I’d be interested in an investigation and comparison of the participants’ Big Five personality scores. As with the XPT, I think it’s likely that the concerned group is higher on the dimensions of openness and neuroticism, and these persistent personality differences caused their persistent differences in predictions.
To flesh out this theory a bit more:
Similar to the XPT, this project failed to find much difference between the two groups’ predictions for the medium term (i.e. through 2030) - at least, not nearly enough disagreement to explain the divergence in their AI risk estimates through 2100. So to explain the divergence, we’d want a factor that (a) was stable over the course of the study, and (b) would influence estimates of xrisk by 2100 but not nearer-term predictions
Compared to the other forecast questions, the question about xrisk by 2100 is especially abstract; generating an estimate requires entering far mode to average out possibilities over a huge set of complex possible worlds. As such, I think predictions on this question are uniquely reliant on one’s high-level priors about whether bizarre and horrible things are generally common or are generally rare—beyond those priors, we really don’t have that much concrete to go on.
I think neuroticism and openness might be strong predictors of these priors:
I think one central component of neuroticism is a global prior on danger.[1] Essentially: is the world essentially a safe place where things are fundamentally okay? Or is the world vulnerable?
I think a central component of openness to experience is something like “openness to weird ideas”[2]: how willing are you to flirt with weird/unusual ideas, especially those that are potentially hazardous or destabilizing to engage with? (Arguments that “the end is nigh” from AI probably fit this bill, once you consider how many religious, social, and political movements have deployed similar arguments to attract followers throughout history.)
Personality traits are by definition mostly stable over time—so if these traits really are the main drivers of the divergence in the groups’ xrisk estimates, that could explain why participants’ estimates didn’t budge over 8 weeks.
I think this roughly lines up with scales c (“openness to theoretical or hypothetical ideas”) and e (“openness to unconventional views of reality”) from here
On a slight tangent from the above: I think I might have once come across an analysis of EAs’ scores on the Big Five scale, which IIRC found that EAs’ most extreme Big Five trait was high openness. (Perhaps it was Rethink Charity’s annual survey of EAs as e.g. analyzed by ElizabethE here, where [eyeballing these results] on a scale from 1-14, the EA respondents scored an average of 11 for openness, vs. less extreme scores on the other four dimensions?)
If EAs really do have especially high average openness, and high openness is a central driver of high AI xrisk estimates, that could also help explain EAs’ general tendency toward high AI xrisk estimates
I’d be interested in an investigation and comparison of the participants’ Big Five personality scores. As with the XPT, I think it’s likely that the concerned group is higher on the dimensions of openness and neuroticism, and these persistent personality differences caused their persistent differences in predictions.
To flesh out this theory a bit more:
Similar to the XPT, this project failed to find much difference between the two groups’ predictions for the medium term (i.e. through 2030) - at least, not nearly enough disagreement to explain the divergence in their AI risk estimates through 2100. So to explain the divergence, we’d want a factor that (a) was stable over the course of the study, and (b) would influence estimates of xrisk by 2100 but not nearer-term predictions
Compared to the other forecast questions, the question about xrisk by 2100 is especially abstract; generating an estimate requires entering far mode to average out possibilities over a huge set of complex possible worlds. As such, I think predictions on this question are uniquely reliant on one’s high-level priors about whether bizarre and horrible things are generally common or are generally rare—beyond those priors, we really don’t have that much concrete to go on.
I think neuroticism and openness might be strong predictors of these priors:
I think one central component of neuroticism is a global prior on danger.[1] Essentially: is the world essentially a safe place where things are fundamentally okay? Or is the world vulnerable?
I think a central component of openness to experience is something like “openness to weird ideas”[2]: how willing are you to flirt with weird/unusual ideas, especially those that are potentially hazardous or destabilizing to engage with? (Arguments that “the end is nigh” from AI probably fit this bill, once you consider how many religious, social, and political movements have deployed similar arguments to attract followers throughout history.)
Personality traits are by definition mostly stable over time—so if these traits really are the main drivers of the divergence in the groups’ xrisk estimates, that could explain why participants’ estimates didn’t budge over 8 weeks.
For example, this source identifies “a pervasive perception that the world is a dangerous and threatening place” as a core component of neuroticism.
I think this roughly lines up with scales c (“openness to theoretical or hypothetical ideas”) and e (“openness to unconventional views of reality”) from here
On a slight tangent from the above: I think I might have once come across an analysis of EAs’ scores on the Big Five scale, which IIRC found that EAs’ most extreme Big Five trait was high openness. (Perhaps it was Rethink Charity’s annual survey of EAs as e.g. analyzed by ElizabethE here, where [eyeballing these results] on a scale from 1-14, the EA respondents scored an average of 11 for openness, vs. less extreme scores on the other four dimensions?)
If EAs really do have especially high average openness, and high openness is a central driver of high AI xrisk estimates, that could also help explain EAs’ general tendency toward high AI xrisk estimates