- 13:30 - 14:30
- Professor Michael Siegrist
- Baines Wing SR (4.12), University of Leeds
- Who can attend:
- This event is open to University of Leeds staff, students, alumni and external guests who have an interest in the topic.
'Symbolic Information Causes Biased Decisions'
As part of the Centre for Decision Research's seminar series, Professor Michael Siegrist will be discussing symbolic information causing biased decisions.
He will be discussing the below:
"In assessing the outcomes of decisions, people often rely on the symbolic information while neglecting other crucial information. People may be especially prone to rely on this information on topics that are subject to social norms, such as environmentally friendly behavior, environmental risks or risks for humans. In one experiment, participants were presented with two energy consumer descriptions. One contained a positive symbolic significant attribute (e.g., driving a Toyota Prius) and a negative symbolic neutral attribute (e.g., covering 28,700 km); for the other one, the reverse was true (e.g., driving an SUV and covering 11,400 km). As expected, participants were influenced by the symbolic information and this resulted in biased decisions. In another set of experiments, we could show that negative outcomes are more negatively perceived if caused by humans compared with nature. Perceiving gene technology as unnatural may be one reason why the risks and the benefits associated with this technology is perceived differently compared with the risks and the benefits associated with conventional breeding technology. The results of our experiments demonstrate that symbolic information may cause biased decisions. These biased decisions have been observed in different contexts, and they may result in non-optimal decisions."
This event is hosted by the Centre for Decision Research, Priestley International Centre for Climate, the Sustainability Research Institute, and the ESRC Centre for Climate Change Economics and Policy
For further information please contact research.LUBS@leeds.ac.uk