts. Both of these projects are in the early stages of planning, so the details have not been worked out, but they share the goal of encouraging public figures with strong positions on important issues to convert those positions into concrete forecasts.

We expect that the funds provided by our grant will be used for a variety of activities that could be described as pilot projects for the two projects described above. If these early projects go well, we may consider funding a larger and more public effort at a later date.

Professor Tetlock expects to have limited time and attention available to spend on these projects. During our conversations with him, he expressed interest in hiring superforecasters for day-to-day roles relating to these projects.

2.2 Case for the grant

We see this as a fairly speculative grant; our intention is to support someone we believe has done very good work on a potentially important topic, by providing sufficient funding to allow him some freedom to plan and develop new projects.

When describing the motivation behind his “public goods” projects, Professor Tetlock has pointed to the extremely polarized rhetoric that is often used to discuss political issues. He notes that the positions of people on both sides of a given issue usually rely on implicit predictions about the future, but that such predictions are usually phrased so vaguely that it is difficult to say, even in retrospect, whether they were correct.9

As we understand it, Professor Tetlock believes that if making explicit predictions were a more expected part of publicly defending a strong position, pundits with polarized views would both (a) be held accountable to the implications of their views, and (b) have more incentive to listen to others with opposite opinions, in the interest of improving their own forecasts. This underlies the design of the two projects described above.

We share Professor Tetlock’s intuition that making forecasting a more normalized part of mainstream political discourse would be valuable, and find the proposed mechanism of the projects plausible (though we are not confident they will be successful).

The basic case for this grant, as we see it, is that:

  • Professor Tetlock has a very strong record of studying and improving forecasting techniques, and has garnered a reasonable amount of public attention for this work.
  • We believe that increasing the use of forecasting in public debate on policy questions (whether by increasing the amount that public figures make forecasts themselves, making it more common to refer to forecasts by others, or something else) would very likely be a positive development, potentially improving the quality of both discourse and decision-making.
  • Based on conversations with Professor Tetlock, our impression is that he would now like to develop projects specifically targeting this ‘public discourse’ angle, and that having funds available would make it easier for him to make progress with those projects.

As an alternate framing, we think it also makes sense to describe our interest in this grant in terms of the considerations we rely on when prioritizing between cause areas. Our current (informal and preliminary) take is that this grant is supporting work in an area that is important (in that it could affect many very important decisions if successful), neglected (in that Professor Tetlock, who stands out in the field for his past work, does not appear to be “fully funded” in our estimation), and tractable (in that Professor Tetlock’s work over the last several decades seems to us to have generated substantive insights about how to improve forecasting, and to have been somewhat successful in attracting public attention).

This grant is primarily about open-ended support of someone we believe has done impressive work in the past.

2.3 Risks and reservations

We see this grant as speculative by nature, and accordingly believe there is a reasonable chance that it does not have much impact; this could be either if the projects themselves do not amount to much, or if, in the absence of our grant, other funding sources would have been found.

One salient risk is that Professor Tetlock has other obligations and does not expect to personally be able to dedicate much time or attention to these projects. Another point that strikes us as relevant is that we are unaware of anyone involved with the projects with extensive experience running a large public-facing project (which these might eventually become), though Professor Tetlock does have experience fielding publicity for his work with the Good Judgment Project and his books, Expert Political Judgment and Superforecasting.10

2.4 Room for more funding

Prior to this grant from the Open Philanthropy Project, Professor Tetlock secured $200,000 from another funder and he has been in discussions with other potential sources of funding. Per the previous section, we do believe it is possible that our grant will simply displace funds that would have come from other sources. However, our impression based on conversations with Professor Tetlock is that our funding will allow him to develop the projects more quickly and potentially more ambitiously than might otherwise have been possible.

3. Plans for follow-up

3.1 Goals and expectations for this grant

We do not have settled expectations for this grant. We expect that there is a large range of possible outcomes that we would be happy with, and that would be hard to predict in advance.

We think that it is reasonable to expect that this grant enables Professor Tetlock’s future projects to launch, and perhaps to become more ambitious than they otherwise would have been. We would be pleased if these projects improve our understanding of forecasting and prediction-making in general, or if they provide a platform for Professor Tetlock to bring his existing findings to a more mainstream audience.

An example of a very positive outcome, from our perspective, would be if this grant contributes to a shift towards a world in which comparing policy claims to the best available forecasts becomes a standard component of evaluating such claims. We consider it very unlikely that this will be a direct outcome of this grant, but we would be excited if the grant laid some groundwork for further work in this direction.

An example of the kind of impact we would consider a moderate success for this type of effort in the longer term is the effect that Nate Silver’s statistical modeling at FiveThirtyEight11 has had on the analysis of presidential elections. We would not characterize this impact as revolutionary, but we believe that it has been notable, and that his analyses and models are well-known and respected among people who think seriously about elections.

3.2 Internal forecasts

We’re experimenting with recording explicit numerical forecasts of events related to our decisionmaking (especially grantmaking), in part in connection with our interest in the topic of this grant. The idea behind this is to pull out the implicit predictions that are playing a role in our decisions, and make it possible for us to look back on how well-calibrated and accurate those are. For this grant, we are recording the following forecast:

  • The Alpha Pundit Challenge, or something like it, will have converted five or more vague predictions from pundits into numerical predictions, beyond those described in Tetlock, Alpha Pundit Challenge Proposal, by December 31, 2016: 50%

3.3 Key questions for follow up

Questions we anticipate asking Professor Tetlock as part of our follow-up on this grant include:

  • How was the funding spent?
  • What progress has been made on Adversarial Collaboration Tournaments, the Alpha Pundit Challenge, and any other relevant projects?
  • Did interesting or high profile people become involved with either project?
  • Was he able to attract significant public attention to either project?

3.4 Follow up expectations

We plan to speak to Professor Tetlock about these projects roughly every six months. We anticipate producing a written update on this grant after one or two years. If we decide at some point to make a follow up grant, we expect that we would produce a written update at that time.

4. Our process

Professor Tetlock posted on Twitter in December 2015 about the Alpha Pundit Challenge as a means of gauging interest for this project.12 In response, we contacted him to inquire about his funding situation. We discussed several possible projects with him, including the Alpha Pundit Challenge and the Adversarial Collaboration Tournaments. After considering several options and combinations of options, we decided to provide him with $500,000 in unrestricted funding.

Other options we considered included:

  • Funding the operation costs of these projects during a pilot-year.
  • Organizing and funding a small planning convening to refine Professor Tetlock’s proposal.
  • Running a large attention-generating conference.

5. Sources

DOCUMENT SOURCE
FiveThirtyEight Website Source (archive)
Good Judgment Project, Six Lessons about Crowd Prediction Source (archive)
Good Judgment website Source (archive)
Philip E. Tetlock, Publications Source (archive)
Spiegel 2014 Source (archive)
Superforecasting Website, In the Media Source (archive)
Tetlock 2005 Source (archive)
Tetlock and Gardner 2015 Source (archive)
Tetlock and Scoblic 2015 Source
Tetlock, Alpha Pundit Challenge Proposal Source