782 Decision-making Biases and Information Systems Marita Turpin* Niek du Plooy** *Centre for Logistics and Decision Support CSIR Pretoria, South Africa Email: mturpin@csir.co.za **Department of Informatics University of Pretoria Pretoria, South Africa Email: nfduplooy@absamail.co.za Abstract Information systems and in particular decision support systems have been developed to supplement human information processing and to assist with decision-making. Human decision-making is facilitated by the often unconscious use of heuristics in situations where it may not be possible or feasible to search for the best decision. Judgemental heuristics have previously been found to lead to biases in decision-making. When information systems are used as decision aids, they may have an influence on biases. This study investigates the role of information systems in introducing, reinforcing or reducing biases. It was found that information systems have the ability to introduce new biases and to reinforce biases. Information systems can also reduce biases, but this requires innovative thinking on the way information is represented and the way human decision-making processes are supported. It was also found that in the real world, as opposed to the laboratories where biases are usually measured, other constraints on rational decision-making, such as politics or data errors, can overshadow the effects of biases. Keywords Biases, decision-making, information processing, information systems. 1. INTRODUCTION Information systems and in particular decision support systems have been developed to supplement human information processing and to assist with decision-making. In order to develop systems that support decision- making, the process of decision-making itself needs to be better understood. A number of decision-making models exist, as are described in eg. Keen and Scott Morton (1978) and Huber (1981). Of these, the rational model (eg. Simon 1977) is believed to be the norm or ideal. More descriptive theories are those of bounded rationality (Simon 1979), the garbage can model (Cohen et al. 1972), the organisational procedures view (March 1988; Krabuanrat and Phelps 1998), the political view (Pfeffer, 1981) and the logical incrementalist view (Das and Teng 1999; Lindblom 1959). Simon’s (1979) model of bounded rationality describes how people ‘satisfice’ in order to reach good enough rather than optimal decisions. In the process, they make use of judgemental heuristics. These heuristics are useful but can lead to biases in judgement or decision-making (Tversky and Kahneman 1974; Hogarth 1980; Hammond et al. 1999; Russo and Schoemaker 2002). When information systems are used to support decision-making, what effect do they have on biases? Do they reduce or enlarge biases, and can they introduce new biases? These questions are the concern of this paper. The remainder of the document is structured as follows. Heuristics and biases are introduced in the context of decision-making. Following this, different kinds of biases are discussed, as well as research on debiasing. The next section considers biases in an information systems context. After speculating on the role of information systems with respect to biases, the literature on biases and information systems is summarised, classified and analysed. Subsequently, a case study is discussed where exception reports have been done for a government department. The occurrence of biases on the reported project is investigated.