I was intrigued by an article in Scientific American by philosopher, Philip Goff, mainly because I disagree with his ultimate conclusion. He makes a very cogent logical argument, but I am having trouble with one piece of it. Here’s the quick summary:

The core enigma is the fine-tuning problem with the universe. There are a number of physical constants, such as gravity, the charge of an electron, etc., and the behavior of stuff in the universe depends on the values of all these constants. The problem is that if the values of all these constants was not pretty much exactly what they are, then complex life would not be possible in our universe. Clearly complex life is possible, because we exist, so how do we explain the fabulously improbable physical laws of the universe?  To put this into perspective, Goff points out that:

The physicist Lee Smolin has calculated that the odds of life-compatible numbers coming up by chance is 1 in 10²²⁹.

The notion that this just happened by chance, and that we are incredibly lucky to exist, is not satisfying. What are some possible explanations for this highly improbable fact? One is that some powerful being (i.e. God) made the universe with these precise values so that complex life could exist. This does not solve the problem, however, it just pushes back the mystery one step – for where did God come from? I also reject this answer as an obvious “god of the gaps” argument – filling in an unknown by invoking, essentially, magic. It gets us nowhere. Another possible answer is that there is some underlying reason for the laws of physics, a metalaw, that determines that these constants must have these values. We don’t know what this could be, but at least this is something to investigate.

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“There is a cult of ignorance in the United States, and there has always been. The strain of anti-intellectualism has been a constant thread winding its way through our political and cultural life, nurtured by the false notion that democracy means that ‘my ignorance is just as good as your knowledge.”
― Issac Asimov

As science-communicators and skeptics we are trying to understand the phenomenon of rejection of evidence, logic, and the consensus of expert scientific opinion. There is, of course, no one explanation – complex psychological phenomena are likely to be multifactorial. Decades ago the blame was placed mostly on scientific illiteracy, a knowledge deficit problem, and the prescription was science education. Many studies over the last 20 years or so have found a host of factors – including moral purity, religious identity, ideology, political identity, intuitive (as opposed to analytical) thinking style, and a tendency toward conspiratorial thinking. And yes, knowledge deficit also plays a role. These many factors contribute to varying degrees on different issues and with different groups. They are also not independent variables, as they interact with each other.  Religious and political identity, for example, may be partially linked, and may contribute to a desire for moral purity.

Also, all this is just one layer, mostly focused on explaining the motivation for rejecting science. The process of rejection involves motivated reasoning, the Dunning-Kruger effect, and a host of self-reinforcing cognitive biases, such as confirmation bias. Shameless plug – for a full discussion of cognitive biases and related topics, see my book.

So let’s add one more concept into the mix: anti-intellectualism – the generalized mistrust of intellectuals and experts. This leads people to a contrarian position. They may consider themselves skeptics, but they do not primarily hold positions on scientific issues because of the evidence, but mainly because it is contrary to the mainstream or consensus opinion. If those elite experts claim it, then it must be wrong, so I will believe the opposite. This is distinct from conspiracy thinking, although there is a relationship. As an aside, what the evidence here shows is that some people believe in most or all conspiracies because they are conspiracy theorists. Others believe only in some conspiracies opportunistically, because it’s necessary to maintain a position they hold for other reasons. There is therefore bound to be a lot of overlap between anti-intellectualism and holding one or more conspiracies, but they are not the same thing.

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Recently celebrity supporters of Extinction Rebellion, a protest group calling for aggressive action on climate change, signed a letter admitting to being hypocrites. They state:

“Dear journalists who have called us hypocrites. You’re right. We live high carbon lives and the industries that we are part of have huge carbon footprints.”

But they go on to say:

“Like you, and everyone else, we are stuck in this fossil-fuel economy and without systemic change, our lifestyles will keep on causing climate and ecological harm.”

Their letter highlights an interesting conflict between personal responsibility and collective responsibility. How much is it on all of us as individuals to make sacrifices, or at least make a reasonable effort, to limit our carbon footprint? Coincidentally there was an interesting take on this question in the latest season of The Good Place (spoiler ahead). The lead characters discover that no one has made it into the Good Place in over 500 years. At first they think that the Bad Place has managed to hack the system in their favor, but ultimately discover that this reality is just an unintended consequence of modern life.

Cosmic points are awarded to individuals based on their actions, but the point system considers all consequences, intended or not, no matter how remote. So buying flowers for your grandmother may earn you points, but you lose more points because the money for those flowers found their way ultimately to a corporation using child labor. The interconnectedness of our global economy has made it literally impossible to be good.

So what do we do? Are we all hypocrites?

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One experience I have had many times is with colleagues or friends who are not aware of the problem of pseudoscience in medicine. At first they are in relative denial – “it can’t be that bad.” “Homeopathy cannot possibly be that dumb!” Once I have had an opportunity to explain it to them sufficiently and they see the evidence for themselves, they go from denial to outrage. They seem to go from one extreme to the other, thinking pseudoscience is hopelessly rampant, and even feeling nihilistic.

This general phenomenon is not limited to medical pseudoscience, and I think it applies broadly. We may be unaware of a problem, but once we learn to recognize it we see it everywhere. Confirmation bias kicks in, and we initially overapply the lessons we recently learned.

I have this problem when I give skeptical lectures. I can spend an hour discussing publication bias, researcher bias, p-hacking, the statistics about error in scientific publications, and all the problems with scientific journals. At first I was a little surprised at the questions I would get, expressing overall nihilism toward science in general. I inadvertently gave the wrong impression by failing to properly balance the lecture. These are all challenges to good science, but good science can and does get done. It’s just harder than many people think.

This relates to Aristotle’s philosophy of the mean – virtue is often a balance between two extreme vices. Similarly, I find there is often a nuanced position on many topics balanced precariously between two extremes. We can neither trust science and scientists explicitly, nor should we dismiss all of science as hopelessly biased and flawed. Freedom of speech is critical for democracy, but that does not mean freedom from the consequences of your speech, or that everyone has a right to any venue they choose.

A recent Guardian article about our current post-truth world reminded me of this philosophy of the mean. To a certain extent, society has gone from one extreme to the other when it comes to facts, expertise, and trusting authoritative sources. This is a massive oversimplification, and of course there have always been people everywhere along this spectrum. But there does seem to have been a shift. In the pre-social media age most people obtained their news from mainstream sources that were curated and edited. Talking head experts were basically trusted, and at least the broad center had a source of shared facts from which to debate.

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Democracy, in a very real sense, is math. The point is to aggregate decision-making in order to arrive at the fairest outcome for the greatest number of people. Andrea Jones-Rooy, who spoke at NECSS this year, gave a great lecture about this. Here is an article she wrote about Arrow’s Theorem that goes over the basic concept, but she went into more detail during the talk. Essentially there is no system of voting that has perfect fairness (ranked choice vs least objectionable option, for example), so we just have to pick one and live with the trade-offs.

Jones-Rooy, however, was talking about different systems that work as intended, no cheating. If, however, one group puts their thumb on the scale, the democratic process can be massively distorted. Beyond a certain point you no longer even have a true democracy. Voting becomes a sham used to give a patina of legitimacy to a dictator or minority rule.

Perhaps the best known form of voting distortion in the US is gerrymandering. The best description I have heard of this is that it is a way for politicians to choose their voters, rather than voters to choose their politicians. The idea is to carve up voting districts deliberately to favor one party, so that even if they have 40% of the voters in one state, they can secure 60% or more of the representatives. (This doesn’t work for senators or presidents where voting is state-wide.)

Researchers, however, have published an article in Nature in which they describe a more insidious form of distortion – information gerrymandering. This amounts to a rigorous mathematical description of a phenomenon we have been discussing, the effect of social media networks on public opinion. They found:

Players are assigned to competing groups (parties) and placed on an ‘influence network’ that determines whose voting intentions each player can observe. Players are incentivized to vote according to partisan interest, but also to coordinate their vote with the entire group. Our mathematical analysis uncovers a phenomenon that we call information gerrymandering: the structure of the influence network can sway the vote outcome towards one party, even when both parties have equal sizes and each player has the same influence.

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The BBC reports a case in which an artificial intelligence (AI) system is named as a possible patent holder for a new invention, and interlocking food container. Apparently none of the people involved with the invention meet the criteria for being a patent holder, since they did not come up with the actual innovation.

As a result, two professors from the University of Surrey have teamed up with the Missouri-based inventor of Dabus AI to file patents in the system’s name with the relevant authorities in the UK, Europe and US.

That’s an interesting solution. It does seem that international patent law needs to evolve in order to deal with the product of machine learning creativity. I think this reveals what a true game-changer current AI can be. It’s breaking our existing categories and legal framework.

But I don’t want to talk about patent law, about which I have no expertise – I want to talk about AI, about which I also have no expertise (but I do have a keen interest and pay attention to the news). Over the last few years there have been numerous developments that show how powerful machine learning algorithms are becoming. Specifically, they are able to create solutions that the AI programmers themselves don’t fully understand. The Dabus system itself uses one component to generate new ideas, based on being fed noisy input. But then a second component evaluates those ideas and gives the first component feedback. This idea, having two AI systems play off each other, creates a feedback loop that can rapidly iterate and improve a design or solution. So essentially we have two AIs talking to each other, and humans are largely out of the loop.

AI systems have come up with simulations and other solutions that the scientists using the system do not understand. Sometimes they don’t even know how it was possible for the AI to come up with the solutions it did.

Even more interesting, AI systems have developed their own language that they use to communicate with each other, and no human currently understands that language.

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Weird things happen to most people at some point in their lives, and if not to you directly than probably to someone you know. But what is the ultimate meaning to such coincidences? They may seem amazing, and psychologically scream out for an equally amazing explanation.

Skeptics caution, however, that our tendency to see patterns and impose satisfying explanations combine with our relative lack of intuition for statistics to jump to unwarranted conclusions. If we do the math, then it becomes clear that very unlikely events should happen all the time, given enough opportunity.

Some people, however, do not want to give up the narrative value of coincidences so easily. Sharon Hewitt Rawlette, for example, has written a book about The Source and Significance of Coincidences, and prefers a more supernatural explanation. In a recent editorial for Psychology Today she strikes back at the skeptical explanation for coincidences. She basically has one point to make, but first she states the skeptical position:

Skeptics argue that, even if the odds that a particular event would occur at this particular moment to this particular person are very low, there are so many moments over the course of our lives and so many people on this planet, that even very improbable coincidences are bound to happen eventually, just by chance. This is often referred to as the Law of Very Large Numbers.

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Authenticity is a tricky concept when it comes to people, and is increasingly being challenged both in psychology and even with regard to physical objects (with regard to objects, the value rather than reality of authenticity is questioned).  Writing for Scientific American, psychologist Scott Barry Kaufman deconstructs the psychological concept of authenticity nicely. But let’s start with a standard psychology definition of what this means:

Authenticity generally reflects the extent to which an individual’s core or true self is operative on a day-to-day basis. Psychologists characterize authenticity as multiple interrelated processes that have important implications for psychological functioning and well-being. Specifically, authenticity is expressed in the dynamic operation of four components: awareness (i.e., self-understanding), unbiased processing (i.e., objective self-evaluation), behavior (i.e., actions congruent with core needs, values, preferences), and relational orientation (i.e., sincerity within close relationships). Research findings indicate that each of these components relates to various aspects of healthy psychological and interpersonal adjustment.

My issue with this definition is that each of those components don’t necessarily add up to something greater than the sum of the parts. I understand the concept of unbiased processing, for example,  but this still tells me nothing about how it leads to authenticity, and by extension what authenticity is. How is it different than just being psychologically healthy, as measured by more specific traits?

Kaufman reviews the research on authenticity and show that really it’s just a rationalization for holding a favorably biased view of ourselves. People tend to think they are being authentic when they are acting on their virtues, being their best self, and also acting in ways that are congruent with societal expectations. The concept of authenticity is, in essence, used to manage one’s reputation. I am being authentic when doing things that other people will view positively, and not being my true self when I do things that will harm my reputation.

But as Kaufman points out – everything we do is a manifestation of some aspect of our true self. If you are acting in a way that is not congruent with your core values, you are still doing it for a reason that is part of your overall personality – that is part of your “true self.” If you are engaging in biased processing, or being insincere, these are part of who you are also – otherwise you wouldn’t be doing them.

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A Reddit thread in the Skeptic subreddit is framed as criticism toward skeptical philosophy. The questions it raises are all important, and honestly the poster should have just framed his points as questions rather than criticisms, because they reflect not problems with skeptical philosophy but their poor understanding of it. So the first lesson here is – humility. Don’t assume that an entire field you don’t fully understand is wrong. Rather, start with the assumption that you have more to learn, and then let proponents make their best case.

There are many good responses in the thread, which shows that a reasonable understanding of skeptical philosophy is out there in the community. The questions are very common beginner errors, and so they are worth responding to in detail. My first response, however, (as others in the thread have pointed out) is to begin with a basic text of the subject. Read a philosophy book. I humbly suggest The Skeptics’ Guide to the Universe, which is designed to be a primer on skeptical philosophy and directly addresses all of the poster’s questions. But there are many good books out there, and even basic philosophical books on epistemology will do (they don’t have to be explicitly skeptical).

I point this out because I frequently encounter people who are trying to do philosophy without even realizing it, or without an appreciation for the depth of philosophy as an intellectual field. Philosophy is one of those things that everyone thinks they can do, even without a lick of education on the topic. Inevitably they make basic mistakes, often ones that were dealt with thousands of years ago by the first philosophers. This would be no different than making pronouncements about a highly technical field of science without ever having studied it, and without really knowing the position of experts.

He begins:

‘Fact’ – What is a ‘fact’? Google search says: “a thing that is known or proved to be true”. Here is my problem: ‘known’…by whom? I am from India and have seen both villages and towns. Different things are ‘known’ in different communities. For example, people in rural areas ‘know’ there exists witches and ghosts.

This is a basic question of epistemology – how do we know anything, and what does it mean to know something? Here is also a pearl – don’t rely on essentially a dictionary definition for insight into a technical term or concept.

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I turns out they were only “mostly dead.” Well, it depends on your definition of death.

This is an interesting study that has been widely reported, with a surprisingly small amount of hype. The New York Times writes:

‘Partly Alive’: Scientists Revive Cells in Brains From Dead Pigs
In a study that upends assumptions about brain death, researchers brought some cells back to life — or something like it.

All the reporting I have seen so far has appropriate caveats, but they are really trying hard to maximize the sensational aspects of this study. I actually wrote about this study one year ago when the data was first presented. Now it has been published, so there is another round of reporting (which interestingly ignores the prior reporting).

The quick version is that Yale neuroscientists collected decapitated pig brains four hours after death and then tried to keep the brain cells alive in order to see what would happen. It’s actually a great real-life Frankenstein type experiment, a fact not missed by some outlets. Here is what they did: Continue Reading »