Making Numbers Meaningful

Much of our everyday activity depends on our ability to comprehend and make decisions based on numerical information. However, many people struggle with innumeracy, the numerical equivalent to illiteracy. A 2014 report for the National Numeracy charity has estimated the cost of low numeracy in the UK to be £20 billion per year.

The proposed project shifts the burden of innumeracy from the consumer of numerical information to the communicator, recognising the importance of the external presentation of numerical information in language and graphs, and how particular communicative strategies can be unintelligible, biasing, or outright distorting the truth.

The project's starting point is that in order to combat innumeracy, we first need to understand what it is that people actually do with numerical communication on a daily basis. For this project, I will assemble an interdisciplinary team of researchers to conduct the so-far largest investigation into numerical communication across multiple communication channels and multiple forms of media.

The proposed project innovates by marrying existing research in psychology, education research, and statistics, with methods and insights from linguistics and computer science, thus transforming the study of numerical communication into a thoroughly interdisciplinary endeavour.

The project takes the insights generated from the large-scale descriptive analysis of naturally occurring language back into the lab, so that experiments into the most effective and transparent communication strategies can be modelled closely after numerical communication "in the wild", thus bridging laboratory conditions with natural conditions. These experimental investigations into the cognitive effects of particular presentational formats will be used to develop automated ways of classifying the numerical accessibility of documents.

The research will make significant academic impact by showing how numerical communication depends on multiple communication systems that interact with each other and therefore need to be studied in an integrated fashion. The project will also impact several different academic fields by innovating methodologies via the use of machine learning tools to automatically extract numerical information from language and graphs.

The proposed research has wide-ranging benefits to non-academic stakeholders. This impact will be realised by working closely together with data analysts from commercial businesses on innovative ways of making pressing societal issues (such as climate risks or health risks) more accessible to people with low numeracy. In addition, the project aims to improve the training of data analysts so that more attention is paid to matters of transparent communication.

The long-term goal is to establish a lasting legacy of data analytics training that leads to improvements in how numerical information is communicated across a large range of data-dependent business sectors.