Interesting article connecting the issue of language and climate change. This also gets at the fact that we don’t always communicate what we think we are and that different groups of people communicate differently. Frank Luntz, discussed below, often uses the adage: It’s not what you say, it’s what people hear.
The science community is supposed to interpret for the rest of us, but its dialect does not always pack rhetorical oomph. “I didn’t realize that pointing to a climate graph I think is the Rosetta stone — people don’t see it the way I see it,” says Brenda Ekwurzel, director of climate science for the Union of Concerned Scientists. “We as humans don’t experience an exponential curve viscerally, in our gut.”
More on Luntz
Frank Luntz is a popular American pollster but also famous for helping the Republican Party hone its messaging and use of language in the 1990s and 2000s. He authored a famous memo on messaging the “War on Terror.” One can argue with the ethics of what he did (intentionally tying 9/11 and Iraq in people’s minds without ever explicitly making the connection for example) but his work was devastatingly effective. This memo made for much better discussion teaching TOK 10 years ago but I think is very interesting to still study.
Download Luntz Memo On Terrorism
Here is Luntz being challenged about another famous memo he wrote on climate change. He has since changed his mind.
Image of Luntz now discussing messaging on discussing climate change.
May need some context on the fact that Data is an android without emotions to help explain the clip but it speaks for itself. Don’t think I’d use it with students but it explains some important concepts succinctly.
Great video that lays out some key concepts in science about scientific models and predictions. What’s really interesting is that despite successful prediction, other observations may yet be incompatible and so we know that some explanations are “wrong” or at least, “incomplete.”
fake detection technology is important, but it’s only part of the solution. It is the human factor—weaknesses in our human psychology—not their technical sophistication that make deep fakes so effective. New research hints at how foundational the problem is.
The biggest threat of deepfakes isn’t the deepfakes themselves
“Deepfakes do pose a risk to politics in terms of fake media appearing to be real, but right now the more tangible threat is how the idea of deepfakes can be invoked to make the real appear fake,” says Henry Ajder, one of the authors of the report. “The hype and rather sensational coverage speculating on deepfakes’ political impact has overshadowed the real cases where deepfakes have had an impact.”
I think it’s time we take a lesson from the history of science. Beauty does not have a good track record as a guide for theory-development. Many beautiful hypotheses were just wrong, like Johannes Kepler’s idea that planetary orbits are stacked in regular polyhedrons known as ‘Platonic solids’, or that atoms are knots in an invisible aether, or that the Universe is in a ‘steady state’ rather than undergoing expansion.
And other theories that were once considered ugly have stood the test of time.
A Scientist Must Go where the Evidence Leads
When our cherished ideas are contradicted by the facts, we must avoid the human tendency to double down on those ideas.
Impartial attention to evidence should get priority over inertia or social pressure in dictating the mainstream scientific agenda. An honest response of scientists to failed models would set an exemplar for intellectual leadership on how to walk the walk, and not just talk the talk, about revising our notions of reality when the evidence demands we must. This has implications for all aspects of life—including public policy.
The ability to refresh our models of reality over time is the trademark of wisdom. The commitment of using our best models of reality to navigate forward is the trademark of outstanding leadership.
This topic connects well to so many related topics in TOK. How do we acquire knowledge? What ethical responsibility do media companies (like youtube) have to promoting “truth”? How do we produce knowledge in the natural sciences? How reliable is intuition in acquiring knowledge?
Related video on Netflix, Behind the Curve