What Is Adversarial Collaboration?

Adversarial collaboration is a scientific approach that involves researchers with opposing theories working together to design and conduct experiments. This helps to resolve differences, and build new knowledge. Impartial collaborators sometimes facilitate this process, coordinating the research, moderating disputes, and ensuring reliable data collection. The goal is to foster productive discussions based on robust evidence and, thereby, accelerate the generation of new knowledge.

 

This method emphasizes collaboration, transparency, and a commitment to resolving disagreements, even if the researchers ultimately reach different conclusions about the results.

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Key Features of Adversarial Collaboration:

• Jointly Designed Experiments: Researchers from opposing perspectives collaborate to design experiments that address their points of contention. This ensures the research is relevant to their debate, with both parties having a vested interest in the outcome.

• A Commitment to Collaborate: All parties recognise that disagreements exist, but commit to collaborate openly towards finding a solution. This may involve regular discussions and making an effort to understand all perspectives.

• Open Data Sharing: Data collected during adversarial collaborations is often shared publicly, allowing other researchers to review the results and conduct their own analyses. This openness promotes transparency and speeds up the research process.

• Joint Authorship: Ideally, all participating researchers are listed as co-authors on resulting publications, recognizing their contributions and fostering a spirit of collaboration.

 

Why Structured Adversarial Collaboration?​

The Templeton World Charity Foundation (TWCF) developed the Structured Adversarial Collaboration (STAC) process to address challenges and advance consciousness research.

 

Some key motivations include:

• In 2017, TWCF found numerous competing theories in consciousness research, with limited resources to support them all.

• Distributing funds equally risked diluting the impact, while prioritizing a few theories could skew the field. Limited funding from other sources worsened this dilemma.

• Traditional open grant proposals were insufficient due to inherent biases and inefficiencies in the application process.

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The STAC process aims to accelerate testing and challenging theories of consciousness by fostering collaboration between researchers. The main departure from traditional Adversarial Collaboration is that STAC involves a structured process and oversight from a funding agency. This makes it easier to standardize best practices and allows researchers to secure resources more effectively.

 

How Does Adversarial Collaboration Work?

The acceleratingresearch.org platform features five research projects that follow the STAC model. They use different approaches and methodologies but all retain the same commitment to collaboration and progress. 

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The process begins with a workshop where proponents of different theories come together to discuss their ideas and identify key points of disagreement. Next, they develop an experimental design to test the conflicting predictions of their theories.

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A key element of STAC is preregistration, where hypotheses, methods, and analysis plans are specified in advance to ensure transparency and reduce bias. Ideally, experts with a broad range of methodologies are involved to mitigate potential biases and increase the validity of the findings. To enhance objectivity, experiments can be conducted by a neutral third party if all team members agree. 

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The five projects featured on this platform are set to yield large datasets based on sophisticated methodologies. These data will be analysed to test the predictions made by each theory leader. Although none of the tests were designed to prove a theory, they all have the potential to challenge at least one theory. We hope this critical evidence will advance the field by ruling out explanations that don’t hold up against the data. Importantly, failure to challenge a theory doesn't necessarily mean it is correct—the experiment may simply not have been designed to expose its weaknesses.