science and ethical consideration

Misinformation in and about science.

originally published as https://facultyopinions.com/article/739916951 – July 2021

There have been many calls for improved “scientific literacy”. Scientific literacy has been defined in a number of, often ambiguous, ways (see National Academies of Sciences and Medicine, 2016 {1}). According to Krajcik & Sutherland (2010) {2} it is “the understanding of science content and scientific practices and the ability to use that knowledge”, which implies “the ability to critique the quality of evidence or validity of conclusions about science in various media, including newspapers, magazines, television, and the Internet”. But what types of critiques are we talking about, and how often is this ability to critique, and the scientific knowledge it rests on, explicitly emphasized in the courses non-science (or science) students take? As an example, highlighted by Sabine Hossenfelder (2020) {3}, are students introduced to the higher order reasoning and understanding of the scientific enterprise needed to dismiss a belief in a flat (or a ~6000 year old) Earth?

While the sources of scientific illiteracy are often ascribed to social media, religious beliefs, or economically or politically motivated distortions, West and Bergstrom point out how scientists and the scientific establishment (public relations departments and the occasional science writer) also play a role. They identify the problems arising from the fact that the scientific enterprise (and the people who work within it) act within “an attention economy” and “compete for eyeballs just as journalists do.” The authors provide a review of all of the factors that contribute to misinformation within the scientific literature and its media ramifications, including the contribution of “predatory publishers” and call for “better ways of detecting untrustworthy publishers.” At the same time, there are ingrained features of the scientific enterprise that serve to distort the relevance of published studies, these include not explicitly identifying the organism in which the studies are carried out, and so obscuring the possibility that they might not be relevant to humans (see Kolata, 2013 {4}). There are also systemic biases within the research community. Consider the observation, characterized by Pandey et al. (2014) {5} that studies of “important” genes, expressed in the nervous system, are skewed: the “top 5% of genes absorb 70% of the relevant literature” while “approximately 20% of genes have essentially no neuroscience literature”. What appears to be the “major distinguishing characteristic between these sets of genes is date of discovery, early discovery being associated with greater research momentum—a genomic bandwagon effect”, a version of the “Matthew effect” described by Merton (1968) {6}. In the context of the scientific community, various forms of visibility (including pedigree and publicity) are in play in funding decisions and career advancement. Not pointed out explicitly by West and Bergstrom is the impact of disciplinary experts who pontificate outside of their areas of expertise and speculate beyond what can be observed or rejected experimentally, including speculations on the existence of non-observable multiverses, the ubiquity of consciousness (Tononi & Koch, 2015 {7}), and the rejection of experimental tests as a necessary criterion of scientific speculation (see Loeb, 2018 {8}) spring to mind.

Many educational institutions demand that non-science students take introductory courses in one or more sciences in the name of cultivating “scientific literacy”. This is a policy that seems to me to be tragically misguided, and perhaps based more on institutional economics than student learning outcomes. Instead, a course on “how science works and how it can be distorted” would be more likely to move students close to the ability to “critique the quality of evidence or validity of conclusions about science”. Such a course could well be based on an extended consideration of the West and Bergstrom article, together with their recently published trade book “Calling bullshit: the art of skepticism in a data-driven world” (Bergstrom and West, 2021 {9}), which outlines many of the ways that information can be distorted. Courses that take this approach to developing a skeptical (and realistic) approach to understanding how the sciences work are mentioned, although what measures of learning outcomes have been used to assess their efficacy are not described.

literature cited

Science literacy: concepts, contexts, and consequencesCommittee on Science Literacy and Public Perception of Science, Board on Science Education, Division of Behavioral and Social Sciences and Education, National Academies of Sciences, Engineering, and Medicine.2016 10 14; PMID: 27854404
Supporting students in developing literacy in science. Krajcik JS, Sutherland LM.Science. 2010 Apr 23; 328(5977):456-459PMID: 20413490
Flat Earth “Science”: Wrong, but not Stupid. Hossenfelder S. BackRe(Action) blog, 2020, Aug 22 (accessed Jul 29, 2021)
Mice fall short as test subjects for humans’ deadly ills. Kolata G. New York Times, 2013, Feb 11 (accessed Jul 29, 2021)
Functionally enigmatic genes: a case study of the brain ignorome. Pandey AK, Lu L, Wang X, Homayouni R, Williams RW.PLoS ONE. 2014; 9(2):e88889PMID: 24523945
The Matthew Effect in Science: The reward and communication systems of science are considered.Merton RK.Science. 1968 Jan 5; 159:56-63 PMID: 17737466
Consciousness: here, there and everywhere? Tononi G, Koch C.Philos Trans R Soc Lond B Biol Sci. 2015 May 19; 370(1668)PMID: 25823865
Theoretical Physics Is Pointless without Experimental Tests. Loeb A. Scientific American blog, 2018, Aug 10 [ Blog piece] (accessed Jul 29, 2021)
Calling bullshit: the art of skepticism in a data-driven world.Bergstrom CT, West JD. Random House Trade Paperbacks, 2021ISBN: ‎ 978-0141987057

Remembering the past and recognizing the limits of science …

A recent article in the Guardian reports on a debate at University College London (1) on whether to rename buildings because the people honored harbored odious ideological and political positions. Similar debates and decisions, in some cases involving unacceptable and abusive behaviors rather than ideological positions, have occurred at a number of institutions (see Calhoun at Yale, Sackler in NYC, James Watson at Cold Spring Harbor, Tim Hunt at the MRC, and sexual predators within the National Academy of Sciences). These debates raise important and sometimes troubling issues.

When a building is named after a scientist, it is generally in order to honor that person’s scientific contributions. The scientist’s ideological opinions are rarely considered explicitly, although they may influence the decision at the time. In general, scientific contributions are timeless in that they represent important steps in the evolution of a discipline, often by establishing a key observation, idea, or conceptual framework upon which subsequent progress is based – they are historically important. In this sense, whether a scientific contribution was correct (as we currently understand the natural world) is less critical than what that contribution led to. The contribution marks a milestone or a turning point in a discipline, understanding that the efforts of many underlie disciplinary progress and that those contributors made it possible for others to “see further.” (2)

Since science is not about recognizing or establishing a single unchanging capital-T-Truth, but rather about developing an increasingly accurate model for how the world works, it is constantly evolving and open to revision. Working scientists are not particularly upset when new observations lead to revisions to or the abandonment of ideas or the addition of new terms to equations.(3)

Compare that to the situation in the ideological, political, or religious realms. A new translation or interpretation of a sacred text can provoke schism and remarkably violent responses between respective groups of believers. The closer the groups are to one another, the more horrific the levels of violence that emerge often are. In contrast, over the long term, scientific schools of thought resolve, often merging with one another to form unified disciplines. From my own perspective, and not withstanding the temptation to generate new sub-disciplines (in part in response to funding factors), all of the life sciences have collapsed into a unified evolutionary/molecular framework. All scientific disciplines tend to become, over time, consistent with, although not necessarily deducible from, one another, particularly when the discipline respects and retains connections to the real (observable) world.(4) How different from the political and ideological.

The historical progression of scientific ideas is dramatically different from that of political, religious, or social mores. No matter what some might claim, the modern quantum mechanical view of the atom bears little meaningful similarity to the ideas of the cohort that included Leucippus and Democritus. There is progress in science. In contrast, various belief systems rarely abandon their basic premises. A politically right- or left-wing ideologue might well find kindred spirits in the ancient world. There were genocidal racists, theists, and nationalists in the past and there are genocidal racists, theists, and nationalists now. There were (limited) democracies then, as there are (limited) democracies now; monarchical, oligarchical, and dictatorial political systems then and now; theistic religions then and now. Absolutist ideals of innate human rights, then as now, are routinely sacrificed for a range of mostly self-serving or politically expedient reasons. Advocates of rule by the people repeatedly install repressive dictatorships. The authors of the United States Constitution declare the sacredness of human rights and then legitimized slavery. “The Bible … posits universal brotherhood, then tells Israel to kill all the Amorites.” (Phil Christman). The eugenic movement is a good example; for the promise of a genetically perfect future, existing people are treated inhumanely – just another version of apocalyptic (ends justify the means) thinking.

Ignoring the simpler case of not honoring criminals (sexual and otherwise), most calls for removing names from buildings are based on the odious ideological positions espoused by the honored – typically some version of racist, nationalistic, or sexist ideologies. The complication comes from the fact that people are complex, shaped by the context within which they grow up, their personal histories and the dominant ideological milieu they experienced, as well as their reactions to it. But these ideological positions are not scientific, although a person’s scientific worldview and their ideological positions may be intertwined. The honoree may claim that science “says” something unambiguous and unarguable, often in an attempt to force others to acquiesce to their perspective. A modern example would be arguments about whether climate is changing due to anthropogenic factors, a scientific topic, and what to do about it, an economic, political, and perhaps ideological question.(5)

So what to do? To me, the answer seems reasonably obvious – assuming that the person’s contribution was significant enough, we should leave the name in place and use the controversy to consider why they held their objectionable beliefs and more explicitly why they were wrong to claim scientific justification for their ideological (racist / nationalist / sexist / socially prejudiced) positions.(6) Consider explicitly why an archeologist (Flinders Petrie), a naturalist (Francis Galton), a statistician (Karl Pearson), and an advocate for women’s reproductive rights (Marie Stopes) might all support the non-scientific ideology of eugenics and forced sterilization. We can use such situations as a framework within which to delineate the boundaries between the scientific and the ideological.

Understanding this distinction is critical and is one of the primary justifications for why people not necessarily interested in science or science-based careers are often required to take science courses. Yet all too often these courses fail to address the constraints of science, the difference between political and ideological opinions, and the implications of scientific models. I would argue that unless students (and citizens) come to understand what constitutes a scientific idea or conclusion and what reflects a political or ideological position couched in scientific or pseudo-scientific terms, they are not learning what they need to know about science or its place in society. That science is used as a proxy for Truth writ large is deeply misguided. It is much more important to understand how science works than it is to remember the number of phyla or the names of amino acids, the ability to calculate the pH of a solution, or to understand processes going on at the center of a galaxy or the details of a black hole’s behavior. While sometimes harmless, misunderstanding science and how it is used socially can result in traumatic social implications, such as drawing harmful conclusions about individuals from statistical generalizations of populations, avoidable deaths from measles, and the forced “eugenic” sterilization of people deemed defective. We should seek out and embrace opportunities to teach about these issues, even if it means we name buildings after imperfect people.

footnotes:

The location of some of my post-doc work.
In the words of Isaac Newton, “If I have seen further than others, it is by standing upon the shoulders of giants.”
Unless, of course, the ideas and equations being revised or abandoned are one’s own.
Perhaps the most striking exception occurs in physics on the subjects of quantum mechanics and relativity, but as I am not a physicist, I am not sure about that.
Perhaps people are “meant” to go extinct.
The situation is rather different outside of science, because the reality of progress is more problematic and past battles continue to be refought. Given the history of Reconstruction and the Confederate “Lost Cause” movement [see PBS’s Reconstruction] following the American Civil War, monuments to defenders of slavery, no matter how admirable they may have been in terms of personal bravery and such, reek of implied violence, subjugation, and repression, particularly when the person honored went on to found an institution dedicated to racial hatred and violent intimidation [link]. There would seem little doubt that a monument in honor of a Nazi needs to be eliminated and replaced by one to their victims or to those who defeated them.

On teaching genetics, social evolution and understanding the origins of racism

Links between genetics and race crop up periodically in the popular press (link; link), but the real, substantive question, and the topic of a number of recent essays (see Saletan. 2018a. Stop Talking About Race and IQ) is whether the idea of “race” as commonly understood, and used by governments to categorize people (link), makes scientific sense. More to the point, do biology educators have an unmet responsibility to modify and extend their materials and pedagogical approaches to address the non-scientific, often racist, implications of racial characterizations. Such questions are complicated by a second factor, independent of whether the term race has any useful scientific purpose, namely to help students understand the biological (evolutionary) origins of racism itself, together with the stressors that lead to its periodic re-emergence as a socio-political factor. In times of social stress, reactions to strangers (others) identified by variations in skin color or overt religious or cultural signs (dress), can provoke hostility against those perceived to be members of a different social group. As far as I can tell, few in the biology education community, which includes those involved in generating textbooks, organizing courses and curricula, or the design, delivery, and funding of various public science programs, including PBS’s NOVA, the science education efforts of HHMI and other private foundations, and programs such as Science Friday on public radio, directly address the roots of racism, roots associated with biological processes such as the origins and maintenance of multicellularity and other forms of social organization among organisms, involved in coordinating their activities and establishing defenses against social cheaters and processes such as cancer, in an organismic context (1). These established defense mechanisms can, if not recognized and understood, morph into reflexive and unjustified intolerance, hostility toward, and persecution of various “distinguishable others.” I will consider both questions, albeit briefly, here.

Two factors have influenced my thinking about these questions. The first involves the design of the biofundamentals text/course and its extension to include topics in genetics (2). This involved thinking about what is commonly taught in genetics, what is critical for students to know going forward (and by implication what is not), and where materials on genetic processes best fit into a molecular biology curriculum (3). While engaged in such navel gazing there came an email from Malcolm Campbell describing student responses to the introduction of a chapter section on race and racism in his textbook Integrating Concepts in Biology. The various ideas of race, the origins of racism, and the periodic appearance of anti-immigrant, anti-religious and racist groups raise important questions – how best to clarify what is an undeniable observation, that different, isolated, sub-populations of a species can be distinguished from one another (see quote from Ernst Mayr’s 1994 “Typological versus Population thinking” →), from the deeper biological reality, that at the level of the individual these differences are meaningless. In what I think is an interesting way, the idea that people can be meaningfully categorized as different types of various platonic ideals (for example, as members of one race or the other) based on anatomical / linguistic differences between once distinct sub-populations of humans is similar to the dichotomy between common wisdom (e.g. that has influenced people’s working understanding of the motion of objects) and the counter-intuitive nature of empirically established scientific ideas (e.g. Newton’s laws and the implications of Einstein’s theory of general relativity). What appears on the surface to be true but in fact is not. In this specific case, there is a pressure toward what Mayr terms “typological” thinking, in which we class people into idealized (platonic) types or races (↓).

As pointed out most dramatically, and repeatedly, by Mayr (1985; 1994; 2000), and supported by the underlying commonality of molecular biological mechanisms and the continuity of life, stretching back to the last universal common ancestor, there are only individuals who are members of various populations that have experienced various degrees of separation from one another. In many cases, these populations have diverged and, through geographic, behavioral, and structure adaptations driven by natural, social, and sexual selection together with the effects of various events, some non-adaptive, such as bottlenecks, founder effects, and genetic drift, may eventually become reproductively isolated from one another, forming new species. An understanding of evolutionary principles and molecular mechanisms transforms biology from a study of non-existent types to a study of populations with their origins in common, sharing a single root – the last universal common ancestor (LUCA). Over the last ~200,000 years the movement of humans first within Africa and then across the planet has been impressive (→). These movements have been accompanied by the fragmentation of human populations. Campbell and Tishkoff (2008) identified 13 distinct ancestral African populations while Busby et al (2016) recognized 48 sub-saharan population groups. The fragmentation of the human population is being reversed (or rather rendered increasingly less informative) by the effects of migration and extensive intermingling (↓).

Ideas, such as race (and in a sense species), try to make sense of the diversity of the many different types of organisms we observe. They are based on a form of essentialist or typological thinking – thinking that different species and populations are completely different “kinds” of objects, rather than individuals in a population connected historically to all other living things. Race is a more pernicious version of this illusion, a pseudo-scientific, political and ideological idea that postulates that humans come in distinct, non-overlapping types (quote ↓ again, from Mayr). Such a weird idea underlies various illogical and often contradictory legal “rules” by which a person’s “race” is determined.

Given the reality of the individual and the unreality of race, racial profiling (see Satel,
2002) can lead to serious medical mistakes, as made clear in the essays by Acquaviva & Mintz (2010) “Are We Teaching Racial Profiling?”, Yudell et al (2016) “Taking Race out of Human Genetics”, and Donovan (2014) “The impact of the hidden curriculum”.

The idea of race as a type fails to recognize the dynamics of the genome over time. If possible (sadly not) a comparative analysis of the genome of a “living fossil”, such as modern day coelacanths and their ancestors (living more than 80 million years ago) would likely reveal dramatic changes in genomic DNA sequence. In this light the fact that between 100 to 200 new mutations are introduced into the human genome per generation (see Dolgin 2009 Human mutation rate revealed) seems like a useful number to be widely appreciated by students, not to mention the general public. Similarly, the genomic/genetic differences between humans, our primate relatives, and other mammals and the mechanisms behind them (Levchenko et al., 2017)(blog link) would seem worth considering and explicitly incorporating into curricula on genetics and human evolution.

While race may be meaningless, racism is not. How to understand racism? Is it some kind of political artifact, or does it arise from biological factors. Here, I believe, we find a important omission in many biology courses, textbooks, and curricula – namely an introduction and meaningful discussion of social evolutionary mechanisms. Many is the molecular/cell biology curriculum that completely ignores such evolutionary processes. Yet, the organisms that are the primary focus of biological research (and who pay for such research, e.g. humans) are social organisms at two levels. In multicellular organisms somatic cells, which specialize to form muscular, neural, circulatory and immune systems, bone and connective tissues, sacrifice their own inter-generational reproductive future to assist their germ line (sperm and/or eggs) relatives, the cells that give rise to the next generation of organisms, a form of inclusive fitness (Dugatkin, 2007). Moreover, humans are social organisms, often sacrificing themselves, sharing their resources, and showing kindness to other members of their group. This social cooperation is threatened by cheaters of various types (POST LINK). Unless these social cheaters are suppressed, by a range of mechanisms, and through processes of kin/group selection, multicellular organisms die and socially dysfunctional social populations are likely to die out. Without the willingness to cooperate, and when necessary, self-sacrifice, social organization is impossible – no bee hives, no civilizations. Imagine a human population composed solely of people who behave in a completely selfish manner, not honoring their promises or social obligations.

A key to social interactions involves recognizing those who are, and who are not part of your social group. A range of traits can serve as markers for social inclusion. A plausible hypothesis is that the explicit importance of group membership and defined social interactions becomes more critical when a society, or a part of society, is under stress. Within the context of social stratification, those in the less privileged groups may feel that the social contract has been broken or made a mockery of. The feeling (apparent reality) that members of “elite” or excessively privileged sub-groups are not willing to make sacrifices for others serves as evidence that social bonds are being broken (4). Times of economic and social disruption (migrations and conquests) can lead to increased explicit recognition of both group and non-group identification. The idea that outsiders (non-group members) threaten the group can feed racism, a justification for why non-group members should be treated differently from group members. From this position it is a small (conceptual) jump to the conclusion that non-group members are somehow less worthy, less smart, less trustworthy, less human – different in type from members of the group – many of these same points are made in an op-ed piece by Judis. 2018. What the Left Misses About Nationalism.

That economic or climatic stresses can foster the growth of racist ideas is no new idea; consider the unequal effects of various disruptions likely to be associated with the spread of automation (quote from George Will ↓) and the impact of climate change on migrations of groups within and between countries (see Saletan 2018b: Why Immigration Opponents Should Worry About Climate Change) are likely to spur various forms of social unrest, whether revolution or racism, or both – responses that could be difficult to avoid or control.

So back to the question of biology education – in this context understanding the ingrained responses of social creatures associated with social cohesion and integrity need to be explicitly presented. Similarly, variants of such mechanisms occur within multicellular organisms and how they work is critical to understanding how diseases such as cancer, one of the clearest forms of a cheater phenotype, are suppressed. Social evolutionary mechanisms provide the basis for understanding a range of phenomena, and the ingrained effects of social selection may be seen as one of the roots of racism, or at the very least a contributing factor worth acknowledging explicitly.

Thanks to Melanie Cooper and Paul Strode for comments. Minor edits 4 May 2019.

Footnotes:

It is an interesting possibility whether the 1%, or rather the super 0.1% represent their own unique form of social parasite, leading periodically to various revolutions – although sadly, new social parasites appear to re-emerge quite quickly.
A part of the CoreBIO-biofundamentals project
At this point it is worth noting that biofundamentals itself includes sections on social evolution, kin/group and sexual selection (see Klymkowsky et al., 2016; LibreText link).
One might be forgiven for thinking that rich and privileged folk who escape paying what is seen as their fair share of taxes, might be cast as social cheaters (parasites) who, rather than encouraging racism might lead to revolutionary thoughts and actions.

Literature cited:

Acquaviva & Mintz. (2010). Perspective: Are we teaching racial profiling? The dangers of subjective determinations of race and ethnicity in case presentations. Academic Medicine 85, 702-705.

Busby et al. (2016). Admixture into and within sub-Saharan Africa. Elife 5, e15266.

Campbell & Tishkoff. (2008). African genetic diversity: implications for human demographic history, modern human origins, and complex disease mapping. Annu. Rev. Genomics Hum. Genet. 9, 403-433.

Donovan, B.M. (2014). Playing with fire? The impact of the hidden curriculum in school genetics on essentialist conceptions of race. Journal of Research in Science Teaching 51: 462-496.

Dugatkin, L. A. (2007). Inclusive fitness theory from Darwin to Hamilton. Genetics 176, 1375-1380.

Klymkowsky et al., (2016). The design and transformation of Biofundamentals: a non-survey introductory evolutionary and molecular biology course..” LSE Cell Biol Edu pii: ar70.

Levchenko et al., (2017). Human accelerated regions and other human-specific sequence variations in the context of evolution and their relevance for brain development. Genome biology and evolution 10, 166-188.

Mayr, E. (1985). The Growth of Biological Thought: Diversity, Evolution, and Inheritance. Cambridge, MA: Belknap Press of Harvard University Press.

Mayr, E. (1994). Typological versus population thinking. Conceptual issues in evolutionary biology, 157-160.

—- (2000). Darwin’s influence on modern thought. Scientific American 283, 78-83.

Satel, S. (2002). I am a racially profiling doctor. New York Times 5, 56-58.

Yudell et al., (2016). Taking race out of human genetics. Science 351, 564-565.

Can we talk scientifically about free will?

(edited and updated – 3 May 2019)

For some, the scientific way of thinking is both challenging and attractive. Thinking scientifically leads to an introduction to, and sometimes membership in a unique community, who at their best are curious, critical, creative, and receptive to new and mind-boggling ideas, anchored in objective (reproducible) observations whose implications can be rigorously considered (1).

What I particularly love about science is its communal aspect, within which the novice can point to a new observation or logical limitation, and force the Nobel laureate (assuming that they remain cognitively nimble, ego-flexible, and interested in listening) to rethink and revise there positions. Add to that the amazing phenomena that the scientific enterprise has revealed to us, the apparent age and size of the universe, the underlying unity, and remarkable diversity of life, the mind-bending behavior of matter-energy at the quantum level, and the apparent bending of space-time. Yet, and not withstanding the power of the scientific approach, there are many essential topics that simply cannot be studied scientifically, and even more in which a range of practical constraints seriously limit our ability to come to meaningful conclusions.

Perhaps acknowledging the limits of science is nowhere more important than in the scientific study of consciousness and self-consciousness. While we can confidently dismiss various speculations (often from disillusioned and displaced physicists) that all matter is “conscious” (2), or mystical speculations on the roles of super-natural forces (spirits and such), we need to recognize explicitly why studying consciousness and self-consciousness remains an extremely difficult and problematic area of research. One aspect is that various scientific-sounding pronouncements on the impossibility or illusory nature of free will have far ranging and largely pernicious if not down right toxic social and personal implications. Denying the possibility of free will implies that people are not responsible for their actions – and so cannot reasonably be held accountable. In a broader sense, such a view can be seen as justifying treating people as disposable machines, to be sacrificed for some ideological or religious faith (3). It directly contradicts the founding presumptions and aspirations behind the enterprise that is the United States of America, as articulated by Thomas Jefferson, a fragile bulwark against sacrificing individuals on the alter of often pseudoscientific or half-baked ideas.

So the critical question is, is there a compelling reason to take pronouncements such as those that deny the reality of free will, seriously? I think not. I would assume that all “normal” human beings come to feel that there is someone (them) listening to various aspects of neural activity and that they (the listener) can in turn decide (or at the very least influence) what happens next, how they behave, what they think and how they feel. All of which is to say that there is an undeniable (self-evident) reality associated with self-consciousness, as well as the feeling of (at least partial) control.

This is not to imply that humans (and other animals) are totally in control of their thoughts and actions, completely “free” – obviously not. First, one’s life history and the details of a situation can dramatically impact thoughts and behaviors, and much of that is based on luck, a range of hereditary factors, our experiences (both long and short term) that combine to influence our response to a particular situation – recognition of which is critical for developing empathy for ourselves and others (see The radical moral implications of luck in human life). At the same time how we (our brain) experiences and interprets what our brain (also us) is “saying” to itself is based on genetically and developmentally shaped neural circuitry and signaling systems that influence the activities of complex ensembles of interconnected cellular systems – it is not neurons firing in deterministic patterns, since at the cellular level there are multiple stochastic processes that influence the behaviors of neural networks. There is noise (spontaneous activity) that impacts patterns of neuronal signaling, as well as stochastic processes, such as the timing of synaptic vesicle fusion events, the cellular impacts of diffusing molecules, the monoallelic expression of genes (Deng et al., 2014; Zakharova et al., 2009) and various feedback networks that can lead to subtle and likely functional differences between apparently identical cells of what appear to be the “same” type (for the implications of stochastic, single cell processes see: Biology education in the light of single cell/molecule studies).

So let us consider what it would take to make a fully deterministic model of the brain, without considering for the moment the challenges associated with incorporating the effects of molecular and cellular level noise. First there is the inherent difficulty (practical impossibility) of fully characterizing the properties of the living human brain, with its ~100,000,000,000 neurons, making ~7,000,000,000,000,000 synapses with one another, and interacting in various ways with ~100,000,000,000 glia that include non-neuronal astrocytes, oligodendrocytes, and immune system microglia (von Bartheld et al., 2016). These considerations ignore the recently discovered effects of the rest of the body (and its microbiome) on the brain (see Mayer et al., 2014; Smith, 2015).

Then there is the fact that measuring a system changes a system. In a manner analogous to the Heisenberg uncertainty principle, measuring aspects of neuronal function (or glial-neural interactions) will necessarily involve perturbations to the examined cells – recent studies have used a range of light emitting reporters to follow various aspects of neuronal activity (see Lin and Schnitzer, 2016), but these reporters also perturb the system, if only through heating effects associated with absorbing and emitting light. Or if they, for example, serve to report the levels of intracellular calcium ions, involved in a range of cellular behaviors, they will necessarily influence calcium ion concentrations, etc. Such high resolution analyses, orders of magnitude higher than functional MRI (fMRI) studies would likely kill or cripple the person measured. The more accurate the measurement, the more perturbed, and the more altered future behaviors can be expected to be and the less accurate our model of the functioning brain will be.

There is, however, another more practical question to consider, namely are current neurobiological methods adequate for revealing how the brain works. This point has been made in a particularly interesting way by Jonas & Kording (2017) in their paper “Could a neuroscientist understand a microprocessor?” – their analysis indicates the answer is “probably not”, even though such a processor represents a completely deterministic system.

If it is not possible to predict the system, then any discussion of free will or determinism is mute – unknowable and in an important scientific sense uninteresting. In a Popperian way (only the ability to predict and falsify interesting predictions makes, at the end of the day, something scientifically useful.

I have little intelligent to say about artificial intelligence, since free will and intelligence are rather different things. While it is clearly possible to build a computer system (hardware and software) that can beat people at complex games such as chess (Kasparov, 2010; see AlphaZero) and GO (Silver et al., 2016), it remains unclear whether a computer can “want” to play chess or go in the same way as a human being does. We can even consider the value of evolving free will, as a way to confuse our enemies and seduce love interests or non-sexual social contacts. Brembs (2010) presents an interesting paper on the evolutionary value of free will in lower organisms (invertebrates).

What seems clear to me (and considered before: The pernicious effects of disrespecting the constraints of science) is that the damage, social, emotional, and political, associated with claiming to have come to an “scientifically established” conclusion on topics that are demonstrably beyond the scope of scientific resolution, conclusions that make a completely knowable and strictly deterministic universe impossible to attain) should be explained and understood to both the general public and stressed on and by the scientific and educational community. They could be seen as a form of scientific malpractice that should be, quite rightly, dismissed out of hand. Rather than become the focus of academic or public debate, they are best ignored and those who promulgate them, often out of careerist motivations (or just arrogance) should be pitied, rather than being promoted as public intellectuals to be taken seriously.A note on images: Parts of the header image are modified from images created by Tom Edwards (of WallyWare fame) and used by permission. The “Becky O” Bad Mom card by Roz Chast is used by permission. Thanks to Michael Stowell for pointing out the work of Jonas and Kording. Also it turns out that physicist Sabine Hossenfelder has recently had something to say on the subject. Minor updates and the re-insertion of figures – 26 October 2020.

Footnotes

1. We won’t consider them at their worst, suffice it to say, they can embrace all that is wrong with humanity, leading to a range of atrocities.

3. The universe may be conscious, say prominent scientists

4. A common topic of the philosopher John Gray: Believing in Reason is Childish

Literature cited:

Brembs, B. (2010). Towards a scientific concept of free will as a biological trait: spontaneous actions and decision-making in invertebrates. Proceedings of the Royal Society of London B: Biological Sciences, rspb20102325.

Deng, Q., Ramsköld, D., Reinius, B. and Sandberg, R. (2014). Single-cell RNA-seq reveals dynamic, random monoallelic gene expression in mammalian cells. Science 343, 193-196.

Kasparov, G. (2010). The chess master and the computer. The New York Review of Books 57, 16-19.

Lin, M. Z. and Schnitzer, M. J. (2016). Genetically encoded indicators of neuronal activity. Nature neuroscience 19, 1142.

Jonas, E., & Kording, K. P. (2017). Could a neuroscientist understand a microprocessor?. PLoS computational biology, 13, e1005268.

Mayer, E. A., Knight, R., Mazmanian, S. K., Cryan, J. F., & Tillisch, K. (2014). Gut microbes and the brain: paradigm shift in neuroscience. Journal of Neuroscience, 34, 15490-15496.

Silver et al. (2016). Mastering the game of Go with deep neural networks and tree search. nature 529, 484.

Smith, P. A. (2015). The tantalizing links between gut microbes and the brain. Nature News, 526, 312.

von Bartheld, C. S., Bahney, J. and Herculano‐Houzel, S. (2016). The search for true numbers of neurons and glial cells in the human brain: a review of 150 years of cell counting. Journal of Comparative Neurology 524, 3865-3895.

Zakharova, I. S., Shevchenko, A. I. and Zakian, S. M. (2009). Monoallelic gene expression in mammals. Chromosoma 118, 279-290.

Balancing research prestige, human decency, and educational outcomes.

Or why do academic institutions shield predators? Many working scientists, particularly those early in their careers or those oblivious to practical realities, maintain an idealistic view of the scientific enterprise. They see science as driven by curious, passionate, and skeptical scholars, working to build an increasingly accurate and all encompassing understanding of the material world and the various phenomena associated with it, ranging from the origins of the universe and the Earth to the development of the brain and the emergence of consciousness and self-consciousness (1). At the same time, the discipline of science can be difficult to maintain (see PLoS post: The pernicious effects of disrespecting the constraints of science). Scientific research relies on understanding what people have already discovered and established to be true; all too often, exploring the literature associated with a topic can reveal that one’s brilliant and totally novel “first of its kind” or “first to show” observation or idea is only a confirmation or a modest extension of someone else’s previous discovery. That is the nature of the scientific enterprise, and a major reason why significant new discoveries are rare and why graduate students’ Ph.D. theses can take years to complete.

Acting to oppose a rigorous scholarly approach are the real life pressures faced by working scientists: a competitive landscape in which only novel observations get rewarded by research grants and various forms of fame or notoriety in one’s field, including a tenure-track or tenured academic position. Such pressures encourage one to distort the significance or novelty of one’s accomplishments; such exaggerations are tacitly encouraged by the editors of high profile journals (e.g. Nature, Science) who seek to publish “high impact” claims, such as the claim for “Arsenic-life” (see link). As a recent and prosaic example, consider a paper that claims in its title that “Dietary Restriction and AMPK Increase Lifespan via Mitochondrial Network and Peroxisome Remodeling” (link), without mentioning (in the title) the rather significant fact that the effect was observed in the nematode C. elegans, whose lifespan is typically between 300 to 500 hours and which displays a trait not found in humans (and other vertebrates), namely the ability to assume a highly specialized “dauer” state that can survive hostile environmental conditions for months. Is the work wrong or insignificant? Certainly not, but it is presented to the unwary (through the Harvard Gazette under the title, “In pursuit of healthy aging: Harvard study shows how intermittent fasting and manipulating mitochondrial networks may increase lifespan,” with the clear implication that people, including Harvard alumni, might want to consider the adequacy of their retirement investments

Such pleas for attention are generally quickly placed in context and their significance evaluated, at least within the scientific community – although many go on to stimulate the economic health of the nutritional supplement industry. Lower level claims often go unchallenged, just part of the incessant buzz associated with pleas for attention in our excessively distracted society (see link). Given the reward structure of the modern scientific enterprise, the proliferation of such claims is not surprising. Even “staid” academics seek attention well beyond the immediate significance of their (tax-payer funded) observations. Unfortunately, the explosively expanding size of the scientific enterprise makes policing such transgressions (generally through peer review or replication) difficult or impossible, at least in the short term.

The hype and exaggeration associated with some scientific claims for attention are not the most distressing aspect of the quest for “reputation.” Rather, there are growing number of revelations of academic institutions protecting those guilty of abusing their dependent colleagues. These reflect how scientific research teams are organized. Most scientific studies involve groups of people working with one another, generating data, testing ideas, and eventually publishing their observations and conclusions, and speculating on their broader implications.

Research groups can vary greatly in size. In some areas, they involve isolated individuals, whether thinkers (theorists) or naturalists, in the mode of Darwin and Wallace. In other cases, these are larger and include senior researchers, post-doctoral fellows, graduate students, technicians, undergraduates, and even high school students. Such research groups can range from the small (2 to 3 people) to the significantly larger (~20-50 people); the largest of such groups are associated mega-projects, such as the human genome project and the Large Hadron Collider-based search for the Higgs boson (see: Physics paper sets record with more than 5,000 authors). A look at this site [link] describing the human genome project reflects two aspects of such mega-science: 1) while many thousands of people were involved [see Initial sequencing and analysis of the human genome], generally only the “big names” are singled out for valorization (e.g., receiving a Nobel Prize). That said, there would be little or no progress without general scientific community that evaluates and extends ideas and observations. In this context, “lead investigators” are charged primarily with securing the funds needed to mobilize such groups, convincing funders that the work is significant; it is members of the group that work out the technical details and enable the project to succeed.

As with many such social groups, there are systems in play that serve to establish the status of the individuals involved – something necessary (apparently) in a system in which individuals compete for jobs, positions, and resources. Generally, one’s status is established through recommendations from others in the field, often the senior member(s) of one’s research group or the (generally small) group of senior scientists who work in the same or a closely related area. The importance of professional status is particularly critical in academia, where the number of senior (e.g. tenured or tenure-track professorships) is limited. The result is a system that is increasingly susceptible to the formation of clubs, membership in which is often determined by who knows who, rather than who has done what (see Steve McKnight’s “The curse of committees and clubs”). Over time, scientific social status translates into who is considered productive, important, trustworthy, or (using an oft-misused term) brilliant. Achieving status can mean putting up with abusive and unwanted behaviors (particularly sexual). Examples of this behavior have recently been emerging with increasing frequency (which has been extensively described elsewhere: see Confronting Sexual Harassment in Science; More universities must confront sexual harassment; What’s to be done about the numerous reports of faculty misconduct dating back years and even decades?; Academia needs to confront sexism; and The Trouble With Girls’: The Enduring Sexism in Science).

So why is abusive behavior tolerated? One might argue that this reflects humans’ current and historical obsession with “stars,” pharaohs, kings, and dictators as isolated geniuses who make things work. Perhaps the most visible example of such abused scientists (although there are in fact many others : see History’s Most Overlooked Scientists) is Rosalind Franklin, whose data was essential to solving the structure of double stranded DNA, yet whose contributions were consistently and systematically minimized, a clear example of sexual marginalization. In this light, many is the technician who got an experiment to “work,” leading to their research supervisor’s being awarded the prizes associated with the breakthrough (2).

Amplifying the star effect is the role of research status at the institutional level; an institution’s academic ranking is often based upon the presence of faculty “stars.” Perhaps surprisingly to those outside of academia, an institution’s research status, as reflected in the number of stars on staff, often trumps its educational effectiveness, particularly with undergraduates, that is the people who pay the bulk of the institution’s running costs. In this light, it is not surprising that research stars who display various abusive behavior (often to women) are shielded by institutions from public censure.

So what is to be done? My own modest proposal (to be described in more detail in a later post) is to increase the emphasis on institution’s (and departments within institutions) effectiveness at undergraduate educational success. This would provide a counter-balancing force that could (might?) place research status in a more realistic context.

a footnote or two:

on the assumption that there is nothing but a material world.
Although I am no star, I would acknowledge Joe Dent, who worked out the whole-mount immunocytochemical methods that we have used extensively in our work over the years).
Thanks to Becky for editorial comments as well as a dramatic reading!

Is it time to start worrying about conscious human “mini-brains”?

A human iPSC cerebral organoid in which pigmented retinal epithelial cells can be seen (from the work of McClure-Begley et al.). Also see “Can lab-grown brains become conscious?” by Sara Readon Nature 2020.

The fact that experiments on people are severely constrained is a major obstacle in understanding human development and disease. Some of these constraints are moral and ethical and clearly appropriate and necessary given the depressing history of medical atrocities. Others are technical, associated with the slow pace of human development. The combination of moral and technical factors has driven experimental biologists to explore the behavior of a wide range of “model systems” from bacteria, yeasts, fruit flies, and worms to fish, frogs, birds, rodents, and primates. Justified by the deep evolutionary continuity between these organisms (after all, all organisms appear to be descended from a single common ancestor and share many molecular features), experimental evolution-based studies of model systems have led to many therapeutically valuable insights in humans – something that I suspect a devotee of intelligent design creationism would be hard pressed to predict or explain (post link).

While humans are closely related to other mammals, it is immediately obvious that there are important differences – after all people are instantly recognizable from members of other closely related species and certainly look and behave differently from mice. For example, the surface layer of our brains is extensively folded (they are known as gyrencephalic) while the brain of a mouse is smooth as a baby’s bottom (and referred to as lissencephalic). In humans, the failure of the brain cortex to fold is known as lissencephaly, a disorder associated with severe neurological defects. With the advent of more and more genomic sequence data, we can identify human specific molecular (genomic) differences. Many of these sequence differences occur in regions of our DNA that regulate when and where specific genes are expressed. Sholtis & Noonan (1) provide an example: the HACNS1 locus is a 81 basepair region that is highly conserved in various vertebrates from birds to chimpanzees; there are 13 human specific changes in this sequence that appear to alter its activity, leading to human-specific changes in the expression of nearby genes (↓). At this point ~1000 genetic elements that are different in humans compared to other vertebrates have been identified and more are likely to emerge (2). Such human-specific changes can make modeling human-specific behaviors, at the cellular, tissue, organ, and organism level, in non-human model systems difficult and problematic (3, 4). It is for this reason that scientists have attempted to generate better human specific systems.

One particularly promising approach is based on what are known as embryonic stem cells (ESCs) or pluripotent stem cells (PSCs). Human embryonic stem cells are generated from the inner cell mass of a human embryo and so involve the destruction of that embryo – which raises a number of ethical and religious concerns as to when “life begins” (5). Human pluripotent stem cells are isolated from adult tissues but in most cases require invasive harvesting methods that limit their usefulness. Both ESCs and PSCs can be grown in the laboratory and can be induced to differentiate into what are known as gastruloids. Such gastruloids can develop anterior-posterior (head-tail), dorsal-ventral (back-belly), and left-right axes analogous to those found in embryos (6) and adults (top panel ↓). In the case of PSCs, the gastruloid (bottom panel ↓) is essentially a twin of the organism from which the PSCs were derived, a situation that raises difficult questions: is it a distinct individual, is it the property of the donor or the creation of a technician. The situation will be further complicated if (or rather, when) it becomes possible to generate viable embryos from such gastruloids.

The Nobel prize winning work of Kazutoshi Takahashi and Shinya Yamanaka (7), who devised methods to take differentiated (somatic) human cells and reprogram them into ESC/PSC-like cells, cells known as induced pluripotent stem cells (iPSCs)(8), represented a technical breakthrough that jump-started this field. While the original methods derived sample cells from tissue biopsies, it is possible to reprogram kidney epithelial cells recovered from urine, a non-invasive approach (9, 10). Subsequently, Madeline Lancaster, Jurgen Knōblich, and colleagues devised an approach by which such cells could be induced to form what they termed “cerebral organoids” (although Yoshiki Sasai and colleagues were the first to generate neuronal organoids); they used this method to examine the developmental defects associated with microencephaly (11). The value of the approach was rapidly recognized and a number of studies on human conditions, including lissencephaly (12), Zika-virus infection-induced microencephaly (13), and Down’s syndrome (14); investigators have begun to exploit these methods to study a range of human diseases – and rapid technological progress is being made.

The production of cerebral organoids from reprogrammed human somatic cells has also attracted the attention of the media (15). While “mini-brain” is certainly a catchier name, it is a less accurate description of a cerebral organoid, itself possibly a bit of an overstatement, since it is not clear exactly how “cerebral” such organoids are. For example, the developing brain is patterned by embryonic signals that establish its asymmetries; it forms at the anterior end of the neural tube (the nascent central nervous system and spinal cord) and with distinctive anterior-posterior, dorsal-ventral, and left-right asymmetries, something that simple cerebral organoids do not display. Moreover, current methods for generating cerebral organoids involve primarily what are known as neuroectodermal cells – our nervous system (and that of other vertebrates) is a specialized form of the embryo’s surface layer that gets internalized during development. In the embryo, the developing neuroectoderm interacts with cells of the circulatory system (capillaries, veins, and arteries), formed by endothelial cells and what are known as pericytes that surround them. These cells, together with interactions with glial cells (astrocytes, a non-neuronal cell type) combine to form the blood brain barrier. Other glial cells (oligodendrocytes) are also present; in contrast, both types of glia (astrocytes and oligodendrocytes) are rare in the current generation of cerebral organoids. Finally, there are microglial cells, immune system cells that originate from outside the neuroectoderm; they invade and interact with neurons and glia as part of the brain’s dynamic neural system. The left panel of the figure shows, in highly schematic form how these cells interact (16). The right panel is a drawing of neural tissue stained by the Golgi method (17), which reveals ~3-5% of the neurons present. There are at least as many glial cells present, as well as microglia, none of which are visible in the image. At this point, cerebral organoids typically contain few astrocytes and oligodendrocytes, no vasculature, and no microglia. Moreover, they grow to be about 1 to 3 mm in diameter over the course of 6 to 9 months; that is significantly smaller in volume than a fetal or newborn’s brain. While cerebral organoids can generate structures characteristic of retinal pigment epithelia (top figure) and photo-responsive neurons (18), such as those associated with the retina, an extension of the brain, it is not at all clear that there is any significant sensory input into the neuronal networks that are formed within a cerebral organoid, or any significant outputs, at least compared to the role that the human brain plays in controlling bodily and mental functions.

The reasonable question, then, must be whether a cerebral organoid, which is a relatively simple system of cells (although itself complex), is conscious. It becomes more reasonable as increasingly complex systems are developed, and such work is proceeding apace. Already researchers are manipulating the developing organoid’s environment to facilitate axis formation, and one can anticipate the introduction of vasculature. Indeed, the generation of microglia-like cells from iPSCs has been reported; such cells can be incorporated into cerebral organoids where they appear to respond to neuronal damage in much the same way as microglia behave in intact neural tissue (19).

We can ask ourselves, what would convince us that a cerebral organoid, living within a laboratory incubator, was conscious? How would such consciousness manifest itself? Through some specific pattern of neural activity, perhaps? As a biologist, albeit one primarily interested in molecular and cellular systems, I discount the idea, proposed by some physicists and philosophers as well as the more mystical, that consciousness is a universal property of matter (20,21). I take consciousness to be an emergent property of complex neural systems, generated by evolutionary mechanisms, built during embryonic and subsequent development, and influenced by social interactions (BLOG LINK) using information encoded within the human genome (something similar to this: A New Theory Explains How Consciousness Evolved). While a future concern, in a world full of more immediate and pressing issues, it will be interesting to listen to the academic, social, and political debate on what to do with mini-brains as they grow in complexity and perhaps inevitably, towards consciousness.

Footnotes and references

Thanks to Rebecca Klymkowsky, Esq. and Joshua Sanes, Ph.D. for editing and disciplinary support. Minor updates and the reintroduction of figures 22 Oct. 2020.