Humans and Numbers

Numbers are everywhere. We use them to count and measure, to communicate facts, and to make sense of our experiences and the world around us. Although numbers often represent something real and tangible, it is up to us as humans to interpret and use them. How we do this differs from person to person, between contexts, and over time. Understanding how and why these differences occur is of critical importance for academics, science communicators, and policy makers. For example, when presented with statistics such as the risks of Covid-19 or self-tracking data, how do we interpret this information? Do we trust it? Does it affect how we behave? These questions are not only affected by our own numeracy but also by our backgrounds and experiences, cultures and communities, and the era we live in. The interdisciplinary perspective of this project enables a deeper understanding and varied ways to address the complexities arising when humans interact with numbers.

Building on ideas generated during an IAS supported Research Development Project in 2022/23 and workshops on Statistical Literacy and Science Communication, this interdisciplinary project has three cognate research themes – each with its own set of questions and proposed outcomes.

Research Themes

1) Expertise and uncertainty:
The aim of this theme is to understand how individuals think and subsequently behave when presented with information from expert sources. For example, how does our understanding and behaviour change when statistical knowledge is presented as evidence from practitioners and professionals to the news and media. This knowledge can range from the chances of rain to the risks of intervention in maternal health and genocidal deaths. Furthermore, what precisely is an expert and has public trust in experts waned in recent years?
When considering expertise and their advice, it is natural to ask how much our prior beliefs – which are influenced amongst other factors by our political views and confidence with numbers – affect how we judge and view statistics and expert knowledge. Broadening this, what happens when we mix numbers with qualitative characterisations of uncertainty? Scientists cannot hope to model everything mathematically so how do we cope with that shortfall, and does the language used and the potential ambiguities feed into unease with using such information?
Of course, expert judgement touches policy making, guides industry decision making and is brought to bear in courts of law. This raises significant questions from a legal and ethical framework: do people understand these risks that are presented to them? There have been multiple occasions in the past where statistical evidence has been misrepresented in court leading to a partial ban on its use.

2) The Quantified Self:
This theme seeks to understand how humans view, feel, and understand data about the self. Self-tracking data is often associated with wearable technology that tracks individuals’ performance when exercising or taking part in sport. GPS watches and digital self-tracking devices (DSTDs) create dyadic and collective relationships between individuals and data. Relatedly, self-tracking devices have been used in health ranging from calorie counting to tracking sleep quality. The quantified self is becoming
increasingly used in businesses which often feature as a part of Knowledge Performance Indexes (KPIs) such as tracking personal sales or customer satisfaction. This raises questions that we argue can only be addressed fully when incorporating interdisciplinary perspectives (e.g., Psychology, Sociology, Exercise Sciences, Law) such as how individuals feel and understand these measures? How is mood affected if the data suggest that they have failed to meet targets – whether set internally or externally? Is the quantified self a recent phenomenon – driven by new technologies – or is it simply an ongoing extension of the story of humanity using numbers to make sense of the world? How is self-tracking data stored and used by businesses, and who gets access?

3) Statistical literacy and the media:
This final theme challenges current research perspectives of statistical literacy in society and offers novel avenues from an interdisciplinary perspective that address (a) how it affects key groups in society (e.g., policy decision-makers, journalists), and (b) whether and how it should be integrated into wider curricula (e.g., in schools, universities). Statistical literacy, broadly defined as the ability to interpret, critically evaluate, and communicate statistics, is essential to navigating not only the news, but arguably today’s society. Statistical literacy is increasingly of concern in the broader society as well as in those groups – such as journalists – who shape how expert knowledge is disseminated.
One argument is that journalists may knowingly spread misleading information to gain readership. However, if journalists have little or no understanding of how numbers are made (e.g., the design and analysis of scientific data) and how they can go wrong (e.g., the limitations of scientific research), then it is possible that they unintentionally report information that is misleading to their readers.

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Events and Activities: