Archive for the 'Science and the Media' Category

Aug 13 2024

Framing and Global Warming

When we talk publicly about the effects of human activity on the climate should we refer to “global warming”, “climate change”, the “climate crisis” or to “climate justice”? Perhaps we should also be more technical and say specifically, “anthropogenic climate change”. This kind of question is often referred to as “framing”, meaning that we need to be thoughtful about how we frame topics for science communication and open discussion.

I remember about two decades ago when the concept of “framing” was really introduced into the skeptical community. There was a lot of pushback, because the practice was considered to be deceptive, and more aligned with political persuasion than science communication. This criticism was unfounded, in my opinion, largely because it is naive. It assumes, falsely, that you can communicate without framing. In reality you are framing your messages whether you know it or not, so you might as well be conscious and thoughtful about it.

To get into more detail, what is meant by framing is the overall approach to a topic in terms of major perspectives and considerations. For example, we can frame a discussion on GMOs as purely a scientific question – what does the evidence say about the risks and benefits of genetic engineering technology? We can also frame the topic as one of regulation – how should governments regulate GMOs? Or we can focus on corporate behavior and power. Often, the explicit framing I take on this blog, the framing focusses on critical thinking, pseudoscience, and conspiracy theories. How do we think logically and make sense of all the claims and information?

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Jun 03 2024

Clickbait and Misinformation

Which is worse – clickbaity headlines for news articles that are factually correct, but may be playing up a sensational angle, or straight-up misinformation? It depends on what you mean by “worse”. A new study tries to address this information, with some interesting findings.

Misinformation is an increasingly important topic, one with far reaching implications for society. Our individual lives and our society is increasingly run on information. It is a critical resource, and the ability to evaluate and utilize information may be a determining factor in our quality of life. My favorite example remains Steve Jobs, because he is such a stark example. He was one of the richest people on the planet, with every physical resource at his disposal, and was a titan of an information industry. And yet he died prematurely of a potentially curable disease. He chose to delay mainstream treatment in order to pursue “natural” therapies that were ultimately worthless. We cannot know for sure what would have happened if he did not take this course, but his odds of survival would have been better.

At a societal level the most visible impact that our information ecosystems have deals with politics and public health. We are facing a rather dramatic decision regarding the next presidential election in the US, and this will ultimately be determined by how people are accessing and evaluating information. This has always been the case in a democracy, but I think most people alive today have not experienced a divergence of narrative and opinion as intense as we have today.

We also just when through the worst pandemic in a century, which brought into focus every issue dealing with misinformation. How do we deal with it in an age of social media? How do we balance the interests of making sure people get accurate health information so they can make informed choices, and freedom of speech and the value of open debate? There is no one correct answer, we just have to choose our tradeoffs.

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Feb 07 2022

Joe Rogan and the Media Algorithm

The latest controversy over Joe Rogan and Spotify is a symptom of a long-standing trend, exacerbated by social media but not caused by it. The problem is with the algorithms used by media outlets to determine what to include on their platform.

The quick summary is that Joe Rogan’s podcast is the most popular podcast in the world with millions of listeners. Rogan follows a long interview format, and he is sometimes criticized for having on guests that promote pseudoscience or misinformation, for not holding them to account, or for promoting misinformation himself. In particular he has come under fire for spreading dangerous COVID misinformation during a health crisis, specifically his interview with Dr. Malone. In an open letter to Rogan’s podcast host, Spotify, health experts wrote:

“With an estimated 11 million listeners per episode, JRE, which is hosted exclusively on Spotify, is the world’s largest podcast and has tremendous influence,” the letter reads. “Spotify has a responsibility to mitigate the spread of misinformation on its platform, though the company presently has no misinformation policy.”

Then Neil Young gave Spotify an ultimatum – either Rogan goes, or he goes. Spotify did not respond, leading to Young pulling his entire catalog of music from the platform. Other artists have also joined the boycott. This entire episode has prompted yet another round of discussion over censorship and the responsibility of media platforms, outlets, and content producers. Rogan himself produced a video to explain his position. The video is definitively not an apology or even an attempt at one. In it Rogan makes two core points. The first is that he himself is not an expert of any kind, therefore he should not be held responsible for the scientific accuracy of what he says or the questions he asks. Second, his goal with the podcast is to simply interview interesting people. Rogan has long used these two points to absolve himself of any journalistic responsibility, so this is nothing new. He did muddy the waters a little when he went on to say that maybe he can research his interviewees more thoroughly to ask better informed questions, but this was presented as more of an afterthought. He stands by his core justifications.

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Sep 18 2020

Review of The Social Dilemma

I just watched the Netflix documentary, The Social Dilemma, and found it extremely interesting, if flawed. The show is about the inside operation of the big social media tech companies and the impact they are having on society. Like all documentaries – this one has a particular narrative, and that narrative is a choice made by the filmmakers. These narratives never reflect the full complexity of reality, and often drive the viewer to a certain conclusion. In short, you can never take them at face value and should try to understand them in a broader context.

Having said that, there is a lot of useful insight in the film. What it does well is interview tech insiders who expose the thinking on the part of corporations. We already know many of the pitfalls of social media, and I have discussed many of them here. Social media can be addictive, can lead to depression and a low self-esteem, and to FOMO (fear of missing out). We definitely need to explore the psychological aspects of social media, and this is still a new and active area of research.

Also, social media lends itself to information bubbles. When we rely mostly on social media for our news and information, over time that information is increasing curated to cater to a particular point of view. We can go down rabbit holes of subculture, conspiracy theories, and radical political perspectives. Social media algorithsms have essentially convinced people that the Earth is flat, that JFK Jr. is alive and secretly working for Trump, and that the experts are all lying to us.

This is where I think the documentary was very persuasive and the conclusions resonated. They argued that increasingly people of different political identities are literally living in different worlds. They are cocooned in an information ecosystem that not only has its own set of opinions but its own set of facts. This makes a conversation between different camps impossible. There is no common ground of a shared reality. In fact, the idea of facts, truth, and reality fades away and is replaced entirely with opinion and perspective, and a false equivalency that erases expertise, process, and any measure of validity. At least, this is what happens in the extreme (and I think we have all experienced this).

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Sep 10 2020

Miscibility Gaps Alloy Thermal Storage

I was recently sent this article about a new miscibility gaps alloy (MGA) thermal storage material. The technology is, perhaps, an incremental advance and may be useful for grid storage, but the article itself represents, in my opinion, horrible science communication. It seems like what you get when a general reporter, not trained in science journalism, reports on a complicated science topic. It didn’t give me any of the information I wanted, didn’t put this new technology into meaningful or accurate context, and didn’t explain some basic concepts involved.

Here is the basic story – a University of Newcastle (in Australia) team has developed an MGA material that could potentially be useful in grid storage by serving as a medium for thermal energy storage.  They also describe what an MGA material is by using an analogy to a chocolate chip cookie, where the chocolate chips melt when heated, storing most of the energy, but the rest of the cookie remains solid. That is about all the information you get from this article, stated in two sentences. The chocolate chip cookie analogy is fair, but following up with a slightly more technical definition would have been nice. MGAs are mixed materials where there is a range of temperatures (more specifically a region of the phase diagram that includes both pressure and temperature) where the different materials are in two or more phases. The rest of the article just states over and over again in different ways, like this is a new idea, why grid storage would be useful.

Why are MGAs particularly useful for thermal energy storage? First, the particles that melt store a lot of energy in the phase change while the particles that don’t melt can maintain the solidity of the overall material. But further, because of the liquid components, these materials have great thermal conductivity, so they don’t need infrastructure just to conduct the heat through the material. The Newcastle MGA is supposed to be an innovation because it is made from readily available material that is non-toxic.

I came away from the article with lots of important questions, all unanswered, and had to research them for myself. I was able to find information about MGAs in general, but not the Newcastle MGA specifically.

My first question, which you should ask about any proposed grid storage option, is – what is the round-trip efficiency? There are lots of grid storage options (which I review here), none of which are perfect. We need to know about each – what is the cost, how scalable are they, are they location-specific, what are the environmental effects, what are the energy losses over time, and what is the round-trip efficiency (the loss of energy from converting grid electricity to storage and then back to grid electricity). The best round trip efficiency is from pumped hydro, about 80-90%, but this is very limited by location and has serious environmental implications. Battery storage is not bad, at 60-70% round trip efficiency, but this is still an expensive option with lots of material waste and a limited lifespan.

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Aug 03 2020

Do Your Own Research?

A recent commentary on Forbes advises: You Must Not ‘Do Your Own Research’ When It Comes To Science. I agree  with everything the author, Ethan Siegel, says in the piece. It was a good start – but did not go far enough. For example, he did not really reach any conclusion about what people should actually do, beyond “listen to the experts.” OK – how, exactly, do we do that? This is not a criticism (I have written similar articles before) but an observation: after trying to communicate these same skeptical themes for decades and getting thousands of questions from the public, I have realized that it is perhaps not so obvious what it means to listen to the experts.

First let me amplify what Siegel gets right, although I may reframe it a bit. He correctly describes the typical process that people use when evaluating new information, although does not name it – confirmation bias. His summary is as good as any:

  • formulating an initial opinion the first time we hear about something,
  • evaluating everything we encounter after that through that lens of our gut instinct,
  • finding reasons to think positively about the portions of the narrative that support or justify our initial opinion,
  • and finding reasons to discount or otherwise dismiss the portions that detract from it.

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Jun 19 2020

News vs Commentary

The line between news and commentary has arguably become more blurred in recent decades. This has implications for libel law, which also reflects the shifting media landscape. A recent lawsuit involving Tucker Carlson illustrates the problem.

Carlson is being sued for defamation by Karen McDougal for a segment in which she claims Carlson accused her of extortion.  She is one of two women that we know of who were paid off to remain silent about affairs with Trump. Here is the money quote from Carlson:

“Two women approached Donald Trump and threatened to ruin his career and humiliate his family if he doesn’t give them money. Now that sounds like a classic case of extortion.”

For background, libel cases are hard to prove in the US. You need to demonstrate that statements were made in public that are claims to facts, that are factually wrong, where the person making the statement knew they were wrong or had a disregard for the truth, that there was malice of intent, and that actual harm resulted. For some statements you don’t have to prove harm, they are “libel per se,” such as accusing someone of pedophilia. The harm is taken for granted. If the target of the alleged defamation is a public figure, then the burden of proof is even higher.

At issue here are whether Carlson’s statements were presented as facts or opinion. Opinion is completely protected free speech, and cannot be defamatory legally. The first part of Carlson’s statement above is stated as simple fact. The second part (“that sounds like”) seems to be his analysis or opinion. Forgetting the other aspects of the defamation standard for now, this question seems to be the crux of the case. Was Carlson making a factual claim he knew to be untrue, or without concern for whether or not it was true? The defamation standard requires more than just being wrong.

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May 08 2020

Spoofing the Lede in Science Journalism

In journalism “burying the lede” means that the truly newsworthy part of a story is not mentioned until deep in the story, rather than up front where it belongs. I tried to find if there is a term that means the opposite – to take something that is not really part of the story and present it as if it the lede.  I could not find it. Perhaps it doesn’t exist (if anyone knows of such a term, let me know). So I made up my own – spoofing the lede.

This is very common is science journalism. It entails taking a study, finding, or discovery and not reporting the actual findings of the study up front, but rather reporting one possible implication of the study. This might be purely speculative, even fanciful. For example, take any study that discovers anything about viruses, and the headline might read, “Scientists find possible cure for the common cold.” The study may have nothing at all to do with the common cold.

This comes from journalists (and often those in the press office whose job it is to “sell” the research of their institution) asking the question – what does this mean? What are the implications of this finding that average people can relate to? That is fine, as far as it goes, but there are often two main problems with implementation. The first is when the possible implication is a real stretch. The connection is super thin, even strained. No, that metamaterial will not lead to a “Harry Potter-like invisibility cloak.”

The second is when that thin possible implication of the research is presented as if it is the actual results of the study. That is the false lede that should be buried – put that toward the end of the article, and put it into proper perspective. This kind of research (for example) helps us understand viral replication, and any such knowledge might lead to potential treatments for viral illness, like the common cold. However, it takes decades for such basic research to lead to direct applications, which cannot be predicted.

I do think this is nothing less than a massive systematic failure of popular science communications – focusing on the sexy speculative implication of research, and burying the actual research.

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Nov 14 2019

The Science Wars

In an ideal world (not the one we live in) science should be apolitical. In fact, it should be completely protected from political and other ideological influence. By this I mean the conduct of scientific research itself, so that the results are shielded from bias, conflicts of interest, and undue influence.

There are ways in which science and politics legitimately interact. If governments fund scientific research, then they have a right to set standards and dictate priorities for the research they fund. They don’t, however, have a right to dictate results, because then that perverts science into ideological pseudoscience. Priorities should also be broadly defined – what basic goal are you trying to achieve, such as finding cures for cancer. But they should avoid micromanaging the direction of scientific research, which optimally should follow the science itself.

The other legitimate interaction is that science should inform politics. It cannot determine politics, because politics also includes value judgements and priorities that are partly subjective. But scientific information can answer important questions helpful to setting political priorities or crafting specific solutions. Scientific research can also be used to determine how effective and efficient specific policies and programs are.

What we need to avoid, however, is a situation in which those with a vested interest are able to put their thumb on the scale, to create scientific research that serves their ends, rather than honestly pursuing the truth. When you work backwards from a desired result, that is not even science. That is pseudoscience.

But there is also a more subtle way in which political or corporate agendas can corrupt science – not by creating the scientific results they want, but by cherry picking those results. Science is complex and imperfect, so any big question in science is likely to contain research with results that are all over the place (just by chance alone). If you are able to cherry pick the results you want, without honestly looking at all the research based on quality alone, then again you can easily distort the scientific process to political will or vested interests.

This is a political battle that is going on right now – which science is admissible in terms of informing government policy? For example, in 2017 EPA director Scott Pruitt announced a new policy that would ban scientists from the EPA’s scientific advisory board if they received funding from the EPA. This was presented as a way to limit the perception of conflicts of interest.

However, in practice this was a way to exclude many academic scientists. If you are an environmental expert working in academia, chances are you have received some government funding. This would be the equivalent of banning medical scientists from government advisory boards who ever received funding from the NIH – so basically any qualified academic researcher.

The rule, however, made no mention of industry conflicts of interest. The result was to pack the scientific advisory panel with industry experts at the expense of independent academic experts – all under the pretext of quality control.

Similarly, you can craft rules to exclude specific scientific studies, again under the pretext of quality control, but designed to exclude studies more likely to be unfriendly to your political agenda. The EPA just announced a proposed rule to require scientists submit raw data for any studies they cite when informing government policy.

A new draft of the Environmental Protection Agency proposal, titled Strengthening Transparency in Regulatory Science, would require that scientists disclose all of their raw data, including confidential medical records, before the agency could consider an academic study’s conclusions. E.P.A. officials called the plan a step toward transparency and said the disclosure of raw data would allow conclusions to be verified independently.

Disclosure of raw data for independent analysis is a good thing, but it is being perverted here for political ends. The devil, as always, is in the details. What if a study that is the basis of EPA policy is 20 or 30 years old, and the raw data is no longer available? Now they have an excuse to roll back regulations based on those older studies. What if the study includes confidential personal medical data? There are rules for the use and disclosure of such information, and so you can manufacture a regulatory conflict that excludes legitimate studies from consideration.

This is all the regulatory equivalent of p-hacking – making necessary and legitimate decisions about how to conduct research, but with an eye on how it affects the data so as to massage the results toward statistical significance.

Transparence and quality control in the science used by government agencies to inform policy is a necessary and good thing, but if specific rules are crafted with an eye toward favoring industry and excluding independent experts, you can engineer a desired outcome. Even more sinister – if you goal is just to promote uncertainty and doubt, to paralyze regulatory efforts, then just keep raising the bar of quality control to exclude more and more legitimate science.

No scientific studies are pristine. No researcher is without any connections to either industry or government that can be spun into a potential conflict of interest (or the appearance of one). He works in a lab with another researcher who received funding from an organization that is partly funded by industry – COI!

Elizabeth Warren is now promising to fight back from the other side.

Any studies found to present conflicts of interest “will be excluded from the rulemaking process and will be inadmissible in any subsequent court challenges unless the research has passed rigorous, independent peer review,” Warren wrote.

Again, the devil is in the details. How will this policy be implemented? It can easily turn into an industry witch hunt that excludes legitimate research based on tenuous or perfectly innocent connections. And who will do the independent peer-review? That’s really the question.

I believe that Warren’s intentions are pure, but here is my concern. She is thinking this is a way to exclude research, for example, funded by the fossil fuel industry with the intention of muddying the waters on climate change to delay regulations.

But – the same rules can then be used to exclude research on GMOs because of industry connections and frustrate the approval of new crops. And how will this affect the pharmaceutical industry?

Even if Warren’s rules are used wisely, the apparatus is in place for the next administration who may have very different priorities.

The inherent dilemma is that we have government deciding how government will determine what science to use to form government policy. The process is just begging to be distorted for political ends.

What we need to do is craft an infrastructure of quality control for science that informs government policy that is as isolated and independent from undue political influence as possible. This can never be perfect, but it can be robust with sufficient checks and balances. We recognize the need, for example, for an independent judiciary that priorities justice over politics. We recognize the independence of the Fed to isolate monetary policy from politics. We also need to recognize the importance of independent scientific advice as insulated from political influence as possible. This should not be at the whim of the current administration, or easily weakened or perverted.

This can’t turn into a war between industry and academics. Both are needed, and good science has connections to both private and public funding. What we need is independent scientific advice that priorities objectivity and quality and is buffered from short-term political agendas.

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Aug 26 2019

False Memories and Fake News

Here’s yet another reminder that our memories are reconstructed fabrications our brains use to reinforce existing narratives. A new study of 3,140 participants finds that exposing people to fake news created false memories of the depicted events in about half of subjects.

What the researchers did specifically was show people in Ireland prior to the 2018 referendum on abortion, six news stories, two of which were fake. One of the fake stories was about campaign posters being destroyed after it was discovered that they were illegally funded by an American. Later, about half of the subjects reported false memories regarding at least one of the two fake stories. About one third of the subjects included details in their fake memories that were not included in the original stories.

Further, subjects were more likely to form false memories if the fake news dealt with a scandal for the other side (so “yes” voters were more likely to form false memories regarding a scandal involving the “no” vote). And perhaps most concerning, when the subjects were told which news stories were fake, this only decreased the false memories slightly. It did not correct the effect.

None of this is entirely new, but it is the first study like it involving a real-time political event. This research reinforces what psychologists have been demonstrating for years – that memories are constructed, and then reconstructed in remembering, that memories are partly thematic and the details will morph to fit the theme, and that fake memories are relatively easy to create. Once formed a fake memory feels just like a real memory. They are just as vivid and compelling as a genuine or more accurate memory. Vividness does not predict accuracy, despite the fact that this is what most people assume.

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