philosophy
Contents
Notes on philosophy relevant to explanation (particularly in science)
6.7. philosophy#
6.7.1. 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
in some cases, such as simple physics, we can hope to get a theory - however, when the underlying process is complicated, interpretation canât hope to simplify it
in other cases, we might hope just for a description
6.7.2. 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 âmerely descriptiveâ
these theories focus only on explanations of why things happen
concepts: explanation, description, causation
6.7.2.1. 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 \(PV=nRT\)
6.7.2.2. 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 = âlawfulâ
explanans must contain a âlaw of natureâ
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 donât get pregnant)
feels like their is something missing about âcausalityâ, 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
6.7.2.3. 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 \(P(BâŁA,C) \neq P(BâŁA)\)
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
6.7.2.4. 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
6.7.2.5. 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
doesnât easily admit laws at different graunlarities
6.7.2.6. pragmatic = contextual explanation models#
scriven (1962), bromberger (1966), van Fraassen (1980), achinstein (1983)
takes audience into account
others have been after characterizing a single âtrueâ explanation and the role of the audience was minimized
âpragmaticâ here means not just useful but also explicitly considering psychology + context
âCausalâexplanatory pluralismâ (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 âempirically adequateâ
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 âŚâa t three-term relation between theory, fact, and contextâ
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 donât need to analyze human psych
somewhat circular - if this is true, then how can we resolve ambiguities?
6.7.2.7. 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)
6.7.3. the beggining of infinity (david deutsch, 2011)#
all progress has resulted from the quest for good explanations
good explanation - hard to vary while still acocounting for what it purports to account for
the reach of an explanation is something we find out only after the fact (though we strive for explanations with good reach)
seek âan idea so simpleâŚthatâŚwe sill all say to each other, how could it have been otherwiseâ?
tenets
problems are inevitable
problems are soluble
optimisim = the proposition that all evils are due to a lack of knowledge, and that knowledge is attainable by the methods of reason and science
e.g. the distence between a ânaturalâ disaster andone brought about by ignorance is parochial (e.g. famine)
theories
empiricism - we âderiveâ all our knowledge from sensory experience (deutsch argues that evidence is not used to generate theories but rather to choose between theories that have already been guessed)
inductivisim - idea that theories are obtained by generalizing repeated experiences
instrumentalism - science cannot describe reality, only predict outcomes of observations
evolution
evolution (darwinian) - creation of knowledge through alternating variation & selection
lamarckism - mistaken evolutionary theory that adaptations are acquired by organisms during their lifetime then passed down
fine-tuning - if the constants or laws of physics were slightly different, there would be no life
meme - explanations must spread both by being replicated and enacted in the brains of others
a substantial proportion of all evolution on our planet to date has occured in human brains
only 2 basic strategies of meme replication
help holders (rational)
distable holderâs critical faculties (anti-rational)
creativity developed as a way to better emulate ordinary things for mate selection, but proved to have much greater reach
morality
moral philosophy addresses the problem of what sort of life to want
reductionism - misocnception that mus always explain things by analyzing them into components
âyou canât derive an ought from an isâ (paraphrase from David Hume)
politics
just as science seeks explanations that are experimentally testable, a rational political system makes it as easy as possible to detect + persuade others that a leader or policy is bad, and to remove them without violence if they are (popperâs criterion)
the moral imperative not to destroy the means of correcting mistakes could be the only moral imperative
arguments against the problem of apportioning representatives â argues instead for plularity voting system
a culture is a set of ideas that cause their holders to behave alike in some ways
aesthetics
when a piece of music has the attribute âdisplace one note and there would be diminishmentâ, there is an explanation (one day it may be expressible in words)
jump to universality - gradually improving systems undergo a sudden large increase in functionality
e.g. numbering systems failed a couple times before becoming universal
e.g. genetic code
many theories for sustaining may be too limiting (e.g. propose studying carbon capture rather than limiting carbon production)
minor
people in 1900 did not consider the internet or nuclear power unlikely: they did not conceive of them at all
the original sources of scientific theories are almost nevery good - weird that philiosophy places such an emphasis on original texts
most people believe that an income of about twice their own should be sufficient to satisfy any reasonable person (hard to imagine what it would be like to have twice as much) - David Friedman
6.7.4. philosophy of science#
6.7.4.1. thomas kuhn#
science enjoys periods of stable growth punctuated by revisionary revolutions
the development of science is driven, in normal periods of science, by adherence to what Kuhn called a âparadigmâ
The functions of a paradigm are to supply puzzles for scientists to solve and to provide the tools for their solution
A crisis in science arises when confidence is lost in the ability of the paradigm to solve particularly worrying puzzles called âanomaliesâ
scientific revolutions involve a revision to existing scientific belief or practice
âincommensurability thesisâ - theories from differing periods suffer from certain deep kinds of failure of comparability
controversial - goes against the idea that science constantly builds
6.7.5. 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, platoâs 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 oneâs 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
âI think therefore I amâ
bacon embraces epicureanism - donât want anything
scors knowledge that doesnât 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 beliefsâŚinterestingly 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
âHave strongly-held values, and malleable opinionsâ. - 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 â 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 âthe supermanâ
bertrand russel
starts with symbolic reasoning
after WWI, shifts tow grounded philosophy in pacifism, communism
6.7.6. stability#
Foundationalism - where the chain of justifications eventually relies on basic beliefs or axioms that are left unproven
Platoâs 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)
4 major aspects: causation-association, theory-data, retrospective-prospective, bias-variance
(causal) explanation is often more about picking the right class of models (which minimizes bias) rather than fitting their parameters