Notes on philosophy relevant to explanation (particularly in science)

6.6. philosophy

6.6.1. basics

  • try to understand what principles underly all phenomena

  • Machine Learning and the Future of Realism (hooker & hooker, 2017)

    • lack of interpretability in DNNs is part of what makes them powerful

    • naked predictions - numbers with no real interpretation

      • more central to science than modelling?

      • no theory needed? (Breiman 2001)

    • old school: realist studied neuroscience (Wundt), anti-realist just stimuli/response patterns (Skinner), now neither

    • interpretability properties

      • simplicity - too complex

      • risk - too complex

      • efficiency - basically generalizability

      • unification - answers ontology - the nature of being

      • realism in a partially accessible world

    • overall, they believe there is inherent value of ontological description

  • Explainable Artificial Intelligence and Machine Learning: A reality rooted perspective (Emmert-Streib et al. 2020)

    • explainable AI is not a new field but has been already recognized and discussed for expert systems in the 1980s

    1. in some cases, such as simple physics, we can hope to get a theory - however, when the underlying process is complicated, interpretation can’t hope to simplify it

    2. in other cases, we might hope just for a description

6.6.2. scientific explanation (SEP)

  • distinction between scientific explanation and non-scientific explanation (although can put things on a spectrum)

  • distinction between explanations and accounts which are “merely descriptive”

  • these theories focus only on explanations of why things happen

  • concepts: explanation, description, causation

6.6.2.1. some overarching examples - what causes what?

  • do birth pills stop pregnancy (both for men/women)?

  • sun, flagpole, shadow

  • barometer, air pressure, storm

  • collision of pool balls

  • supply/demand curves in economics

  • gas law \(PV=nRT\)

6.6.2.2. DN model = Deductive-Nomological Model

  • by Popper, Hempel, Oppenheim (popper 1935, hempel 1942)

  • explanation has 2 constituents

    • explanandum - sentence describing phemonenon to be explained

    • explanans - class of sentences used to account for the phenomenon

  • deductive

    • explanans must be true

    • explanandum must be a logical consequence of the explanans

  • nomological = “lawful”

    • explanans must contain a “law of nature”

    • the law of nature must be essential to deriving the explanans

  • still hard to decide exactly what is a law - should be exceptionless generalizations describing regularities

    • can have probabilistic laws as well (e.g. prob of recovering after taking penicillin is high)

  • why this framework

    • by framing terms of laws and cricumstances, the explanation shows that the phenomenon was to be expected and helps us understand why it occured

    • sometimes, an explanation-sketch uses words like cause, that can be reframed more precisely in the DN model

  • counterexamples

    • assymetry (e.g. shadow length, flagpole height, sun angle) - derive shadow length seems explanatory, but not deriving flapole height

    • irrelevant details (e.g. being a man + taking birth control pills explains why you don’t get pregnant)

    • feels like their is something missing about “causality”, but this is difficult to pin down - suggests DN model states necessary but not sufficient conditions

    • features of an explanation must be recognized / used by users of an explanation

6.6.2.3. statistical relevance - wesley salmon

  • starts with (salmon, 1971)

  • given some class or population A, an attribute C will be statistically relevant to another attribute B iff \(P(B∣A,C) \neq P(B∣A)\)

    • find a set of attributes which divide the target into a homogenous partition = even if we split the cells further, they keep the same probability

      • like in causal inference, assume no missing variables

    • then, the explanation for a new target x gives the cells, the prob. for each of the cells, and which cell x belongs to

  • this method is almost information-theoretic - same explanans equally explains the same model with inverted probabilies

  • ex. (Salmon, 1971) atmospheric pressure, barometer, and storm - barometer is explanatory but not causal

6.6.2.4. causal mechanical models

  • starts with (salmon, 1984)

  • elements

    • causal process - leaves marks on the world which persist spatiotemporally (these marks hint at counterfactuals)

      • contrasts with a pseudoprocess, like a shadow

    • causal interaction - interaction of such processes, e.g. a car crash

  • explanation consists of 2 parts which both track causal process + interactions

    • etiological - leading up to event

    • constitutive parts - during event

  • issues: hard to distinguish between explanatory causes (e.g. for a pool ball collision, mass + velocity) vs other so-called causal processes (e.g. chalk mark on ball)

    • tends towards overly complex physical descriptions - e.g. for gas law track all particles rather than something global like pressure

6.6.2.5. unificationist models

  • important attempts include friedman (1974) and kitcher (1989)

  • seeks a unified account of a range of different phenomena

  • best explanations explains most phenomena with as few + as stringent arguments possible

  • potential issues

    • causal asymmetries - equally likely to say planets in future cause motion now then planets now cause motion in the future - this is honestly probably fine

    • doesn’t easily admit laws at different graunlarities

6.6.2.6. pragmatic = contextual explanation models

  • scriven (1962), bromberger (1966), van Fraassen (1980), achinstein (1983)

  • takes audience into account

  • others have been after characterizing a single “true” explanation and the role of the audience was minimized

  • “pragmatic” here means not just useful but also explicitly considering psychology + context

  • “Causal–explanatory pluralism” (lombrozo 2010 [PDF]) - subjects prefer explanations that appeal to relationships that are relatively stable (in the sense of continuing to hold across changing circumstances)

  • constructive empiricism (Bas van Fraasen)

    • just want theories that are “empirically adequate”

    • explanations are answers to questions - usually why? questions

      • explanations pick something from a set and tell why it is not any of the other things in the set (the set is given from context)

    • explanation is …”a t three-term relation between theory, fact, and context”

    • asymmetries coem of rom context

  • main criticism: this theory is too flexible, ironically it might be too flexible to be meaningfully (practically) useful

    • however, it is possible that this is the most flexible framework that is still accurate

    • want context to come in for as few steps as possible during an explanation - maybe we don’t need to analyze human psych

    • somewhat circular - if this is true, then how can we resolve ambiguities?

6.6.2.7. open areas

  • understand casuality

  • more focus on whethery expalanations capture our intuitive judgements and more on the issue of why the info they convey is valuable + relates to our goals

  • to what extent does a single model work across sciences (e.g. biologists claim to be interested in mechanisms whereas physicists in laws)

6.6.3. the story of philosophy

book by will durant

  • states his own view that philosophy should focus on ethics rather the epistemiology (i.e. how we know what we know)

    • every science begins as philosophy and ends as art

  • some definitions of philosophy

    • pursuit of fundamental laws

    • quest of unity

  • plato

    • socrates, plato’s teacher pursued stricter definitions and was put to death

    • plato writes the Republic - fictitional dialogue w/ socrates as the protagonist

      • argues that democracy failes because people are greedy

      • advocates for an absolute meritocracy with 3 classes

        • ruling class should live like communists, decent state salary, disallowed from excess

        • soldiers / auxiliaries

        • general population

      • requires equality of education

      • requires religion to placated the non-ruling majority

      • excess is regulated

      • justice = having and doing what is one’s own

        • each shall receive equivalent to what he produces + perform function for which he is best fit

      • juxtapositions

        • jesus: kindness to the weak

        • nietzsche: bravery of the strong

        • plato: effective harmony of the whole

    • only 3 things: truth, beauty, + justice

  • aristotle

    • starts systematic science, library science, and logic

    • advocates for uinversals as individuals (e.g. a man, not man like Plat argues for)

      • this is more grounded in reality

    • theology: God moves the work like force, but does little else

    • science: infinitesimal distinctions - boundaries between plant/animal categories are blurry

      • form: man, matter: child = possibility of form

    • politics: ideally a monarchy / aristocracy but more realistically would be constitutional gov. (people determine needs, leaders determine how to meet them)

      • restrictions on pop.

      • believes in slavery / female inferiority

  • francis bacon

    • lived in 1500s/1600s in England

    • father of the scientific method

      • objective and realistic

      • in contrast to descartes = subjctive/idealistic

        • “I think therefore I am”

    • bacon embraces epicureanism - don’t want anything

    • scors knowledge that doesn’t lead to action

    • science = organization of knowledge

    • philosophy = organization of science

    • doubt all assumptions

  • spinoza

    • baroch de espinoza

    • jew who was excommunicated for anti-religious writing

    • no distinction between body and mind

    • no free will - only desires that guide everything

      • beginnings of doubting rationalism

  • voltaire

    • frenchman who was exiled

    • seeks history of ideas, beginning with The Essay on Morals

    • Candide - short story, denouncing optimism for pragmatism

    • real philosophy begins with Philosophic dictionary

    • strongly against superstition

    • wrote simple, accessible pamphlets

    • in his later years, turns to focus on the pursuit of usefulness rather than truth

    • contrasts with younger Roussea, who wanted more action, instinct, social contract

  • kant: mind has prior beliefes

    • what makes a math law better than some other thing? kant says a priori beliefs…interestingly those beliefs were from evolution in the first place

    • mind is not blank slate: mind filters in what we perceive a priori in contrast to growing popular belief that everything comes from perception

    • understanding can never go beyond the limits of sensibility

      • certain things in science/religion etc. can never be known, just interpreted

      • time and space are not realities but just our interpretations

    • lots of connections to priors in modern AI research

    • morals come from an innate sense

    • somewhat pro-religion but not fully, still still faced persecution in Prussia

    • “Have strongly-held values, and malleable opinions”. - Francois Chollet tweet

  • schopenhauer

    • everything is will: continuing trend from espinoza + kant against rationalism

    • pessimist: even in Utopia, ennui sets in

    • objects of science is universal that contains many particulars while object of art is particular than contains a universal – this requires more genius

  • herbert spencer

    • evolution as a guiding philosophy of everything

    • darwin published Origin of Species in 1859, when spencer was 40

      • spencer is thus more lamarckian

    • greatest contributions were to sociology: carefully curates data for sociology analysis

    • resulting philosophy is conservative, laissez-fare, anti-regulation

  • friedrich nietzsche

    • evolution as morality: favors the strong

    • germans have 2 words for good / bad - one is closer to strong, the other to kind

    • everything is due to an underlying will for power

    • evolution towards “the superman”

  • bertrand russel

    • starts with symbolic reasoning

    • after WWI, shifts tow grounded philosophy in pacifism, communism

6.6.4. stability

  • Foundationalism - where the chain of justifications eventually relies on basic beliefs or axioms that are left unproven

    • Plato’s Republic

  • the stability of belief: how rational belief coheres with probability (leitgeb, 2017) - introduction

  • To Explain or to Predict? (Shmueli, 2010)

    • explanatory modeling as the use of statistical models for testing causal explanations

    • many philosophies view explanation and prediction as distinct (but not incompatible)