1. Victoria University of Wellington.
How the moral quality of actions affects judgments of cause and blame: When intentions matter.
Briar Moir
John McClure
Victoria University of Wellington.

2. Consider two types of cause
Intentional Actions
‘A man deliberately set fire to an area of forest. A stranger came by and intentionally fanned the flames.’
Physical events
‘A lightning strike set fire to an area of forest. A breeze came through and fanned the flames.’

3. How do people perceive these two types of cause?
Legal theories (Hart & Honore, 1985)
Human actions are “special”.
Abnormal physical events: violate the natural order
Psychological Theories
Goal based - Exhibit properties of equifinality (Heider, 1958)
Evolutionary - More adaptive (Keysers & Gazzola, 2007)
Social Functionalists - More controllable (Tetlock, 2002)
Covariation - More effective at producing the outcome (Spellman, 1997)

4. Research on Attributional Judgments
Single Target Event
Outcome
Causal Chain: Multiple Target Events
Outcome
Distal Event
Proximal Event
Negative Outcome
Human Action
Physical Event
McClure, Hilton & Sutton (2007):
Voluntary events are judged better explanations than physical events.
Irrespective of position in sequence.
Lagnado & Channon (2008):
Intentional actions rated higher than unintentional actions or physical events.
Later events rated higher than earlier events.

5. Intent vs. Outcome
Is it intent per se or is it because the outcome is negative?
e.g. An arsonist lights a forest fire, homes are destroyed.
What about actions that were positively motivated or positive outcomes?
e.g. A conservation department officer lights a burn-off, homes are saved.
Asymmetries between positive and negative outcomes.
e.g., Patient recovers or patient dies (Alicke, Rose, & Bloom, in press).
Asymmetries between positive and negative motives
e.g., Man hides anniversary present or hides cocaine. (Alicke, 1992).

6. Question:
How do peoples’ judgments differ with positive actions and good outcomes?
If previous theories apply:
Positive motives would also be rated better explanations than physical events.
Judgments higher for chains leading to negative rather than positive outcomes.
Proximal
Event
Positive Motive
Negative Motive
Physical Event
Positive Outcome
Negative Outcome

7. Scenario Structure: Distal Event-Type
Proximal
Physical
Event
Positive Motive
Negative Motive
Physical Event
Outcome
Positive Motivation
A Conservation Department officer deliberately set fire to an area of forest. His goal was to cause a burn-off to prevent a larger fire from spreading.
Negative Motivation
An arsonist deliberately set fire to an area of forest. His goal was to cause a larger fire to spread.
Physical Event
A lightning strike set fire to an area of forest.
(adapted from McClure et al., 2007; Hilton et al., 2010)

8. Scenario Structure Positive Outcome Proximal Event Negative Outcome
Distal Event
Negative Outcome
Proximal Physical Event
A strong wind developed which fanned the flames.
Positive Outcome
These events prevented the larger fire from reaching the nearby town, saving dozens of homes.
Negative Outcome
These events led to the larger fire reaching the nearby town, destroying dozens of homes.

9. Negative Outcomes: Cause ratings and positive actions?
Negative Actions and physical
events:
Replicates earlier findings.
Positive Action:
Opposite pattern of results.
Challenges:
Heider, and Hart & Honore
Supports:
Alicke & Knobe
Moral evaluations determine judgments of cause?

10. Cause Ratings and Positive Outcomes.....Motives don’t matter?
3-way interaction Distal & Proximal Cause * Motivation * Outcome F(2,254) = 6.77, p = .00

11. Ratings of Blame
None of the theories are able to fully explain all of the findings.
3-way interaction Distal & Proximal Blame * Motivation * Outcome F(2,254) = 9.30, p = .00

12. Implications When things turn out badly, intention is important.
But, when things turn out well, intention doesn’t matter.
Or, are the effects due to:-
Do chains with positive or negative outcomes have a different logical structure?
Presence vs. absence of outcome effects?
e.g., lives lost vs. lives saved.
Is the baseline outcome probability higher for positive rather negative outcomes?
Conceptual differences between events
Abnormal vs. normal events e.g., strong wind vs. tornado.
Facilitating vs. inhibiting causes.
Measurement issues

13. Addressing the issues:
Measures:
Praise / Blame (Alicke, Rose & Bloom, 2010)
Responsibility (Alicke, 1992)
Punitiveness (Tetlock et al., 2007)
Probability Task (Mandel, 2003)
Counterfactual Reasoning Task (Mandel, 2003)
Scenario Revisions:
Distal and proximal physical events met legal criteria for abnormality, e.g., ‘a strong wind’ became ‘a tornado’ (Moore, 2009).
2. Background condition added
e.g., ‘A forestry town was surrounded by wildfires and had been completely cut off from outside help.
Events ‘resulted in’ rather than ‘led to’ or ‘prevented’ the outcome.
4.Removed emotive and normative descriptors of actor.
e.g., ‘an arsonist’ or ‘a conservation department officer’ became ‘a man’

14. Issue 1: Baseline Outcome and Chain Structure Effects
Outcome effects:
Prior to either event occurring, people expect things to turn out well.
When both events occurred, people see a negative outcome as more probable than a positive outcome.
Chain Structure: People judge a sequence of events very differently depending on how things end.
Outcome* Temporal Order * Event-type, F(4, 702) = 9.81, p < .001.

15. Issue 2: Something about the events themselves?
Motives matter..... when things don’t turn out as planned.
When motive and outcome are mismatched, people discount the voluntary action and augment the proximal event.
But, when things end as planned, intent doesn’t matter
When motive and outcome match, people judge voluntary actions as equally causal as physical events. Outcome * Distal-event-type * Temporal Order, F(2, 351) = 12.32, p < .001

16. Issue 3: Measuring Praise / Blame
Outcome Effects: Events rated higher for negative rather than positive outcomes.
Voluntary Actions: Regardless of outcome, motive dominates the field, people judge the action. Bad actions are bad, good actions are neutral..
Physical Events: How the sequence begins and ends matters....
People seem to dissociate the action from the outcome for moral judgments.
Physical events subjected to moral evaluation.

17. Summary: Chain Structure Effects
Two Physical Events
Positive Outcome
Negative Outcome
Contribution – recency effect
Equally causal
Equally blameworthy
Contribute equally
Match / Mismatch Effects: Distal Voluntary Actions and Proximal Physical Events
Positive Actions
Less causal
Less blameworthy
Negative Actions
More blameworthy
Something other than intent also appears to have a strong intervening influence on judgments…….. Theories?

18. Conclusion:
Is it the cause, or is it something to do with the structure?
Motive, outcome, and the structure of the sequence of events affects judgments.
People see sequences very differently depending on how they end.
Outcome valence appears to prompt differing sets of reasoning criteria.
The moral quality of actions then influences how people see each event within the sequence.
Motive matters when things don’t turn out as planned. But, when things end as expected, intent doesn’t matter ‘All things are equal’.
The ultimate effect of the structure on judgments appears to be a compensatory one.
Physical events are not immune to moral evaluation.

19. THANK YOU Event Type Causal Structure Intention Outcome Philosophy Law
Study 7
Positive
Negative
Outcome
Positive
Negative
Studies 4 & 5
Human Agency
Studies 4 & 5
Event Type
Studies 4 & 5
Physical Events
Studies 1, 2, & 3
Causal Structure
Philosophy
Law
Psychology