People interpret verbal expressions of probabilities (e.g. ‘very likely’) in different ways, yet words are commonly preferred to numbers when communicating uncertainty. Simply providing numerical translations alongside reports or text containing verbal probabilities should encourage consistency, but these guidelines are often ignored. In an online experiment with 924 participants, we compared four different formats for presenting verbal probabilities with the numerical guidelines used in the US Intelligence Community Directive (ICD) 203 to see whether any could improve the correspondence between the intended meaning and participants’ interpretation (‘in-context’). This extends previous work in the domain of climate science. The four experimental conditions we tested were: 1. numerical guidelines bracketed in text, e.g. X is very unlikely (05–20%) , 2. click to see the full guidelines table in a new window, 3. numerical guidelines appear in a mouse over tool tip, and 4. no guidelines provided (control). Results indicate that correspondence with the ICD 203 standard is substantially improved only when numerical guidelines are bracketed in text. For this condition, average correspondence was 66%, compared with 32% in the control. We also elicited ‘context-free’ numerical judgements from participants for each of the seven verbal probability expressions contained in ICD 203 (i.e., we asked participants what range of numbers they, personally, would assign to those expressions), and constructed ‘evidence-based lexicons’ based on two methods from similar research, ‘membership functions’ and ‘peak values’, that reflect our large sample’s intuitive translations of the terms. Better aligning the intended and assumed meaning of fuzzy words like ‘unlikely’ can reduce communication problems between the reporter and receiver of probabilistic information. In turn, this can improve decision making under uncertainty.
Genetic editing technologies have long been used to modify domesticated nonhuman animals and plants. Recently, attention and funding have also been directed toward projects for modifying nonhuman organisms in the shared environment—that is, in the “wild.” Interest in gene editing nonhuman organisms for wild release is motivated by a variety of goals, and such releases hold the possibility of significant, potentially transformative benefit. The technologies also pose risks and are often surrounded by a high uncertainty. Given the stakes, scientists and advisory bodies have called for public engagement in the science, ethics, and governance of gene editing research in nonhuman organisms. Most calls for public engagement lack details about how to design a broad public deliberation, including questions about participation, how to structure the conversations, how to report on the content, and how to link the deliberations to policy. We summarize the key design elements that can improve broad public deliberations about gene editing in the wild.
The development of technologies for gene editing in the wild has the potential to generate tremendous benefit, but also raises important concerns. Using some form of public deliberation to inform decisions about the use of these technologies is appealing, but public deliberation about them will tend to fall back on various forms of heuristics to account for limited personal experience with these technologies. Deliberations are likely to involve narrative reasoning—or reasoning embedded within stories. These are used to help people discuss risks, processes, and fears that are otherwise difficult to convey. In this article, we identify three forms of collective narrative that are particularly relevant to debates about modifying genes in the wild. Our purpose is not to privilege any particular narrative, but to encourage people involved in deliberations to make these narratives transparent. Doing so can help guard against the way some narratives—referred to here as “crafted narratives”—may be manipulated by powerful elites and concentrated economic interests for their own strategic ends.
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