---
title: Manifesto test
tags: manifesto
---

**<center>Why citizens need reliable knowledge</center>**

Many of the most pressing challenges societies face today—from climate change to global pandemics—require large-scale, collective decisions informed by the best available evidence. It is only when public beliefs are built on reliable knowledge, rather than poorly informed opinions, that we can successfully address these challenges. However, there are barriers to effective science communication, especially in rapidly evolving crisis situations or when evidence conflicts with political or commercial interests.

**Barriers: social media**
Social media notoriously prioritises emotion above evidence-based information and it is especially vulnerable to very active, extreme voices, which can skew users' perceptions of the opinion landscape. The rejection of authoritative sources can also create an "epistemic vacuum," leading people down the rabbit hole of conspiratorial sources and low-credibility content as they seek alternate sources and explanations.

**Barriers: misinformation**
Organized efforts to misinform or confuse the public, or to propagate conspiracy theories, endanger informed public discourse. For example, disinformation lobbying groups can disrupt science communication such that collectively supported opinions become treated as equal to collectively supported evidence. As a result, they restrict citizens from implementing scientifically sound solutions. Against organised disinformation campaigns, individual scientists are poorly matched, as they are vulnerable to direct attack from those opposed to specific types of scientific data.

**Barriers: communicating as individuals**
There are further disadvantages to scientists communicating as individuals. First, some scientists may have views that are at odds with the scientific majority, but these lone voices can still alter public perceptions of consensus, portray an erroneous balance, or paint an inaccurate picture of the controversies surrounding a particular issue. Second, incentives for individual science communication tend to be focussed on achieving short-term goals, such as generating media coverage, rather than on developing trust or achieving specific behaviour- or policy-related outcomes. This lack of strategic planning can put scientists at a disadvantage compared to others who are more adept at communication strategy. Finally, the pressure to publicise one’s findings can in some cases lead to scientific findings being presented to the public as facts even where the research may have important limitations such as methodological weaknesses and small effect sizes, or where it may not yet have undergone peer review or been replicated.

**Why collective intelligence can help**

We will be better able to counteract misinformation and contribute to an informed public if we can leverage the pooled expertise of a large number of scientists. A [collective intelligence approach](https://www.nesta.org.uk/toolkit/collective-intelligence-design-playbook/) to science communication would use expert consensus to weigh information. In public debate, this may allow for more decisive conclusions to be drawn since greater expert consensus typically reflects the quality of the evidence supporting a particular position and the degree of certainty around a hypothesis. Communicating scientific consensus can thus help boost public acceptance of scientific findings and support for action, even across partisan lines. Furthermore, scientists, like all individuals, need to avoid cognitive biases when seeking out evidence, including the tendency for confirmation bias. This is particularly important when evidence-seeking in an environment where the rapid pace of scientific production outpaces the ability to critically evaluate it. The judgements and decisions of a diverse collective will likely be less prone to bias and perceived to be less biased - a quality that is often considered important by policymakers and which should therefore facilitate communication with them.

**<center>What should science communication as collective intelligence look like?</center>**

**It should communicate the strength of the evidence**

Science should not be viewed as an all-or-nothing process in which hypotheses are either entirely disproved or entirely supported. Instead, the prominence given to different positions, both in terms of attention and importance, must be proportionate to the strength of the evidence supporting them. Collective intelligence in science communication should function as a source of reputable information that establishes the strength of evidence and variability of study findings, through evidence syntheses such as meta-analyses, systematic reviews, narrative reviews, and expert surveys.

**It should be honest about uncertainty and error**

Uncertainty and deliberation are integral to the scientific process and should be communicated openly, as should methodological constraints and contentious theories. Although politically-motivated actors may weaponize uncertainty to undermine scientific evidence, communicators can overcome those attempts by being clear about sources and extent of uncertainty. To aid this, evidence syntheses should integrate and communicate uncertainty in and across scientific studies as well as explain the causes and types of uncertainty. In crisis situations, characterised by high uncertainty, experts will disagree, and in these cases it may be inappropriate to communicate a single, aggregate scientific conclusion.

**It should be diverse**

To ensure accurate evidence synthesis, a scientific collective must be epistemically diverse and must guard against bias. Scientific research is a complex iterative process that requires methodological variety. As such, consensus formation should not be hasty but should instead genuinely reflect the breadth of views brought by different disciplinary perspectives and life experiences. Such diversity has the additional advantage of enabling more groups to identify with the scientific collective, rather than perceiving scientists as an out-group.

**It should be open to alternative perspectives**

A collectively intelligent science communication system must allow for evidence-based dissent. This should take a constructive form: when scientists engage with stakeholders, all parties should first seek to understand the other party's norms, values, power structures, and experiences. All parties should also be clear about the purpose of the interaction, and they should be willing to persuade, and be persuaded by, the strength of the other's arguments. New incentives should promote listening to, engaging with, platforming, and amplifying the views of others.

**It should be transparent**

Transparency allows people to see how decisions were made based on the available information and to understand how applying different personal values would have affected the decision. Scientific transparency can be improved in several ways – through pre-registration and openly sharing data and analysis codes, by communicating the degree of scientific consensus, and highlighting how single studies relate to the overall body of scientific evidence. Finally, when like-minded scientists collectively publish a declaration about a specific proposition, the process by which this statement was reached should be thoroughly scrutinised to minimise bias.

**It should build trust**

Building trust in science should be a priority for future emergencies. To this end, participatory research (where scientists develop research in collaboration with stakeholders) could help promote trust between the scientific community and the public.

**It should be motivated by the common good**

Science communication must be viewed as more than an opportunity to promote one's own research or preferred scientific viewpoint. During an emergency, the scientific community should re-prioritise and coordinate their communication efforts towards activities most likely to protect communities from harm.

**It should be easy to understand**

Scientific communication, should foster a shared understanding of scientific methodology. Simpler language can help achieve this, as well as reach larger audiences and promote multidisciplinary knowledge sharing and knowledge retention.

**<center>Meeting the challenges of science communication as collective intelligence</center>**

To address these challenges, science communication needs to embrace innovation. We suggest scientists need to focus on the following:

* Scientists as a collective need to define what constitutes expert consensus, as opposed to just group opinion.
* More research is needed to determine how audiences perceive and understand sources of scientific uncertainty, so that scientists can communicate this effectively to society.
* Researchers and social media businesses should continue to develop powerful artificial intelligence tools for sifting through large datasets, identifying misleading content, and flagging it for users.
* Systems that allow for comments on published research could enable experts in the field to draw on scientific consensus to provide ongoing re-evaluation of peer-reviewed publications. Machine learning algorithms that monitor new publications could be used to keep evidence syntheses up to date.
* Online platforms could be used to help facilitate rapid knowledge exchange between scientists as well as discussion of evidence, and consensus formation.
* A “machine of scientific accumulation” might be constructed to depict the global state of scientific evidence over time. As further data and evidence are generated in support of or against certain policies, the global state variable could indicate drift diffusion processes demonstrating the amount of evidence and confidence among the scientific community. This could assist scientists in making specific policy recommendations.
* Scientists could develop more strategic communication programmes, similar to those used in public relations.
* To minimise risks of polarisation, entrenchment, and degeneration of discourse, new methods are needed to enable scientists to prioritise ideas, evidence, and arguments.

As a starting point, in Table 1, we provide some examples of where collective intelligence has been harnessed in science communication efforts.

_Test red propositions_

## Instructions
Blah blah blah add stuff about the process of turning long draft into short form.

We ask you to make **TWO** votes.
1. Whether you **endorse** the proposition.
* Cast your endorsement for the propositions HERE (Not done, see link below for mock example)

2. Whether you believe it should be **included** in the short-form manifesto.
* Cast your vote for inclusion of propositions [HERE](https://pol.is/7ejyarvven)

## Propositions
Here you can read the propositions and more details that support it. These are drawn from the [long draft](https://docs.google.com/document/d/1TQfGDkvAMjF7pGuvenlzPf5KW2UwJgzqrckeDV2wFKU/edit).

### 1. It is only when public beliefs are built on reliable knowledge, rather than poorly informed opinions, that we can successfully address pressing societal challenges.

:::spoiler Context
Many of the most pressing challenges that societies face today-- from climate change to a global pandemic--require large-scale, collective decisions informed by the best available evidence. It is only when public beliefs are built on reliable knowledge, rather than poorly informed opinions, that we can successfully address these challenges.
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### 2. Organised efforts to misinform, sow public confusion, or advance conspiracy theories threaten informed public debate and therefore prevent citizens from implementing scientifcally-grounded solutions

:::spoiler Context

In many situations in which evidence is in conflict with political or commercial interests, public discourse is polluted by organized efforts to misinform, sow public confusion, or advance conspiracy theories (APCO Worldwide, 2021; Graham et al., 2020). Those efforts can severely threaten informed debate among citizens and policy makers. For example, there is little doubt that organized climate denial has delayed mitigative policy action (Lewandowsky, 2020, 2021). The coronavirus pandemic has both exacerbated and exposed many of the dangers of science-related misinformation. It is now known that coordinated campaigns kick-started the hoax that 5G Internet causes the coronavirus (Graham et al., 2020), and that at least one libertarian think tank with a history of climate denial has funded opposition to social distancing measures to control the pandemic (Lewandowsky, 2021; Bragman & Kotch, 2021). Anti-vaccination misinformation is increasingly embedded within broader conspiracy narratives such as ‘The Great Reset’, pushing the idea that vaccinations are part of a plan to exert population control (APCO Worldwide, 2021).

From a policy and public health perspective, this means that effective public health measures have become increasingly contested (Vériter et al., 2020), preventing some citizens from implementing scientifically-grounded health measures (Posetti & Bontcheva, 2020; plus include original publications). Furthermore, we now know that the COVID-19 pandemic has been exploited by state-sponsored media, and far-right networks that are the key drivers of online misinformation by means of orchestrated, strategic information operations (ISD, 2020; Starbird et al., 2019) In other words, we now know that disinformation often arises from well-organized collaborative work–not just in the context of COVID (Starbird et al., 2019) but also in the context of climate change (Lewandowsky, 2021b), tobacco control, and numerous other instances in which scientific evidence threatened vested interests (e.g., Oreskes & Conway, 2010).

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### 3. Science communication needs to harness collective knowledge and expertise of many scientists to combat misinformation and inform citizens

:::spoiler Context
This manifesto lays the foundation for a collective intelligence view on science communication that harnesses the collective knowledge and expertise of large numbers of scientists worldwide, thereby providing high-quality information, and engaging with stakeholders, thereby delivering more effective countermeasures to the spread of mis- and disinformation, and ultimately contributing to an informed citizenry.

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### 4. Those who oppose adverse scientific evidence target the scientists communicating as individuals rather than the whole scientific field.

:::spoiler Context
A collective intelligence approach to science communication provides a remedy to the perils and pitfalls of the traditional “one-person reporting” model. One pitfall of communication by single individuals is that opponents can pursue the “Serengeti strategy” (Mann, 2015), which refers to the idea that in the same way that lions in the Serengeti seek out individual zebras that are left behind or stray from the herd, vested interests and political operatives faced with adverse scientific evidence often target individual scientists rather than take on an entire scientific field at once. It is for this reason that individual prominent scientists often become a focus of attacks by contrarians. Perhaps the most prominent recent example involves Dr Anthony Fauci, the Chief Medical Advisor to the President of the United States, who has been relentlessly and personally attacked by political operatives who objected to pandemic-control measures (Korecki & Owermohle, 2021).

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### 5. Lone voices can distort public perceptions of consensus and present a false balance/create a misleading picture of controversy on issues.

:::spoiler Context
Another pitfall of individuals communicating on their own is that lone voices may distort perceptions of a scientific consensus. For too long, media coverage of scientific evidence on topics such as climate change or vaccinations has been falsely “balanced”, lending equal weight to a position that is supported by overwhelming evidence and by the majority of scientists, and a position that is supported by little or no evidence. Although mainstream media has largely moved beyond false balance in recent years, (Bruggemann & Engesser, 2017), this strategy has succeeded in maintaining public uncertainty about the scientific consensus around anthropogenic climate change or the vaccine-autism myth (Dixon & Clarke, 2012; Koehler, 2016). (Although the illusion of false balance may be appearing again in the COVID-19 context.)

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### 6. Communicating consensus can influence public attitudes in favour of science, even across partisan lines.

:::spoiler Context
Another danger in single individuals communicating science lies in them (intentionally or not) misrepresenting an actual consensus, or being perceived as misrepresenting a consensus. A collective intelligence approach to science communication, in contrast, weights information by the strength of evidence: Rather than perceiving evidence as just “one more piece of information” in the debate, evidence that is supported by the consensus of the collective can be seen as decisive (e.g., Imundo & Rapp, 2021). A collective intelligence approach to science communication therefore delivers evidence that can reliably inform the actions of citizens and governments alike.

There is ample evidence that collective communication, embodied in messages that reflect a scientific consensus, can reliably shift the public’s attitudes and strengthen calls for policy action in climate change (van der Linden et al., 2019), COVID-19 mitigation (Kerr & van der Linden, 2021) and vaccinations (van der Linden et al., 2015). Communicating a consensus can be effective even across partisan lines. It has been shown that underscoring the consensus on climate change can be particularly effective for individuals who tend to be predisposed towards rejecting scientific evidence for climate change (Lewandowsky et al., 2013).

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### 7. Science communication has thus far leveraged collective intelligence to inform, educate, engage, and network with the public.

:::spoiler Context
In its broadest form, CI can be seen as the process of collaborative problem solving and collective decision making, with the aim to produce outputs that are better than the sum of its parts. Before unpacking the general concept of CI any further, it is important to realize that research on CI spans a wide spectrum of research fields, such as psychology, biology, management, economics, sociology, political science, and computer science (Malone & Bernstein, 2015). Furthermore, applications of CI range across diverse domains, such as crowdsourcing medical diagnostics (e.g., The Human Diagnosis Project), crowdsourcing geopolitical forecasting (e.g. the Good Judgment Project and its "Superforcasters"), citizen science in astronomy and beyond (e.g., Zooniverse), collaborative writing and editing on wikipedia, or collective deliberation in political processes.

Examples of collective intelligence in the context of science communication can be drawn from various sources and disciplines (Suran et al. 2020). An attempt is made here to present tangible, balanced, and accessible collective intelligence examples from the science communication area that help inform, educate, engage, and network the public and use different channels to communicate their important messages. These systems and platforms enable, for instance, problem-solving, decision-making, and knowledge-sharing.

Some recent examples include guidebook creation, information dissemination to assist policy-development, and environmental education and solution-generation. These are only a few of the important issues science communication brings to the public by leveraging the strengths of collective intelligence. These examples illustrate the collaborative nature of science communication and how collective intelligence can be used to highlight the positive power of scientific knowledge, people working together, and engaging the public.
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<br><br>
_~~Here (below) I ran into the problem that pol.is only does 140 characters (after the first seed comments, which can be longer). So I split one sentence into 2 but then it was from the same text. Maybe that means I need to re-think what the main point ought to be!~~_ Ignore this, I found out what I was doing wrong!

### 8a. Collective intelligence in science communication should be a form of universally distributed intelligence, constantly enhanced, coordinated in real time.

### 8b. Collective intelligence in science communication should result in the effective mobilization of skills, embedded in and facilitated by suitable socio-technological systems.

:::spoiler Context

In the context of science communication as a collective intelligence enterprise, we believe it is useful to start out thinking about CI as a "form of universally distributed intelligence, constantly enhanced, coordinated in real time, and resulting in the effective mobilization of skills" (Levy, 1997), embedded in and facilitated by suitable socio-technological systems (e.g., wikis, forums, deliberation platforms).

Those building blocks revolve around four key questions about any CI-system, namely, "who?" (the "staff") is doing "what?" (goal), exactly "how?" (process) and "why?" (motivation). As an example for the process, interactions between crowd members can be dependent (i.e., everybody can see what others are doing) or independent (i.e., everybody works independently, at least initially). As alluded to further above, which configuration is preferable will depend on the specifics of the task.

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### 9a. Science communication should be an intentionally and deliberately system designed to enable collaborative problem solving and collective decision making

### 9b. Science communication as collective intelligence should produce tangible artefacts to communicate information and engage with the public.

:::spoiler Context
In the context of science communication, we think it is useful to focus on those forms of collective behavior that have been intentionally and deliberately designed to produce successful and tangible "artefacts" through collaborative problem solving and collective decision making ("deliberate CI"). In this view, wikipedia is a form of deliberate CI because the collective creates and refines wikipedia articles on particular topics. In contrast, the collective behavior of pedestrians is not a form of deliberate CI, notwithstanding how intelligent the emergent behavior might often be or how intelligent the urban planning supporting it might have been. Science communication, in one way or another, needs tangible artefacts to communicate information and to engage with the public (e.g., data visualizations) .

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