Introduction

Careful attention to ways in which information is communicated and represented can have a significant impact on what decisions will be taken, in a way that has implications for many different professions. For example, journalists can adopt strategies for reporting disasters that facilitate causal analysis and coping in the public, or methods for representing statistical data that enable the public to properly evaluate the validity of politicians’ claims. Doctors can adopt ways of talking about uncertain treatment outcomes that will either encourage or discourage a course of action by a patient. Science teachers and statisticians can adopt graphical formats that enable complex relationships to be better understood by students and the general public. Indeed, as we will show, improving the communication and representation of information that will serve as input into a decision-making process can act as a powerful “scaffold” for optimizing human decision making.

Effective design of communication with the human decision maker depends on the characteristics of the communication channel used (spoken language, verbal text, graphical representation, etc.), and of the information-processing abilities of the recipient. We begin by noting several general features of human communication and information processing that condition the way communications should be designed, before moving on to note some particular ones. We then proceed to give examples that illustrate the importance of taking these features into account. After that, we will demonstrate how the way information is communicated can have a strong impact on judgments about causality; especially in designing external representations such as graphs, one has options about what and how much information to put in, and what to make salient. The issue of external representation becomes even more important when communicating about probabilities, which we will focus on afterwards. The general idea advanced in this chapter is that appropriate ways of communication can be used as a “scaffold” to optimize judgment and decision making: communicators can help decision makers. We will give examples of scaffolding throughout the chapter and will summarize the most important recommendations at the end of it.

In this chapter, I will review some of the potential barriers to scientific cooperation between Britain and France, drawing on my own experience as a British social psychologist who has worked in both countries, as well as in America and Germany. It is the ‘bottom-up’ view of a researcher currently working in the French university system, but who has also worked in business schools in the Grande École system in France. My focus will be on potential opportunities for and barriers to cooperation between British and French universities due to differences in organisation of education and research in the two countries. In my view, it will help the success of these partnerships if there is an understanding of the different institutional contexts on both sides. I will touch on the current reforms of the French system and their potential implications for Franco-British collaborations. I hope that these remarks will be helpful in depicting the institutional and cultural landscapes in which such European collaborations take place.

Before going further, it is important to distinguish between institutional and cultural differences. While the institutional differences are national – for example the Humboldtian view of a university in the UK, where research and teaching are integrated in a single institution, versus the bicephalous organisation of ‘research’ (CNRS, INSERM etc.) and ‘teaching’ (Grandes Écoles, universities) institutions in France – the ‘cultural’ differences are subtle and differ from discipline to discipline. At the cultural level I thus do not believe that sweeping generalisations about the ‘British’ or ‘French’ way of doing things can apply, as within each country there is often considerable sub-cultural variation between research communities in different disciplines. For example, my personal experience suggests that, on the whole, French Economics, Neuroscience and Artificial Intelligence are much more internationalised (and recognised abroad) than French Psychology. One implication of this is that it is much easier for the former disciplines to build international research networks, which can compete for funding in cross-national funding programmes (the ANR–ESRC Franco-British research programme, European Research Area, FP7, etc.). One of the objectives of this chapter is therefore to analyse why some disciplines are more internationalised than others, and to analyse the implications for policy making.

In this chapter, I will review some of the potential barriers to scientific cooperation between Britain and France, drawing on my own experience as a British social psychologist who has worked in both countries, as well as in America and Germany. It is the ‘bottom-up’ view of a researcher currently working in the French university system, but who has also worked in business schools in the Grande École system in France. My focus will be on potential opportunities for and barriers to cooperation between British and French universities due to differences in organisation of education and research in the two countries. In my view, it will help the success of these partnerships if there is an understanding of the different institutional contexts on both sides. I will touch on the current reforms of the French system and their potential implications for Franco-British collaborations. I hope that these remarks will be helpful in depicting the institutional and cultural landscapes in which such European collaborations take place.

Before going further, it is important to distinguish between institutional and cultural differences. While the institutional differences are national – for example the Humboldtian view of a university in the UK, where research and teaching are integrated in a single institution, versus the bicephalous organisation of ‘research’ (CNRS, INSERM etc.) and ‘teaching’ (Grandes Écoles, universities) institutions in France – the ‘cultural’ differences are subtle and differ from discipline to discipline.

Most psychologists conceive of judgment and reasoning as cognitive processes, which go on “in the head” and involve intrapsychic information processing (e.g., Kahneman, Slovic, and Tversky, 1982; Nisbett and Ross, 1980). Although it is incontestable that processes of attention, memory, and inference underpin judgment and reasoning, psychologists have perhaps overlooked the extent to which these mental processes are governed by higher-level assumptions about the social context of the information to be processed. On the other hand, philosophers have in recent years drawn attention to the extent to which reasoning from ordinary language is shaped by the nature of social interaction and conversation (Austin, 1962; Grice, 1975; Hart and Honoré, 1959/1985; Mackie, 1974; Searle, 1969; Strawson, 1952). These higher-level assumptions can determine what we attend to, which memories we search, and what kinds of inference we draw.

Consider the way the word family can be differentially interpreted according to context and thus lead to seemingly inconsistent judgments expressed in a conversational exchange (cf. Strack, Martin, and Schwarz, 1988):

1. Q. How is your family?

2. A. Fairly well, thank you.

A married man might reply this way if he considers that his wife has recently been saddened by the loss of a close friend but that his two children are in good form. The respondent interprets family to mean the wife and kids.

While one can argue that full rationality is the adequate normative framework to evaluate the reasoning of homo scientificus, as science should spare no effort to validate causal hypotheses and to identify correct explanations, I shall argue that ordinary causal reasoning does in fact have other goals – particularly those of cognitive economy and social co-ordination. This translates into a concern with bounded rationality – using heuristics that are simple but smart; and social rationality – using assumptions about conversation which enable speakers and listeners to co-ordinate their efforts around the most relevant explanation. Understanding such concerns can help explain why homo pragmaticus deviates from scientific criteria for causal reasoning while being rational in his or her own terms. It can also help us understand what we need to do to help people reason ‘scientifically’ about causes, where we consider that to be important. Indeed, understanding the pragmatic rationality of human inference processes should help us better understand why they are ‘sticky’, and sometimes resist reformation into ‘fully rational’ modes of thinking which are principally adapted to doing science. I apply this pragmatic analysis to three domains of causal judgement: learning of causal relations; causal hypothesis testing; and discounting vs. backgrounding of causes in explanations.

Introduction

In this chapter I will be primarily interested in how scientific rationality may differ from pragmatic and social rationality with respect to causal thinking.