To which some people in Portland, echoing antifluoridation activists around the world, reply: We don’t believe you.

• This marks a fundamental break in trust between the public and the "powers that be", can this be repaired?

Empowered by their own sources of information and their own interpretations of research, doubters have declared war on the consensus of experts.

• Isn't the issue how to verify who the "experts" are?

Like the rest of us, they’re vulnerable to what they call confirmation bias—the tendency to look for and see only evidence that confirms what they already believe.

• In the age of "filter bubbles", are we purposely limiting our scope in favor of an echo chamber?

Scientific thinking has to be taught, and sometimes it’s not taught well, McNutt says. Students come away thinking of science as a collection of facts, not a method.

• Is this linked to how students are taught science in classrooms? Schools focus on rote memorization over the thinking involved.

In addition to the science communication problem, are our perceptions of science hindered by the static presentation of data?

Especially when topics like climate change occur on a large systemic level, how can information and data be communicated to convey a more impactful and time-aware message?

How can we, as designers, build a more empathetic approach to data?

People often make decisions based on personal stories and rules of thumb and data can apply to a large audience. So how do we determine what narrative we want the data to tell and what behaviours to address in that narrative to appeal to the audience?

1. How can we help alter misconceptions?

2. Is there a way to help people see past their own beliefs?

3. How can we remain unbiased and present the data accurately?

Can we map intuition next to science to help people visualize the mental tug of war?

The article places story (anecdote) in opposition to statistics. When is is relevant for stories to become statistics?

How can we present data in a way that does not challenge individual world views?

"Science appeals to our rational brain, but our beliefs are motivated largely by emotion, and the biggest motivation is remaining tight with our peers."

1 How do we define 'our peers' - family, friends, political party, religion, etc.? Does this mean we should always consider what kinds of people will be viewing our data/designs? Does that make our designs biased in turn?

"Students come away thinking of science as a collection of facts, not a method. Shtulman’s research has shown that even many college students don’t really understand what evidence is. The scientific method doesn’t come naturally."

2 - What are ways that people try to teach the scientific method? Is it helpful to learn it in the context of this course?

"For some people, the tribe is more important than the truth; for the best scientists, the truth is more important than the tribe."

3 - How do you use data and statistics to convey information in a way that will cut past this bias, while remaining unbiased? Is it possible?

R2

1. "For some people, the tribe is more important than the truth; for the best scientists, the truth is more important than the tribe."

*What is absolute truth? *

1. "Some environmental activists want scientists to emerge from their ivory towers and get more involved in the policy battles. Any scientist going that route needs to do so carefully, says Liz Neeley. 'That line between science communication and advocacy is very hard to step back from,' she says."

*If data is neutral, then data visualization is designers advocating a stance or an opinion. What is the danger in that? *

1. "In Kahan’s descriptions of how we decide what to believe, what we decide sometimes sounds almost incidental."

I don't think this is necessarily true. People believe based on the partial facts that are given.

Not a questions but Neil Degrasse Tyson said something along the lines of it being ok to hold alternative views (because freedom of speech and thought and whatnot), but when you hold a position of power and influence over others and you spew incorrect facts/anti-science, you become a risk/danger to the citizens of a nation, especially the young and impressionable ones.

Media seems to be a big problem. Misinformation and sensationalism doesn't help. How can change this? To my knowledge it hasn't always been this bad.

Obviously we aren't teaching science properly to students, but isn't the solution to improve the education system as a whole (which begins at the state/nation policy level with more budget, more qualified teachers)?

We choose personal anecdote/experience over statistics because it's the only thing we can relate to (1 person you know dying > statistic of 1 million people dying), so how can we make statistics hold the same power/emotion?

1. Although evidence suggests that better data rarely changes the minds of those who do not value it, which platforms are best for reaching a more neutral public? What qualities make a visualization accessible?

2. How can analysts and designers work to reduce confusion of correlation and causation when representing data to the public?

3. How can statistics and the science method be made more intuitive as part of our education system? Are there countries that do this better than others, or do entrenched values override education?

1. Can design be the bridge that brings scientific fact to light in a way that is "trendy" and attractive for civilians who just don't get the value of the information?

2. People easily brush things off when they are not imminent problems or if they aren't "their" problems regardless of facts and this has snowballed only to be drastically altered by framed information. What are some ways we can turn this around and include more considerations when presenting data in a convincing way?

3.Many of our habits originate from our parents; is there a more systematic approach to abandoning this idea and putting faith in science?

Questions on R2

Has the internet fundamentally changed the way we perceive truth in the world, or has it merely given us an easier way to give in to confirmation bias?

How can design address and play to people's naive beliefs? How can we use those to help people interact with the world better?

Is there really any line at all between data presentation as part of hard science and advocacy? How can people work in the area in between?

If people aren't swayed by truth presented by mouths they don't want to hear it from, why are we studying data visualisation?

How is it that high scientific literacy only serves to polarize climate debate? How can we as designers, who might not be as scientifically literate, present the debate in an unbiased way?

As in the case of climate change and vaccinations, how has the internet exacerbated or helped the debates? Was there even a debate to begin with?

(Anti-vaccine activist and actress Jenny McCarthy famously said on the Oprah Winfrey Show, “The University of Google is where I got my degree from.”)

Have we already become trapped in one of the two camps? (In which case the article can appear as incredibly condescending?)

It’s hard for all individuals to believe and process factual data when our minds are the strongest weapon we have (for example, placebo effect). So how can we as designers convincingly represent information in a way to help people truly absorb and process the information?

The internet allows users to filter information that is only relevant to their belief. Is there a way to ‘force’ users to view in a different perspective through design?

It would be even more impactful if solutions were presented alongside the data. How can we smoothly integrate these solutions to have an empathetic impact?