Making the Case for Abundance

Few things are more important than ensuring that people have plenty of the critical goods they need to pursue happiness, including jobs, energy, housing and education. Without these basic necessities, human flourishing is all but impossible; with them, people can unleash their unique human potential and make everyone better off. Under the best of circumstances, we’d even achieve “superabundance” and maximize security, freedom and prosperity, three universal goods. This agenda has clear bipartisan appeal.

Nonetheless, abundance has not yet become a major talking point in our nation’s political conversation. Nor has it specifically been embraced by either major party. So, the pressing question is: How do we successfully advocate for an abundance agenda?

Doesn’t it make sense to lead with data, logic and reason? After all, there are mounds of data showing that various policies promote an abundance of critical goods across society. Consider history’s so-called “hockey stick,” the graph depicting our economic history. For tens of thousands of years, almost everyone everywhere was dirt poor. Then, all of a sudden, about 200 years ago, boom! In what Deirdre McCloskey has called “The Great Enrichment,” a confluence of factors created an eruption of economic growth that made billions of people materially and morally better off.

The benefits obviously speak for themselves, don’t they? So we just need to show people these sorts of graphs, and they “should” (whatever “should” means) see the truth and incorporate it into their worldview, right? Not exactly.

As appealing and noble as a data-driven approach sounds, there’s one small problem: By itself, it rarely works because it doesn’t align with how the human mind functions. Data doesn’t persuade. That’s a problem because it’s imperative that we succeed in advocating for principles and policies that will make people better off, especially those most in need. Instead of just data or even reason, a successful abundance advocacy strategy ultimately needs to be heavily infused with emotional intelligence.

Good Data Is Necessary, But Not Sufficient

Many people are wedded to the view that data, logic and rationality can and will win the day in any open and honest conversation. The idea is that if we just do the hard work, run the data properly and offer enough proof for our views, then someone else will readily adopt them because those views have been shown to be “true,” not simply to us, but to anyone willing to keep an open mind and think it through.

This data-centered approach to advocacy has obvious appeal, and it’s crucial for effective advocacy. Indeed, good data puts our principles and policies on firm technical footing. This is undoubtedly necessary because we need a system for demonstrating the quantitative benefits of our ideas and comparing them to competing proposals. And the usual result of building principles and policies on faulty foundations is collapse and, often, catastrophe. We need to avoid that at all costs. What’s more, this approach is clean, simple and logically sound—almost hard to argue against.

Many policy advocates, however, then make a problematic leap. Because solid data is necessary, we come to deem data sufficient for persuasion. This mindset manifests itself far too often in putting “white papers over people” (a phrase shared with me by the Institute for Justice’s communications guru John Kramer). We focus on getting the data “right” in logically written research papers replete with graphs and charts rather than focusing on people and what the data means for them. We think these tightly reasoned expositions will make people see the light and start to see things like we do (as long as they don’t just close their eyes). We tell them: This policy will increase GDP by 1.1 percentage points! That reform will create 500,000 new jobs over three years.

Now, stop and ask yourself: When was the last time you even considered revising your beliefs, especially your core beliefs, upon confronting data that didn’t conform to those beliefs? For most people, the answer is “never.” You probably just looked for other data that affirmed your beliefs and rejected or ignored the conflicting data. (It’s called confirmation bias, and we all do it).

And yet, despite knowing that a data-driven approach doesn’t make us change our minds, we assume that it works with others. The reality is that it simply doesn’t, especially with people who don’t already agree with you. Much as we think (our) data should win, that isn’t how our minds work.

In fact, while we fancy ourselves logic processors, an abundance of research in psychology, neuroscience, economics and political science has shown us to be quite the opposite. For example, Daniel Kahneman, starting in his work with Amos Tversky, has uncovered dozens of cognitive biases—systemic and flawed thinking patterns that arise in everyone in response to decision and judgment situations. These biases include hindsight bias, availability bias and optimistic bias. In total, researchers have uncovered over 180 cognitive biases.

In his recent book, Kahneman explored with his co-authors another problem in human judgment: “Noise.” Noise is unexplained randomness and variability in our judgments, when those judgments should be similar or identical. And it’s pervasive.

Neuroscientist Antonio Damasio has shown that emotion or intuition comes before reason in our thought processes. Social and moral psychologist Jonathan Haidt provides further evidence for this in “The Righteous Mind.” In short, we’re not primarily logic processors. We’re actually story processors first and foremost.

Read the full article at Discourse Magazine.