Search Results for "bias"

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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Jan 18 2022

Are We In a Sixth Extinction

Published by under General Science

There have been five recognized mass extinctions in the history of life on Earth, and a number of smaller ones. They include, in order:

  • Ordovician (444 million years ago; mya) – climate change caused by continental drift
  • Devonian (360 mya) – volcanic eruptions
  • Permian (250 mya) – unknown, could be asteroid strike, eruptions, climate change
  • Triassic-Jurassic (200 mya) – volcanic activity
  • KT (65 mya) – asteroid strike

Many scientists believe we are now in the middle of a sixth mass extinction, this time cause entirely by anthropogenic factors – human activity. We are warming the atmosphere and oceans, acidifying the oceans, polluting the environment, overfishing, hunting some species to extinction, converting ecosystems to farmland and living space, and spreading invasive species. The evidence of a slow-rolling mass extinction seems to be obvious, but still there are those who question if it is really happening. That questioning ranges from healthy scientific skepticism to outright denial.

The reason for the debate is our ability to rigorously document the extinction rate over time. It’s not enough to point out that extinctions are happening. The current estimate is that there are 8.7 million species of plants and animals extant today. Extinction is also a natural part of the evolution of life over time, and biologists also estimate that the background extinction rate is about 10% every million years. This can also be expressed as one extinction per million species years (one extinction per million species per year). This means the background rate should be about 870 extinctions per century. Over the last century there have been recorded about 500 animal extinctions. This is the basis for the argument that we are not in the middle of a mass extinction.

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Jan 06 2022

Gambler’s Fallacy and the Regression to the Mean

Published by under Logic/Philosophy

Humans overall suck at logic. We have the capacity for logic, but it is only one of many algorithms running in our brains, and often gets lost in the noise. Further, we have many intuitions, biases, and cognitive flaws that degrade our ability to think logically. Fortunately, however, we also have the ability for metacognition, the ability to think about our own thinking. We can therefore learn logic and how to think more clearly, filtering out the biases and flaws. It is impossible to do this perfectly, so it is best to think of metacognition as a life-long project of incremental self-improvement. Further, our biases can be so powerful, that when we learn how to think about thinking we often just make our logical fallacies more and more subtle, rather than eliminating them entirely.

Some cognitive flaws are evolutionarily baked into our thinking, likely resulting from heuristics that are practical mental shortcuts but not strictly logically valid. There also appears to be some cognitive abilities that were not prioritized in our evolutionary history, and so our finite brain resources were simply not allocated to them. This is where most math and statistically related fallacies derive. We do not deal well with large numbers, and we have terrible intuitions regarding statistics and probability. We have developed elaborate formal systems for dealing with math and probability, essentially to replace or at least augment our intuitive thinking, and often these systems produce results that are counterintuitive.

Perhaps the most famous example of counter-intuitive statistics is the Monty Hall problem. You are given a choice of three doors, behind one is a prize. You can choose one door. The host of this game, who knows where the prize is, then opens one door without a prize (again – they know where the prize is and deliberately choose one of the unchosen doors without a prize), and then ask if you want to change your choice to the other unopened door. If you change your choice your odds of winning go up from 1/3 to 2/3. If you have not encountered this problem before, this may seem counterintuitive, but it is absolutely correct.

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Nov 09 2021

Brain Stimulation for Cognitive Control

Published by under Neuroscience

A newly published study presents a proof-of-concept for using deep brain stimulation controlled with artificial intelligence (AI) in a closed-loop system to enhance cognitive control, suggesting it might be effective for a number of mental illnesses. That’s a lot to unpack, so let’s go back to the beginning. The most fundamental necessary to understand what is going on here is that your brain is a machine. It’s a really complicated machine, but it’s a machine none-the-less, and we can alter the function of that machine by altering its physical state.

This may seem obvious, but actually people are generally psychologically biased against this view. This may, in fact, be a consequence of brain function itself, which evolved to create a seamless stream of consciousness, an illusion of self unaware of all the subconscious processes that make up brain function. This is why we tend to interpret people’s behavior in terms of personality and conscious choice, when in fact much of our behavior is a consequence of subconscious processes. We are also biased to believe that people can think or will-power their way out of mental illness.

The more we understand about how the brain functions, however, the more it becomes apparent that the brain is just a glitchy machine, and lots can go wrong. Even when functioning within healthy parameters, there are many trade-offs in brain function, with strengths often coming at the price of weaknesses. We need to look out for our own interests, for example, but this comes at the price of anxiety and paranoia. But there are some brain functions that are so basic they are almost universally useful, and impairment of them can cause of host of problems. One such basic brain function is called cognitive control, which is essentially the ability to determine what thoughts and actions will be the focus of your brain’s attention.

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Oct 12 2021

Making Proteins with Plant Molecular Farming

Published by under General Science

As the world is contemplating ways to make its food production systems more efficient, productive, sustainable, and environmentally friendly, biotechnology is probably our best tool. I won’t argue it’s our only tool – there are many aspects of agriculture and they should all be leveraged to achieve our goals. I simply don’t think that we should take any tools off the table because of misguided philosophy, or worse, marketing narratives. The most pernicious such philosophy is the appeal to nature fallacy, where some arbitrary and vague sense of what is “natural” is used to argue (without or even against the evidence) that some options are better than others. We don’t really have this luxury anymore. We need to follow the science.

Essentially we should not fear genetic technology. Genetically modified and gene edited crops have proven to be entirely safe and can offer significant advantages in our quest for better agriculture. The technology has also proven useful in medicine and industry through the use of genetically modified microorganisms, like bacteria and yeast, for industrial scale production of certain proteins. Insulin is a great example, and is essential to modern treatment of diabetes. The cheese industry is mostly dependent on enzymes created with GMO organisms.

This, by the way, is often the “dirty little secret” of many legislative GMO initiatives. They usually include carve out exceptions for critical GMO applications. In Hawaii, perhaps the most anti-GMO state, their regulations exclude GMO papayas, because they saved the papaya industry from blight, and Hawaii apparently is not so dedicated to their anti-GMO bias that they would be willing to kill off a vital industry. Vermont passed the most aggressive GMO labeling law in the States, but made an exception for the cheese industry. These exceptions are good, but they show the hypocrisy in the anti-GMO crowd – “GMO’s are bad (except when we can’t live without them)”.

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Oct 11 2021

Neurofeedback Headbands for Stress Reduction

Published by under Neuroscience

A recent BBC article discusses the emergence of products designed for neurofeedback to aid in stress reduction. The headline asks, “Smart headbands claim to make people calmer. Do they work?” However, the article does not really answer the question, or even get to the heart of the issue. It mostly provide anecdotes and opinions without putting the technology into a clear context. The article focuses mainly on the use of such devices to allegedly improve sports performance.

There are a few premises on which the claims made for such devices are based, varying from well established to questionable. One premise is that we can measure “stress” in the brain using an electroencephalograph (EEG) to measure the electrical activity in the brain. This claim is mostly true, but there is some important background necessary to understand what this means. First, we need to define “stress”. Functionally when researchers are talking about mental stress they mean one of two things, either the stress that results from an immediate physical threat, or the mental stress that results from engaging in a challenging mental task (like doing math in your head while being distracted). For practical purposes the research on EEGs and mental stress use the challenging mental task model.

It his, however, a good representation of stress generally? It is a convenient research paradigm, but how generalizable it is to mental stress is questionable. It can result in objective measures of physiological stress, such as secretion of stress hormones, which is partly why it’s convenient for research and not unreasonable, but it is only a representation of mental stress and might not translate to all “stressful” situations (like sports).

Can EEGs measure this type of mental stress? Yes – a relaxed mind with eyes closed produces a lot of regular alpha waves. A more active mind (and one with eyes open) produces more theta waves and chaotic brainwave activity. EEGs can therefore tell the difference between relaxed and active. How about not just active but stressed? That is trickier, but there are studies which appear to show some statistical differences in the wave patterns regionally with mental stress. So the premise that EEGs can measure certain kinds of mental stress is reasonable, but not as simple as often implied. This also does not necessarily mean that commercial devices claiming to measure EEG markers of stress work.

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Sep 21 2021

Virtual Phobia Treatment

Are you afraid of spiders? I mean, really afraid, to the point that you will alter your plans and your behavior in order to specifically reduce the chance of encountering one of these multi-legged creatures? Intense fears, or phobias, are fairly common, affecting from 3-15% of the population. The technical definition (from the DSM-V) of phobia contains a number of criteria, but basically it is a persistent fear or anxiety provoked by a specific object or situation that is persistent, unreasonable and debilitating. In order to be considered a disorder:

“The fear, anxiety, or avoidance causes clinically significant distress or impairment in social, occupational, or other important areas of functioning.”

The most effective treatment for phobias is exposure therapy, which gradually exposes the person suffering from a phobia to the thing or situation which provokes fear and anxiety. This allows them to slowly build up a tolerance to the exposure (desensitization), to learn that their fears are unwarranted and to reduce their anxiety. Exposure therapy works, and reviews of the research show that it is effective and superior to other treatments, such as cognitive therapy alone.

But there can be practical limitations to exposure therapy. One of which is the inability to find an initial exposure scenario that the person suffering from a phobia will accept. For example, you may be so phobic of spiders that any exposure is unacceptable, and so there is no way to begin the process of exposure therapy. For these reasons there has been a great deal of interest in using virtual/augment reality for exposure therapy for phobia. A 2019 systematic review including nine studies found that VR exposure therapy was as effective as “in vivo” exposure therapy for agoraphobia (fearing situations like crowds that trigger panic) and specific phobias, but not quite as effective for social phobia.

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Sep 03 2021

Trust in Science May Lead to Pseudoscience

Published by under Skepticism

The ultimate goal of scientific skepticism is to skillfully use a process that has the maximal probability of accepting claims that are actually true and rejecting those that are false, while suspending judgment when an answer is not available. This is an open-ended process and is never complete, although some conclusions are so solid that questioning them further requires an extremely high bar of evidence. There are many components to scientific skepticism, broadly contained within scientific literacy, critical thinking skills, and media savvy. Traditional science communication focuses on scientific literacy (the so-called knowledge deficit model), but in the last few decades there has been copious research showing that this approach is not only not sufficient when dealing with many false beliefs, it may even be counterproductive.

A new study offer more evidence to support this view, highlighting the need to combine scientific literacy with critical thinking in order to combat misinformation and false claims. The study focuses on the effect of trust in science as an independent variable, and combined with the ability to critically evaluate scientific evidence. In a series of four experiments they looked at acceptance of false claims regarding either a fictional virus, or false claims about GMOs and tumors:

Depending on experimental condition, however, the claims contained references to either (a) scientific concepts and scientists who claimed to have conducted research on the virus or GMOs (scientific content), or (b) lay descriptions of the same issues from activist sources (no scientific content).

They wanted to see the effect of citing scientists and research on the acceptance of the false claims. As predicted, referring to science or scientists increased acceptance. They found that subjects who scored higher in terms of trust in science were more likely to believe false claims when scientists were cited – so trust in science made them more vulnerable to pseudoscience. For those with low trust in science, the presence or absence of scientific content had no effect on their belief in the false claims. These results replicated in the first three studies, using the fictional virus and the GMO claims.

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Aug 10 2021

IPCC 2021 Report on Climate Change

Published by under General Science

The Intergovernmental Panel on Climate Change (IPCC) has just produced their sixth report. This report builds on their previous work, and the current version (AR6) is the product of 234 scientists from around the world. This is essentially an update from their previous reports, taking into account all new evidence that has come to light. You can read the full report, or the executive summary for policymakers, or if you want more detail, the technical summary. Many news outlets, like the BBC, have also put out a highlight summary of their own.

I am not going to produce my own summary, just read the executive summary if you want the details. It’s only 39 pages. Instead, I am going to make some general observations.

First, for those who say there is no such thing as consensus in science, you are straight-up wrong. That is a strawman and denialist talking point. The strawman is the ubiquitous talking point that science is not determined by consensus. Of course it isn’t – consensus is determined by the science. The IPCC report is a great example of what consensus in science means – 234 experts pour over all the available evidence and then hash out a joint statement about what that evidence says. Next to each and every point there is a confidence notation, which they quantify – unlikely, likely, very likely, etc., with percentage confidence indicated for each notation. They are acknowledging the uncertainty, which torpedoes another strawman, equating consensus with certainty, or that the science is “settled” or that further research or debate is being shut down. This is all nonsense. The IPCC is simply a list of specific scientific statements, with a summary of the current evidence and degree of confidence.

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Aug 03 2021

Where’s My Self-Driving Car?

Published by under Technology

A lot of people have noticed that the self-driving car revolution has been…delayed. For the last decade predictions of when the technology would be ready for mass adoption were converging on the 2020s, beginning early in the decade. In this 2010 article, the prediction was – at least 8 years. Also, “US Secretary of Transportation Anthony Foxx declared in 2016 that we’d have fully autonomous cars everywhere by 2021.” Since then the technology has advanced tremendously, but has not quite crossed the threshold of fully autonomous vehicles. We are stuck in the “driver-assist” stage. Right now you can get a Tesla with the driver-assist package which you can use to summon your car from its parking space, and to assist during driving to help avoid accidents. But the driver must always be attentive and at the wheel. Fully autonomous driving is not yet a reality. What happened?

In retrospect it all seems completely predictable, because we have been here so many times before. This pattern does not necessarily happen with every technology, but it is extremely common, especially for new and complex technology. We have seen this with fusion reactors, artificial general intelligence, gene therapy, stem-cell therapy, the hydrogen economy, and flying cars. There are some common themes that keep cropping up. One is the tendency to overestimate short term progress, while underestimating long term progress. This pattern, in turn, results from some underlying tendencies and cognitive biases.

I think one of the most important is that we tend to default to extrapolating linearly into the future. So we think – if we have made this much progress between 2000 and 2010, then we should make similar progress between 2010 and 2020, and that’s when we will cross the finish line. The problem is, technological progress is not always linear. There is a more complex relationship, which can make net progress both faster and slower than we predict. This is because technological progress can be geometric, rather than linear. But at the same time, challenges can be geometrically difficult, so there is diminishing returns. These are competing geometric issues, and how they sort out can be difficult to extrapolate.

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