This week we look at the impact of irrational biases and the chaos of stories.

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Research Roundup

Social Bias Bias

Loss aversion refers to people's tendency to make different choices “depending on whether outcomes are described as losses or gains”. It seems that observers—managers or juries—show loss aversion, inducing them to “financially punish decision makers who…make risk-averse…choices when choice outcomes are framed as losses” but not as gains. So not only do we need to be worried about our own biases, but social influence forces us to account for the biases of others.

That is not the only way that biases and social behavior interact: “beauty is associated with lower support for redistribution”. Specifically (and perhaps not surprisingly), “attractive individuals are more likely to believe that economic success depends more on individual effort”. This induces (subjectively?) beautiful people to vote for lower taxes and more economically liberal policies, regardless of gender, income, or employment. I suspect that this would generalize to any intrinsically advantaged population level.

Lesson: don't hate me because I'm beautiful…hate me because I’m a self-deluding creep.

Stories We Tell Ourselves

Macroeconomics narratives are “beliefs about the economy that spread contagiously”. As “optimistic narratives” spread within a company, they actually cause the firms to expand, “even though these narratives have no predictive power for future firm fundamentals”. In fact, “narratives explain 32% and 18% of the output reductions over the early 2000s recession and Great Recession, respectively, and 19% of output variance”. We are the stories we tell ourselves.

But what if those stories differ within a single community? It probably makes our intuitive story that “LGBT Americans are distinctively liberal compared to otherwise similar straight and cisgender respondents” across a wide range of policy issues. Curiously, though, “bisexual and transgender respondents are frequently less liberal than lesbians and gay men”. Further, there are “substantial differences between bisexual men and bisexual women, but little evidence of diversity based on gender within lesbian/gay and transgender subgroups”.

One of the most fascinating aspects of using machine learning to study large populations of people is seeing all of the complex and downright chaotic ways stories move like weather through minds.

Weekly Indulgence

My shocking confession: I’ve never visited #Rome or any other part of #Italy…but that’s about to change. I’m speaking at the UN’s AHRMIO conference in Rome Oct 28-30.

Then I’m hanging around #Europe before speaking at Novo Nordisk’s Innovation Day in #Copenhagen on Nov 4th.

In between…I’m yours! Book me for “the most amazing talk I ever heard” and support my work at The Human Trust at the same time.

https://socos.org/speaking – www.thehumantrust.org

Stage & Screen

• October 9-10, NYC: 2 events in one–I'm back at the UN speaking at GlobalMindED
  • then receiving StartOut's Trailblazer Award – Buy a ticket!!!
• October 23, Toronto: Let's spend the day together at Metropolitan University's Future of Work conference
• October 28-19, Rome: Are you as shocked as I that this is my first ever visit to Italy? I'll be talking AI and Humans for the UN.
• November 4, Copenhagen: Novo Nordisk Innovation Day!

Does your company, university, or conference just happen to be in one of the above locations and want the "best keynote I've ever heard" (shockingly spoken by multiple audiences last year)?

<<Support my work: book a keynote or briefing!>>

SciFi, Fantasy, & Me

I just have to admit it: I’ve watched and read a fair bit of scifi and fantasy this last week…but nothing new worth recommending. I’m looking forward to finishing The Umbrella Academy and diving into The Boy and the Heron and Agatha All Along. But the best scifi of the week was a rewatch of Fantastic Planet, which twisted my brain when I was little.

Vivienne L'Ecuyer Ming