Bias

This note is about bias that results from subjectivity, for example the many human biases, including the bias for finding narrative, meaning, and order where they do not exist.

For evidence, see: Human Bias.

Herzen wrote in an article entitled “Apropos of a Drama”:

"There is something about chance that is intolerably repellent to a free spirit…. He wants the misfortunes that overtake him to be predestined—that is, to exist in connection with a universal world order; he wants to accept disasters as persecutions and punishments: this allows him to console himself through submission or rebellion."

Herzen: the future is a variation improvised on the theme of the past.

Humans, as all living beings (cf. Biosemiotics) have inherent biases.

For example, apophenia, or patternicity, is a term/condition that refers to a tendency in humans where they see patterns where patterns do not exist.

Definitions

Bias is a tendency to prefer or favour one response over others.

In both human and nonhuman contexts, many biases are evolved traits or strategies that have been adaptive in particular environments. They help organisms—including humans—make efficient decisions, prioritise information, and respond to recurring challenges. For example, behavioural biases like predator avoidance or foraging preferences increase survival, while perceptual biases attune organisms to the most relevant cues in their environment.

However, biases can become less useful or even maladaptive when circumstances change, or when they are applied outside the context in which they evolved. In modern human societies, some cognitive and social biases may lead to systematic errors, discrimination, or misjudgement. Similarly, in nonhuman communities, specialisation or stability biases may reduce resilience to rapid environmental change.

Cognitive biases

Anchoring bias: the tendency to rely too heavily on the first piece of information encountered (the "anchor") when making decisions.
Availability heuristic: overestimating the importance of information that is most readily available.
Cognitive dissonance bias: the tendency to rationalise contradictory information to maintain internal consistency.
Confirmation bias: the tendency to search for, interpret, and remember information in a way that confirms one's preconceptions or existing beliefs.
Hindsight bias: the inclination to see events as having been predictable after they have already occurred.
Recency bias: the tendency to weigh recent events more heavily than earlier events.

Age bias: favouring perspectives or outcomes associated with particular age groups.
Cultural bias: interpreting and judging phenomena by standards inherent to one's own culture or privileging particular cultural perspectives or values.
Economic bias: favouring perspectives or outcomes associated with particular economic statuses.
Educational bias: favouring perspectives or outcomes associated with particular levels of education.
Gender bias: favouring perspectives or outcomes associated with particular genders.
Group attribution bias: the tendency to generalise about a group based on the behaviour of a few individuals within that group.
Halo effect: the tendency to let an overall impression of a person influence specific judgments about them.
Historical bias: promoting specific historical narratives or interpretations.
Ingroup bias: favouring members of one's own group over those in other groups.
Negativity bias: the tendency to give more weight to negative experiences or information than positive ones.
Self-serving bias: the tendency to attribute positive events to one's own disposition but attribute negative events to external factors.
Stereotyping: generalising about a group of people in which identical characteristics are assigned to virtually all members of the group.
Status quo bias: the preference for the current state of affairs and resistance to change.

Procedural and observational biases

Measurement bias: bias that arises from errors in data collection, leading to inaccurate or misleading data.
Methodological bias: preferring specific research methods or approaches.
Novelty (or innovation) bias: favouring new or innovative ideas over established ones (cf. hype bias or trend bias).
Observer bias: when a researcher's expectations influence their interpretation of outcomes.
Omission bias: the tendency to judge harmful actions as worse, or less moral, than equally harmful omissions.
Publication bias: the tendency for positive or significant results to be published more frequently than negative or inconclusive results.
Reporting bias: bias that occurs when certain outcomes or results are more likely to be reported than others.
Risk bias: prioritising research that addresses perceived risks or threats.
Sampling bias: a form of selection bias where the sample is not representative due to the method of selection.
Selective reporting bias: the tendency to report only certain results or outcomes—typically those that are positive, statistically significant, or align with expectations—while omitting others, which can distort the scientific record.
Survivorship bias: concentrating on the people or things that "survived" some process and overlooking those that did not due to their lack of visibility.
Exaggeration bias: overstating the importance, magnitude, or certainty of findings, often in abstracts, press releases, or media coverage, which can mislead about the true implications or reliability of research results.

Systemic and algorithmic biases

Algorithmic bias: when algorithms produce systematically prejudiced results due to erroneous assumptions in the machine learning process.
Automation bias: the tendency to favour suggestions from automated decision-making systems and to ignore contradictory information made without automation.
Confirmation bias in AI: when AI systems are designed or trained in a way that confirms the developers' preconceptions.
Data bias: bias that occurs when the data used to train a model is not representative of the real-world scenario it is meant to reflect.
Disciplinary bias: giving precedence to certain scientific disciplines or fields of study.
Funding bias: promoting research that aligns with the interests of funding sources.
Institutional bias: prioritising research from specific institutions or organisations.
Interaction bias: bias that occurs when users interact with a system in a way that reinforces existing biases.
Language bias: privileging studies published in particular languages.
Selection bias: bias introduced by the non-random selection of data, leading to a sample that is not representative of the population.
Surveillance bias: increased monitoring leads to increased detection of outcomes, not necessarily increased incidence.

Aesthetic bias: Favouring species that are visually appealing while neglecting or undervaluing those considered unattractive, repulsive, or "ugly".
Anthropocentrism: Viewing humans as the central or most significant entities.
Anthropomorphism: Attributing human characteristics, emotions, or intentions to nonhuman entities, which can distort understanding of their characteristics. Conversely, fear of anthropomorphism can lead to reluctance in recognising similarities between humans and nonhuman beings.
Biomism: Prejudice, discrimination, or antagonism against a particular biome.
Charismatic species bias: Focusing on aesthetically appealing or "charismatic" species.
Citation bias: Preferentially citing already prominent studies, or studies from certain disciplines, languages, regions, or authors.
Disgust bias: Allowing feelings of disgust or repulsion (e.g., toward invertebrates, reptiles, or scavengers) to influence conservation priorities or research attention.
Domestication bias: Favouring domesticated species over wild species in research, conservation, or ethical considerations.
Ecological bias: Undervaluing the roles of less visible or less understood organisms.
Evolutionary bias: Favouring species that are evolutionarily closer to humans.
Extinction bias: Focusing on species that are already extinct or critically endangered, while neglecting those that are declining but not yet at critical levels.
Functional bias: Prioritising species or organisms based on their perceived utility or ecosystem services, while undervaluing those with less obvious roles.
Geographic bias: Favouring certain regions (e.g., developed over remote areas).
Habitat bias: Focusing on certain habitats (e.g., forests) while neglecting others (e.g., wetlands, deserts).
Invasive species bias: Automatically categorising non-native or invasive species as harmful, sometimes overlooking their ecological roles or potential benefits.
Keystone species bias: Overemphasising the importance of keystone species while undervaluing the roles of other species in ecosystems.
Land over ocean bias: Prioritising terrestrial ecosystems over marine ones.
Microbial bias: Overlooking the importance of microorganisms in ecosystems and evolutionary processes.
Mineral or resource bias: Prioritising human use of non-living resources over their intrinsic or ecological value.
Model bias: Favouring certain models or frameworks for understanding ecological systems (e.g., over-reliance on model organisms, which may not be representative).
Neophobia bias: Exhibiting aversion or negative attitudes toward unfamiliar or novel species, which can include both invasive and native organisms.
Novel ecosystem bias: Prioritising pristine or "natural" ecosystems over novel or human-altered ecosystems, despite their ecological significance.
Parochial bias: Focusing on local or regional ecosystems while neglecting global ecological interconnections.
Pest bias: Devaluing or targeting species labelled as pests, often ignoring their ecological functions.
Plant blindness: Overlooking the importance of plants in ecosystems.
Size bias: Favouring larger species over smaller ones.
Speciesism: Prioritising human interests over those of other species.
Taxonomic bias: Focusing on specific taxonomic groups (e.g., vertebrates over invertebrates).
Temperate over tropical bias: Prioritising temperate ecosystems over tropical ones.
Temporal bias: Prioritising short-term ecological changes over long-term evolutionary or ecological processes.
Trophic bias: Focusing on higher trophic levels (e.g., predators) while neglecting lower levels (e.g., decomposers, primary producers).

Biases that Affect All Biological Agents and Communities

Adaptability bias: Favouring flexible, generalist strategies that allow survival in a wide range of conditions, sometimes at the cost of efficiency or specialisation.
Behavioural bias: Innate or learned behaviours favour certain responses over others, based on what has been adaptive in the past (e.g., predator avoidance, foraging preferences).
Communication bias: Nonhuman communication systems (e.g., pheromones, bird song, root signalling) privilege certain types of information and may exclude others, shaping collective knowledge within a species or ecosystem.
Ecological bias: Systematic tendencies in perception, behaviour, or knowledge shaped by an organism’s ecological niche and evolutionary history, which constrain what it can know or respond to in its environment.
Evolutionary bias: Systematic tendencies shaped by evolutionary history, such as favouring traits that were adaptive in ancestral environments, which may not be optimal in current or changing conditions.
Generality bias: Evolving generalist traits or behaviours that allow use of diverse resources or habitats, sometimes at the cost of peak performance in any one context.
Innovation bias: Tendency in some species or systems to favour novel behaviours, strategies, or mutations, which can drive rapid adaptation but may also increase risk.
Opportunistic bias: Preference for immediate, short-term gains or resources, sometimes at the expense of long-term stability or sustainability (e.g., boom-and-bust population cycles).
Perceptual bias: Species-specific sensory modalities (e.g., ultraviolet vision in bees, echolocation in bats) shape what information is salient or accessible to an organism.
Social bias: In social species, group structure and hierarchies influence what information is shared, prioritised, or ignored (e.g., dominance hierarchies in primates or ants).
Specialisation bias: Evolving highly specialised traits or behaviours that optimise performance in a narrow niche, potentially increasing vulnerability to environmental shifts.
Stability bias: Favouring conservative, specialist strategies that maintain stability and efficiency in a consistent environment, but may reduce resilience to change.
Tameness bias: In domesticated or human-influenced environments, selection for tameness or reduced aggression, which can alter social structures, behaviour, and even cognition.
Temporal bias: Some organisms or systems are attuned to short-term cycles (e.g., circadian rhythms), while others are shaped by long-term processes (e.g., tree growth, geological change).
Wildness bias: In wild populations, selection for traits that favour independence, aggression, or avoidance of humans and novel situations.

Relevant Theories

Niche Construction Theory

Explores how organisms shape their own and each other’s selective environments, leading to systematic tendencies (biases) in evolution and ecology.

Cf. Niche

Sensory Ecology, Umwelt, Biosemiotics, Ecosemiotics

The concept of umwelt describes how each organism experiences the world through its own sensory and perceptual biases, shaped by evolutionary history.

Biosemiotics theorises that all living systems interpret and respond to signs in their environment, leading to species- and context-specific biases in meaning-making and action.

Cf. Biosemiotics. Sensory Ecology

Collective Behaviour

Studies of animal societies (e.g., ants, bees, birds, fish) show how group structure, communication, and social learning create collective biases in decision-making and information flow.

Evolutionary Constraints and Trade-offs

Evolutionary biology theorises that all organisms are subject to constraints and trade-offs (e.g., between specialisation and generality, adaptability and stability), which manifest as systematic biases in behaviour, physiology, and ecological roles.

References

Cundiff, Jessica L. 2023. “Understanding and Interrupting Bias.” BioScience 73 (11): 781–84. https://doi.org/10/g9pkc9.

Korteling, J. E. (Hans), Geke C. van de Boer-Visschedijk, Romy a. M. Blankendaal, Rudy C. Boonekamp, and Aletta R. Eikelboom. “Human- Versus Artificial Intelligence.” Frontiers in Artificial Intelligence 4 (2021): 622364. https://doi.org/10/gjrvcx.

Silveira, Fernando A. O. 2025. “Seven Ways to Prevent Biomism.” Ambio. https://doi.org/10/g9kdj3.

Christie, Alec P., Tatsuya Amano, Philip A. Martin, Silviu O. Petrovan, Gorm E. Shackelford, Benno I. Simmons, Rebecca K. Smith, David R. Williams, Claire F. R. Wordley, and William J. Sutherland. 2021. “The Challenge of Biased Evidence in Conservation.” Conservation Biology 35 (1): 249–62. https://doi.org/10/ghvkgc.

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