- Look at computational science research possibles
Based on feedback from yesterday presentation I’m going to have a look through 11.4 of the LCA book. I’ve skipped the comparison of scenarios and moved to section 11.5
I’m struggling to figure out how to effectively present visualisations of what I’m doing.
What are some useful questions to ask in determining a target audience of presenting an LCA uncertainty analysis?
- How familiar are they with the terms used in an LCA and with the terms used in an uncertainty analysis?
- Based on this, what portions of an uncertainty analysis should be communicated?
- How do we visualise and represent these portions of an uncertainty analysis?
Representation of uncertainty is open to a wide array of interpretation. You’re balancing the probability heuristics that people have with what you’re trying to actually communicate.
Why is ‘good communication’ of risk an ambiguous notion?
It can depend on feelings, liking of material (for whatever reason), intentions, basically a range of subjectivity of the audience.
Implicit in this notion is that ‘good communication’ relies on understanding the feelings and perceptions of the audience.
Affect Heuristic
I started reading Slovic 2006 on how people judge risk with their emotions
Emotions motivating choice.
Denes-Raj and Epstein (1994) showed that, when offered a chance to win $1 by drawing a red jelly bean from an urn, individuals often elected to draw from a bowl containing a greater absolute number of red beans but a smaller proportion of them (e.g., 7 in 100) rather than from a bowl with fewer red beans but a better probability of winning (e.g., 1 in 10). These individuals reported that, although they knew the probabilities were against them, they felt they had a better chance when there were more red beans