Not Exactly Vagueness as Original Sin Kees van

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Not Exactly Vagueness as Original Sin? Kees van Deemter University of Aberdeen EMBL Forum,

Not Exactly Vagueness as Original Sin? Kees van Deemter University of Aberdeen EMBL Forum, Dec 2010

Plan of the talk 1. Vagueness is hard to avoid 2. We are often

Plan of the talk 1. Vagueness is hard to avoid 2. We are often vague for good reasons 3. Vagueness is a problem 4. How to model vagueness formally? EMBL Forum, Dec 2010

1. Vagueness is hard to avoid Vague words have borderline cases An Aberdeen afternoon

1. Vagueness is hard to avoid Vague words have borderline cases An Aberdeen afternoon in December -2 C cold 12 C not cold 5 C ¿cold? EMBL Forum, Dec 2010

n Vague adjectives: warm, cold, large, . . . n Vague nouns: girl, giant,

n Vague adjectives: warm, cold, large, . . . n Vague nouns: girl, giant, island, . . . and so on … Most words in English or German are vague Vagueness is prevalent in science too Example: species terms EMBL Forum, Dec 2010

What makes a species? n Long thought unproblematic (e. g. Linnaeus 1750) n The

What makes a species? n Long thought unproblematic (e. g. Linnaeus 1750) n The interbreeding criterion (Mayr, Dobzhansky, 1940) x is same species as y x interbreeds with y EMBL Forum, Dec 2010

Ensatina (Stebbins 1949, Dawkins 2004) EMBL Forum, Dec 2010

Ensatina (Stebbins 1949, Dawkins 2004) EMBL Forum, Dec 2010

Ensatina’s habitat and interbreeding x p eschscholtzii o CENTRAL VALLEY klauberi c Called a

Ensatina’s habitat and interbreeding x p eschscholtzii o CENTRAL VALLEY klauberi c Called a ring species. Logically: eschscholtzii i x i p i o EMBL Forum, Dec 2010 i c i klauberi

escholtzii i x i p i o i c i klauberi For example, not

escholtzii i x i p i o i c i klauberi For example, not i(eschscholtzii, klauberi) n interbreeding {esch, x} n “same predicts overlapping species: {x, p} {p, o} {o, c} {c, klau} species” is not transitive: same(esch, x) n same(x, p), n not same(esch, p) n EMBL Forum, Dec 2010

Our own ancestry n you stand in relation I to your parents, grandparents, .

Our own ancestry n you stand in relation I to your parents, grandparents, . . . n Let a = the first ancestor such that not i(a, you) n Do you and a belong to same species? EMBL Forum, Dec 2010

Are you and a the same species? n Formal Response: “No; the interbreeding criterion

Are you and a the same species? n Formal Response: “No; the interbreeding criterion should be used” Many overlapping species EMBL Forum, Dec 2010 s. . s 6 s 5 s 4 s 3 s 2 s 1 time

Are you and a the same species? n Formal Response: “No; the interbreeding criterion

Are you and a the same species? n Formal Response: “No; the interbreeding criterion should be used” Many overlapping species n Standard Response: “Yes; species should be defined via the transitive closure of i” EMBL Forum, Dec 2010

Are you and a the same species? n Formal Response: “No; the interbreeding criterion

Are you and a the same species? n Formal Response: “No; the interbreeding criterion should be used” Many overlapping species n Standard Response: “Yes; species should be defined via the transitive closure of i” All living beings are one species EMBL Forum, Dec 2010

Interim conclusion Key concepts of science resist precise definition EMBL Forum, Dec 2010

Interim conclusion Key concepts of science resist precise definition EMBL Forum, Dec 2010

Dawkins on species terms “Let us use names as if they really reflected a

Dawkins on species terms “Let us use names as if they really reflected a discontinuous reality, but let's privately remember that (. . . ) it is no more than a convenient fiction, a pandering to our own limitations”. “Tyranny of the discontinuous mind”. (Dawkins 2004, “The Ancestor’s Tale”) EMBL Forum, Dec 2010

Why is the fiction of species convenient? n Links between species have gone extinct

Why is the fiction of species convenient? n Links between species have gone extinct n When xan and oreg are extinct: esch i xan i pi i oreg i cro i klau Result: three separate species: {esch}, {pi}, {cro, klau} EMBL Forum, Dec 2010

Vagueness as original sin? (with thanks to Tintoretto) EMBL Forum, Dec 2010

Vagueness as original sin? (with thanks to Tintoretto) EMBL Forum, Dec 2010

2. We are often vague for good reasons Why are we often more vague

2. We are often vague for good reasons Why are we often more vague than we need to be? (Game theorists, e. g. , B. Lipman 2000, 2006) Can vagueness be used strategically? Some tentative answers. . EMBL Forum, Dec 2010

A practical perspective: computers speaking vaguely Input: numbers or formulas (15 C, …) Output:

A practical perspective: computers speaking vaguely Input: numbers or formulas (15 C, …) Output: “Mild, … A nice Spring day’’ Input: Time-series data on babies in IC Output: “Slight fever, … Usually, …’’ What’s best understood? Remembered? Acted on? (Peters et al. 2009, Zikmund-Fisher et al 2007) EMBL Forum, Dec 2010

From the BABYTALK corpus “BREATHING – Today he managed 1½ hours off CPAP in

From the BABYTALK corpus “BREATHING – Today he managed 1½ hours off CPAP in about 0. 3 litres nasal prong oxygen, and was put back onto CPAP after a desaturation with bradycardia. However, over the day his oxygen requirements generally have come down from 30% to 25%. Oxygen saturation is very variable. Usually the desaturations are down to the 60 s or 70 s; some are accompanied by bradycardia and mostly they resolve spontaneously, though a few times his saturation has dipped to the 50 s with bradycardia and gentle stimulation was given. He has needed oral suction 3 or 4 times today, oral secretions are thick. ” [BT-Nurse scenario 1] van Deemter, Riga, Jan. 2010

First (tentative) answer to Lipman Vague expressions are easy to produce & digest They

First (tentative) answer to Lipman Vague expressions are easy to produce & digest They allow us to omit irrelevant info n They tend to be brief and efficient n They add interpretation to the facts n EMBL Forum, Dec 2010

We’re not the first to see this … Edwardian “banjo” barometer very dry much

We’re not the first to see this … Edwardian “banjo” barometer very dry much rain EMBL Forum, Dec 2010

Second answer 11 m 12 m EMBL Forum, Dec 2010

Second answer 11 m 12 m EMBL Forum, Dec 2010

Height of house 1 =11 m Height of house 2 =12 m - “the

Height of house 1 =11 m Height of house 2 =12 m - “the 12 m house needs to be demolished” - “the tall house needs to be demolished” Comparison is easier than measurement Therefore, we might prefer “the tall house” EMBL Forum, Dec 2010

Third answer n A politician promising “low unemployment”, or “stable government” n Game-theory models

Third answer n A politician promising “low unemployment”, or “stable government” n Game-theory models predict benefits from vague promises (Aragones & Neeman 2000) Unforeseen contingencies could make concrete promises difficult to honour n Disappointed voters could hold politician to account n EMBL Forum, Dec 2010

3. Vagueness is a problem Sorites puzzle (Eubulides, 450 BC) One of the top

3. Vagueness is a problem Sorites puzzle (Eubulides, 450 BC) One of the top ten unsolved problems of science (“The list universe”, 2007 AD) 0 hairs is bold n (x hairs is bold) (x+1 hairs is bold) n therefore, 106 hairs is bold n Yet 106 hairs is not bold n EMBL Forum, Dec 2010

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Sorites enhanced by science Eubulides in the audio lab Decibel (d. B): measures the

Sorites enhanced by science Eubulides in the audio lab Decibel (d. B): measures the loudness of sounds n -30 d. B is inaudible n 100 d. B is very loud n differences of 0. 5 d. B cannot be discerned EMBL Forum, Dec 2010

Eubulides in the audio lab -30 d. B is inaudible -30 d. B is

Eubulides in the audio lab -30 d. B is inaudible -30 d. B is indistinguishable from -29. 5 d. B, so -29. 5 d. B is inaudible EMBL Forum, Dec 2010

Eubulides in the audio lab -29. 5 d. B is inaudible -29. 5 d.

Eubulides in the audio lab -29. 5 d. B is inaudible -29. 5 d. B is indistinguishable from -29 d. B, so -29 d. B is inaudible EMBL Forum, Dec 2010

Eubulides in the audio lab . . . 99. 5 d. B is inaudible

Eubulides in the audio lab . . . 99. 5 d. B is inaudible 99. 5 d. B is indistinguishable from 100 d. B, so 100 d. B is inaudible !! EMBL Forum, Dec 2010

The new sorites argument as a whole -30 d. B is inaudible -30 d.

The new sorites argument as a whole -30 d. B is inaudible -30 d. B is indistinguishable from -29. 5 d. B, so -29. 5 d. B is inaudible -29. 5 d. B is indistinguishable from -29 d. B, so -29 d. B is inaudible. . . 99. 5 d. B is inaudible 99. 5 d. B is indistinguishable from 100 d. B, so 100 d. B is inaudible !! EMBL Forum, Dec 2010

A further complication: we’re all different Colour terms like “red” (Hilbert 1987) n People

A further complication: we’re all different Colour terms like “red” (Hilbert 1987) n People cannot distinguish the same colours pigment on lens and retina; sensitivity of photo receptors Time words like “evening” (Reiter et al. 2005) n Is dinner time relevant? n The time of year? EMBL Forum, Dec 2010

n For analysing the meaning of language, mathematical logic is the tool of choice

n For analysing the meaning of language, mathematical logic is the tool of choice n Classical logic is built on crisp dichotomies n George Boole (1815 -1864) gave the first algebraic account n A statement is either true or false (1 or 0) n Nice and simple: Boole’s paradise EMBL Forum, Dec 2010

“audible” in classical logic audible x d. B inaudib le EMBL Forum, Dec 2010

“audible” in classical logic audible x d. B inaudib le EMBL Forum, Dec 2010

“audible” in classical logic audible x+ Indistinguishable x d. B x- inaudib le EMBL

“audible” in classical logic audible x+ Indistinguishable x d. B x- inaudib le EMBL Forum, Dec 2010

Semi-classical logics use dichotomies too Context-aware logics (Kamp 1981) use Just-Noticeable Difference E. g.

Semi-classical logics use dichotomies too Context-aware logics (Kamp 1981) use Just-Noticeable Difference E. g. , loudness: JND 1 d. B n JNDs mistakenly modelled as crisp n Crispness contradicted by empirical evidence n Subtler models are needed EMBL Forum, Dec 2010

We have seen: 1. Vagueness is everywhere 2. We are vague for a reason

We have seen: 1. Vagueness is everywhere 2. We are vague for a reason 3. Vagueness is a problem EMBL Forum, Dec 2010

4. How to model vagueness? EMBL Forum, Dec 2010

4. How to model vagueness? EMBL Forum, Dec 2010

Some like it crisp n Blastland & Dilnot (2008): false clarity n Substances that

Some like it crisp n Blastland & Dilnot (2008): false clarity n Substances that are “poisonous” n Genes that “cause” a condition n Dawkins (2004): tyranny of the discontinuous mind EMBL Forum, Dec 2010

C. P. Snow’s Rede Lecture (1959) The Two Cultures C. P. Snow talked about

C. P. Snow’s Rede Lecture (1959) The Two Cultures C. P. Snow talked about the gulf separating n n Scientists & engineers Scholars in the humanities They do not know each other and do not speak with each other SELLC banquet, Guangzhou, Dec 2010

Two approaches to continuous data n Engineers & psychophysicists: approximations, real numbers, Gaussian distributions,

Two approaches to continuous data n Engineers & psychophysicists: approximations, real numbers, Gaussian distributions, n Philosophers, linguists, and most logicians: crisp dichotomies (true/false, 1/0). They inhabit Boole’s Paradise! EMBL Forum, Dec 2010

“Continuous” logics Date back to J. Łukasiewicz 1920 and M. Black 1937 Map statements

“Continuous” logics Date back to J. Łukasiewicz 1920 and M. Black 1937 Map statements to numbers between 0 and 1 EMBL Forum, Dec 2010

Fuzzy logic (L. Zadeh 1975) [φ] = degree of truth of φ [1000 hairs

Fuzzy logic (L. Zadeh 1975) [φ] = degree of truth of φ [1000 hairs is bald] < [100 hairs bald] Negation: [not φ] = 1 - [φ] Disjunction: [φ or ] = max([φ], [ ]) Conjunction: [φ & ] = min([φ], [ ]) EMBL Forum, Dec 2010

sorites paradox in Fuzzy Logic As x increases, Bald(x) becomes less true: [Bald(0)] =

sorites paradox in Fuzzy Logic As x increases, Bald(x) becomes less true: [Bald(0)] = [Bald(103)] [Bald(106)] 1 0. 5 0 Each premiss Bald(x) Bald(x+1) is almost true EMBL Forum, Dec 2010

Problems for Fuzzy Logic n Is 1000 hairs bald or somewhat bald? [Bald(1000)] =

Problems for Fuzzy Logic n Is 1000 hairs bald or somewhat bald? [Bald(1000)] = 0. 5 [Sw. Bald(1000)] = 0. 5 n Consider Bald(1000) or Sw. Bald(1000) Fuzzy Logic assigns a strangely low value: EMBL Forum, Dec 2010

Problems for Fuzzy Logic n Is 1000 hairs bald or somewhat bald? [Bald(1000)] =

Problems for Fuzzy Logic n Is 1000 hairs bald or somewhat bald? [Bald(1000)] = 0. 5 [Sw. Bald(1000)] = 0. 5 n Consider Bald(1000) or Sw. Bald(1000) Fuzzy Logic assigns a strangely low value: [Bald(1000) or Sw. Bald(1000)] = max(0. 5, 0. 5) = 0. 5 EMBL Forum, Dec 2010

A better way (e. g. , Edgington 1992, 1996) [ ] = probability of

A better way (e. g. , Edgington 1992, 1996) [ ] = probability of someone agreeing with [ or ] = [ ] + [ ] - [ & ] [Bald(1000) or Sw. Bald(1000)] = 0. 5 + 0. 5 - 0 = 1 EMBL Forum, Dec 2010

Boole’s 2 -valued paradise was such an attractive place EMBL Forum, Dec 2010

Boole’s 2 -valued paradise was such an attractive place EMBL Forum, Dec 2010

When vagueness is taken seriously. . . n Truthfulness becomes problematic n “We didn’t

When vagueness is taken seriously. . . n Truthfulness becomes problematic n “We didn’t know that smoking causes cancer” Not exactly true n Falsification & Belief Revision n “Are all ravens black? What about this grey-black one? ” Not exactly black EMBL Forum, Dec 2010

n Questions for linguists, logicians, philosophers, psycho-physicists, computer scientists, biologists n A clear need

n Questions for linguists, logicians, philosophers, psycho-physicists, computer scientists, biologists n A clear need for collaboration between academic disciplines EMBL Forum, Dec 2010

The End www. csd. abdn. ac. uk/~kvdeemte/Not. Exactly With thanks to Judith Masthoff (for

The End www. csd. abdn. ac. uk/~kvdeemte/Not. Exactly With thanks to Judith Masthoff (for Homer Simpson’s coiffure) EMBL Forum, Dec 2010

“Not Exactly: in Praise of Vagueness” Oxford University Press, Jan. 2010 Part 1: Vagueness

“Not Exactly: in Praise of Vagueness” Oxford University Press, Jan. 2010 Part 1: Vagueness in science and daily life Part 2: Theories of vagueness Part 3: Vagueness in Artificial Intelligence EMBL Forum, Dec 2010

EMBL Forum, Dec 2010

EMBL Forum, Dec 2010