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Volume 1, Spring Issue, 1988

B O O K R E V I E W

N R T I F I C I L I N T E L L I G E N C E P P R O C HT O L E G L R E S O N I N G

By Anne vonde r Lieth Gardner.Cambridge, Massachuset ts: The MIT Press, 1987,pp. 193.R e v ie w e d b y E d w i n a L . R i s s l a n d

Anne Gardner is both a lawyer and a coruputer scientist. Sheobtained her J.D. from Stanford in 1958, ar:d her book is a revisionof her 1984 dissertation submitted to Stanford's Department ofComputer Science. She plays, in part, the role of pioneer; artifi-cial intelligence ( AI ) techniques have not yet been widely ap-plied to perform legal tasks. Therefore Gardner, and this review,first describe and define the field, then demonstrate a workingmodel in the domain of contract offer and acceptance.

I, THE FIELD: AI AND THE LAWA. A r t i f i c ia l In te l ligence

Malwin Minsky, in his preface to the collection S e m a n t i c I n -f o r m a t i o n P r o c e s s i n g , defined artificial intelligence as the:science of making machines do things that would require intel-ligence if done by [people]. u Better known successful applicationshave included playing chess, identifying bacterial strains, recog-nizing and manipulat ing structures built with childrens' blocksand formulating concepts in set theory.2 Typical programminglanguages include LISP and PROLOG, while typical specialtiesin AI research include case-based reasoning, expert (rule-based)systems, natural language processing, nonmonotonic reasoning,and learning from examples. Above all, the field is marked by itscurrent diversity, rapid growth, and apparent potential2

* AssociateProfessor of Computer and Information Science, Unive rsityof Massachusettsat Amherst; Le cturer on Law, Harvard LaW School. Professor Rissla nd will serve a s ProgramCha ir for the second Inte rna tional Conference of Artificial Intel ligenceand the Law, curren t-ly scheduled for late Spring, 1989 in London. Asecond, more technical version of thi s reviewwill appear in the Fall, 1988 issue ofA/Ma gazine.

I . S E M A N T I C I N F O R M A T I O N P R O C E S S I N G ( M . M i n s k y e d . 1 9 6 8) .2 . S e e g e n e r a l l y W a l t z , A r t i f i c i a l n t e l l i g e n c e C I . A M . , O c t . 1 9 8 2 . F o r a r e c e n t , r e a d a b l e

o v e r v i e w , s e e L i n d e n , P u t t i ~ g n o w l e d g e t o W o r k T I M E , M a r c h 2 8 , 1 9 8 8 .3 . O p t i m i s m i s f o u n d e d i n p a r t u p o n p a r a l le l d e v e l o p m e n t s i n h a ~ d w a r e a n d o p e r a t i n g

systems, such as Intel s 386 and MicmsoR s OS/2. See e.g. Gralla, C h i p s O f f t h e O l d B lo c k :A His tory PC WEEK, Jan. 19, 1988 at S/13 (noting the AI capabili tie sof new microcomputers).


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2 2 4 Harvard Journal of Law and Technology [Vol. 1B. Attraction

T h e l a w is a n a t t r a c t i v e d o m a i n f o r A I r e s e a r c h f or s e v e r a lr e a s o n s . F i r s t , t h e l a w h a s a tr a d i t io n o f e x a m i n i n g i t s o w nr e a s o n i n g p r o c e s s. S e c o n d , le g a l r e a s o n i n g i s s t y li z e d : o n e r e a s o n sa c c o r d i n g t o stare decisis w i t h c a s e s a n d b y a n a lo g y . T h ir d , m u c hl e g a l k n o w l e d g e i s r e a d i l y a c c e s s i b l e a n d r e l a t i v e l y w e l l s t r u c -t u r e d , c o d if ie d a n d i n d e x e d . N e v e r t h e l e s s i t w i l l n o t s u r p r i s e , a n dm a y e v e n p le a se , la w y e r s to le a r n t h a t t h e R e s t a t e m e n t , t h eU n i f o r m C o m m e r c i a l C o d e , a n d c a s e l a w , li k e t h e t h e o r i e s o f l eg a lr e a s o n i n g p r o p o s e d b y K a r l L l e w e l l yn , R o n a l d D w o r k in , E d w a r dL e v i , a n d H . L . A . H a r t , a r e o f l i m i t e d i m m e d i a t e u s e t o A Ip r o g r a m m e r s . T h e r e i s w a n t a m i d s t p l e n t y b e c a u s e th e c e n t r a lq u e s t i o n s - w h a t w e k n o w a n d h o w w e k n o w i t - a r e a n s w e r e d o n lyp a r t i a l l y b y s u c h m a t e r i a l , a n d e v e n t h e s e p a r t ia l a n s w e r s p r o v ed i ff ic u l t t o h a r n e s s c o m p u t a t i o n a l l y .L a w y e r s ' i n t e r e s t i n A I t e c h n i q u e s a n d s o f t w a r e is n a s c e n t b u tc o n c is e ly e x p r e s s e d i n m a r k e t i n g t e r m s . L a w y e r s u s e t o o ls t h a tg a t h e r , s i f t , a n d / o r s t r u c t u r e l e g a l a r g u m e n t s i n a c o s t - e f f e c t i v em a n n e r . L E X I S a n d W E S T L A W , w h i c h a re e s s e n t i a l l y k e y w o r d -b a s e d p r o g r a m s s i f t i n g l a r g e f u l l - t e x t d a t a b a s e s , o p e r a t e a t a le v e lo f s o p h i s t ic a t io n f a r b e l o w t h a t c o n t e m p l a t e d b y A I p r o g r a m m e r ss u c h a s A l a n e G a r d n e r , M a r e k S e r g o t, 4 m y c o l le a g u e K e v i n A s h -le y, 5 o r m a n y o t h e r s . 6 Y e t p r o d u c t s s u c h a s L E X I S a n dW E S T L A W d o i n d i c a te t h e p o t e n t ia l u b i q u i t y o f l e ga l a n a l y s i ss o f t w a r e a n d t h e s y m b i o s is b e t w e e n c o m p u t e r s c i en c e a n d le g a lr e s e a r c h .

C. The HurdlesS e v e r a l s p e c if ic , f a m i l ia r a s p e c t s o f l e g al a n a l y s i s t h a t c h a l-l e n ge A I m a y b e n o t e d .F i r s t , l o gi ca l d e d u c t i o n a l o n e c a n n o t r e s o l v e a l l l e g a l i s s u e s . I nG a r d n e r ' s t e r m s , l e g al r e a s o n i n g i s a r u l e -g u i d e d r a t h e r t h a nr u l e - g o v e r n e d a c t i v i t y (p . 3 ). L e g a l r u l e s h a v e t h e s t a t u s m o r e o fh e u r i s t i c s t h a n o f t h e o r e m s , i n t h a t a ll r u l e s h a v e e x c e p t io n s , a n dr u l e s m a y c o n t r a d i c t .S e c o n d , t h e t e r m s e m p l o y e d i n l e g al d i s c o u r s e a r e o p e n - te x -t u re d . T h a t i s , t h e m e a n i n g s o r d e f in i ti o n s o f m a n y l e ga l t e r m s

4. Sergot Sadri, The British Nationality Act as a Logic Program, 29 COMMUNICATlONSO F TH E A C M 3 7 0 ( 1 9 8 7 l .

5 . R i s s l a n d A s h l e y , A Case.Based System for 7}'ade Secrets Law, PROC. OF THE ANN.CONF. OF THE AM . A. FOR ARTIFICIAL INTELLIGENCE 60 (198 4) ; As h ley , ModellingL~galAr-gument: Reasoning with Cases and Hypotheticals ( u n p u b l i s h e d m a n u s c r i p t ) .

6. See, e.g,, PRO C. OF THE FIRST INT'L CONF. ON ART IFICIAL ][N~rELLIGENCEAND LAW( A C M 1 98 7}. G a r d n e r h e r s e l f o f fe r s a n e x c e l l e n t b i b l i o g r a p h y ( pp . 2 0 1- 1 4) , a n d p r e s e n t s i nC h a p t e r 4 a s u r v e y o f t h e f ie l d c o m p l e t e th r o u g h t h e s p r i n g o f 1 9 8 6.


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S p r i n g , 1 9 8 8 ] Arti f ic ia l In tel l igence 2 2 5a n d p r e d i c a t e s a r e i n h e r e n t l y i n d e t e r m i n a t e i n t h e p h il o s o p h ic a ls e n s e o f n a t u ra l k i n d c l a s s e s .T h i r d , l e g al q u e s t i o n s c o m m o n l y i n v i te m o r e th a n o n e a n s w e r ,y e t l e g al a r g u m e n t i s b o t h t i m e c o n s t r a i n e d a n d r e s o u r c e l im i t e d .F o r w h i l e c o nf li ct , d i s a g r e e m e n t , a n d a r g u m e n t a r e p a r t a n d p a r -c el o f t h e l aw , 7 t h e l a w m u s t p r o v i d e a t i m e l y a n s w e r f o r o n e s i d eo r t h e o t h e r , r e a c h e d a t a s o c i a l ly a c c e p t a b l e c o s t.F i n a ll y , in la w , th e a n s w e r s c h a n g e . W h e t h e r t h e c h a n g e i s in -c r e m e n t a l , a s in t h e m o d e o f K u h n s n o r m a l s ci en c e, o r a b r u p t , a si n a K u h n i a n p a r a d i g m s h if t, a h a r d l e a r n i n g i s s u e s l u r k c lo s e t ot h e s u r f a c e o f t h e l e g a l is s u e s t h a t A I p r o g r a m s a t t e m p t t o r e so l v e .T o a c c o m o d a t e e v e n g ra d u a l c h a ng e , t h e a l g o r it h m s m u s t a d a p tt o a d y n a m i c k n o w l e d g e b a s e : a s h i f t in g f o u n d a t i o n o f c a s e s,s t a t u t e s , a n d t h e i n d i c e s , r u l e s , a n d n o r m s w h i c h m a n i p u l a t et h e m . E v e n t u a l l y o n e m u s t c o n fr o n t t h e c h a n g e i n p r e d i c a t e s a n di n t h e r e p r e s e n t a t i o n i ts e lf , e i t h e r t h r o u g h t h e e m e r g e n c e o f n e wl e g al c o n c e p t s o r t h r o u g h t h e s u b s t a n t i a l m o d i f i c a t io n o f o l d o n e s . 9I n s u m m a r y , l e g a l r e a s o n i n g r e q u i r e s c e r t a in m i n i m u mc a p a b i l i t i e s :1. t h e a b i l i ty to r e a s o n w i t h c a s e s a n d e x a m p l e s , p a r t i c u l a r-

l y t h r o u g h a n a l o g y ;2 . t h e a b i l i t y t o h a n d l e i ll - d ef i n e d , o p e n - t e x t u r e d p r e d i -c a t e s ;3 . t h e a b i l i t y t o h a n d l e e x c e p t i o n s ;4 . t h e a b i l i t y to h a n d l e f u n d a m e n t a l c o nf lic ts b e t w e e nr u l e s ; a n d5 . t h e a b i l i t y t o h a n d l e c h a n g e a n d n o n m o n o t o n ic it y .1 0D. Severa l Poss ib le App roaches

E a c h A I s p e c i a l t y m e n t i o n e d i n S e c t io n A a b o v e i s d e s c r i b e db r i e f ly b e l o w . T h e d i s t i n c t io n s d r a w n a r e noZ a b s o l u t e ; t h e s es p e c i a lt i e s a r e c o m p l e m e n t a r y a n d o f t en o v e r l ap .Case-based reasoning s e e k s t o e m u l a t e t h e c a s e - b a s e d r e a s o n -i n g o f l e g al p r a c t i ti o n e r s . C u r r e n t r e s e a r c h i s f o c u s ed i n p a r t o nc a se m e m o r y a n d i nd e x in g , a s s e s s m e n t o f s i m i la r i ty a n d r e le v a n -cy , c o n t e x t - d e p e n d e n t c a s e co m p a r i so n , a n d a r g u m e n t g e n e r a t i o na n d e v a l u a t io n . A s h l e y s w o r k w i t h t r a d e s e c r e t s u i s a f a i r l y in -c l u s i v e c u r r e n t e f fo r t.Log ic and exper t sy s tems a d a p t e d t o t h e d o c t r in e o f p r e c e d e n t ,

7 . A s G a r d n e r p o i n t s o u t , n o t o n l y a r e a c t o r s i n o u r l e g a l s y s t e m f r e e t o a r g u e , o n h a r dq u e s t i o n s t h e y a r e e x p e c t e d t o d o s o ( p . 3 ).

8 . T . KUHN, T HE STR UC TUR E OF SC lEN TW I C R EVOLUTI ONS ( 1 9 7 0 } .9 . L e g a l r e a s o n i n g t h u s i n e v i t a b l y i n v o l v e s t h e h a r d e s t p r o b l e m s i n le a r n i n g , s u c h a s b i a s

( t he p r ob l em t h a t a n y k n o w l e d g e r e p r e s e n t a t i o n l a n g u a g e d is p o s e s o ne t o e m p h a s i z e o r m i s sc e r t a i n c o n c e p t s / a n d t h e n e w t e r m p r o b l e m ( c o n c e r n i n g t h e p r o g r a m ' s o w n c r e a t i o n o f n e wc o n c e p t s a s n e e d e d ) .

1 0. N n m n t n i c r e a s n i n g i n v Iv e s t h e r e je c t i n a n d / r r e f rm f p r i r d ec i si n s1 1 . R i s s l a n d & A s h l e y , supr n o t e 5 .


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2 2 6 Harvard Journal of Law and Technology [Vol. 1e m p l o y b a c k c h a i n i n g t o r e s o l v e l e g al p r e d i c a t e s . T h e p r o g r a m sp r o c e e d t o w a r d c o n c lu s io n b y e x e c u t i n g a c t io n s n e c e s s a r y t oa c h i ev e id e n t if ie d s u b g o a l s . T h e d a n g e r c o u r t e d h e r e , a s G a r d n e rp o i n t s o u t , i s t h a t t h e r u l e s w i ll r u n o u t b e f o r e p r e d i c a t e s h a v eb e e n r e s o l v e d . C o n f l i c ti n g r e s o l u t i o n s a l s o m a y b e o u t p u t .Natural language processing, i n c l u d i n g t e c h n i q u e s f o r s t o r yu n d e r s t a n d i n g , i s m o s t r e a d i l y a p p l ie d w h e r e s t e r e o ty p i c a l fa c tp a t t e r n s a n d p a r t y r o l e s a r e r e c o g n i z e d . TM S c r i p t - b a s e d u n d e r -s t a n d i n g t e c h n i q u e s m i g h t p r o v e e s p e c i a l ly f r u i t f u l w h e nr e s t r i c t e d to s h o r t c a s e s u m m a r i e s , s u c h a s h e a d n o t e s . I n g e n e r a l,h o w e v e r , n a t u r a l l a n g u a g e p r o c e s s in g i n t h e l a w c o n f r o n ts th es a m e d a u n t i n g c h a l le n g e s o f l a n g u a g e i n o t h e r d o m a i n s . T h e l a w ,a s a m i c r o c o s m o f h u m a n e x p e r ie n c e , p r e s e n t s i n a g g r e g a t e t h ew i d e s t r a n g e o f e x p r e s s io n a n d i n t e r p r e t a t i o n , w h i l e th e s e n s e o fe v e n c o m m o n w o r d s i s p ro b l e m a t i c , '3 a n d s h i f t s w i t h c o n t e x t .F i n a l l y , nonmonotonic reasoning s y s t e m s m a y b e a d a p t e d t oh a n d l e l a w ' s p r o p e n s i t y t o l i m i t o r o v e r t u r n p r i o r r e s u l t s . Ex-ample-based learning m a y e m u l a t e a n y s y s t em , i n c lu d i ng t h el e g al p ro c e s s , w h i c h d e v e l o p s p r i m a r i l y i n r e s p o n s e t o e x a m p l e s .

I I . T H E B O O K A N D T H E P R O G R A M : G A R D N E R ' S A P -P R O A C HA. Gardner s Theory of Hard and Easy Cases

G a r d n e r ' s A I m o d e l r e f le c t s t h e j u r i s p r u d e n c e o f h a r d / e a s yq u e s t io n s , p a r t i c u l a r l y a s d i s c u s s e d b y H .L . A . H a r t , L o n F u l l e r,a n d R o n a l d D w o r k i n ( p p. 3 8 -3 9 ). I n G a r d n e r ' s m o d e l , h a r d q u e s -t io n s c a n a r i s e i n t h r e e w a y s :1. T h e r e e x i s t c o m p e t i n g r u l e s .2 . T h e r e e x i s t u n r e s o l v e d p r e d i c a t e s .3 . T h e r e e x i s t c o m p e t i n g c a s e s .H a r d c a s e s a r e d e t e c t e d b y t h r e e h e u r i s t i c s w h i c h r es o l vep r e d i c a t e s :1 . I f a n a n s w e r c a n b e d e r i v e d u s i n g [ t h e p r o g r a m ' s C o m -m o n S e n s e K n o w l e d g e ( C SK ) ] r u le s a n d i f n o o b je c t i o n s(i .e ., o p p o s i te l y - d e c i d e d c a s e s ) t o u s i n g t h i s a n s w e r c a n

b e fo u n d , a s s u m e t h e q u e s t i o n o f p r e d i c a t e s a t i s f a c ti o nis e a s y a n d t h a t i ts a n s w e r i s t h e a n s w e r j u s t d e r i ve d .(p . 45) .

12. Gardner herselfadopted this approech in the simpler context ofsentences and phrasesrather th an in a continuous story.

13. E.g . Alien Saxon, Compu ter.Aided Normalizing and Unpacking: Some InterestingMachine-Processible Transformations of Legal Rules in COMPUTER POWER AND LEGALREASONING (West 1985).


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S p r i n g , 1 9 8 8 ] A r t i f i c i a l I n t e ll i g e n c e 2 2 7

2 . " I f n o a n s w e r a b o u t t h e s a t i s f a c ti o n o f a l e ga l p r e d i c a t ec a n b e d e r i v e d u s i n g t h e C S K r u le s , t h e n l o o k a t c a s e s ."(p . 46) .3 . ' ~ / h a t e v e r t e n t a t iv e a n s w e r h a s b e e n d e r i ve d u s in g n o n-l e g a l k n o w l e d g e , l o o k f o r c a s e s c a l l i n g f o r t h e o p p o s i t ea n s w e r . " ( p. 46 ) .T h e h a r d / e a s y a n a l y s i s p r o c e e d s i n th e m a n n e r o f g e n e r a t e -a n d - t e s t . A s G a r d n e r s a y s , " [ T ] h e g e n e r a l i d e a i s , f i r s t , t o a l l o we v e r y u n d e f i n e d p r e d i c a t e i n a l eg a l ru l e t h e p o t e n t i a l f o r r a i s i n ga h a r d q u e s t i o n a n d , s e c on d , to p r o v i d e m e a n s f o r c o n c l u d i n g f a ir -

l y q u i c k ly , in a n y p a r t i c u l a r c a s e , t h a t m o s t q u e s t i o n s o f p r e d i-c a t e a p p l i c a t i o n a r e e a s y . " (p . 4 3) I f t h e q u e s t i o n o f p r e d i c a t es a t is f a c ti o n c a n b e d e t e r m i n e d b y a p p ly i n g t h e C S K r u l e s t o t h ef a c ts , t h e p r o g r a m h a s r e a c h e d a t e n t a t i v e a n s w e r . T e n t a t i v ea n s w e r s c arl b e o v e r r i d d e n b y o p p o s i t e c a s e s t h a t o b je c t. O v e r r i d -i n g a l lo w s t h e p r o g r a m t o c o n c lu d e t h a t w h a t a p p e a r e d a t f ir s tg l a n c e t o b e a h a r d q u e s t i o n ( b e c a u s e m e a n i n g s c o u l d n ' t b er e s o lv e d ) is in f a c t e a s y ( b e c a u s e t h e l a w h a s s h o w n h o w t o r e s o l v et h e m ) , o r t o s p o t h a r d q u e s t i o n s ( w h e r e l e g a l r u l e s o r c a s e s c on -f lic t) t o w h i c h t h e C S K r u l e s w e r e a p p l i e d w i t h o u t d i ff ic u lt y.W h i le t h e e a s y m i s l a b a l e d a s h a r d l e a d s to a w a s t e o f r e s o u r c e s ,t h e h a r d m a s q u e r a d i n g a s e a s y m a y l e a d t o f a t a l l y f l aw e d a r g u -m e n t s a n d l o s t c a s e s.

B . T h e P r o g r a m1. D o m a i n a n d T a s k

G a r d n e r ' s p r o g r a m w o r k s i n th e s u b f i e ld o f o f f e r a n d a c c e p-t a n c e f r o m c o n t r a c t l a w . C o n t r a c t l a w i s r e l a t i v e l y s t a b l e , w h a tE d w a r d L e v i w o u l d c al l a " s e c o n d s ta g e " d o m a i n , 4 r o u g h l y c o r-r e s p o n d i n g t o K u h n ' s n o r m a l s c ie n c e sta ge .1 5 C o n t r a c t l a w i s f a ir -l y r e l ia b l y s t r u c t u r e d b y t h e R e s t a t e m e n t S e c o n d ) o f C o n t r a ct s,a b u n d a n t c a se la w , a n d t h e U n i f o rm C o m m e r c ia l C o de . G a r d n e rd i s c u s se s in g r e a t e s t d e t a il h e r p r o g r a m ' s t r e a t m e n t o f A d a m s v.L i n d s e l l , t h e c l a s si c c l a s s r o o m c r o s s e d - o f f e rs c a se . I n p u t is- p r e s e n t e d i n t h e t e x t i n t h e g u i s e o f " [a ] t y p i c a l e x a m i n a t i o nq u e s t i o n " ( p . 4 ). T h e f a m i l i a r t a s k , i n b r ie f , is to s p o t t h e i s s u e s ,a q u i n t e s s e n t i a l l y " i n t e l l i g e n t " p r o c e s s .T h e i s s u e - s p o t t in g t a s k m a y b e v i e w e d a s a se a r c h t h r o u g h as p a c e o f p o s s i b le a l t e r n a t i v e i n t e r p r e t a t i o n s o f t h e f a c ts . S i n c e n o t

14. E. LEVI,AN INTRODUCTIONTO LEGAL REASONING9 (1949) ('rhe second stage is theperiod when the concept is more or less fixed, although reasoning by example continues toclassify items inside and out of the concept. ).15. T. KUHN,supr note 8.


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228 H a r v a r d J o u r n a l o f L a w a n d T e ch n olo g y [Vol. 1all issues are worth arguing about, and in the cont ext of an examor litigation there ar e time and space constraints, the n atu re ofthe search m us t of necessity be heuristic. The ta sk is how to selectissues which raise de fens ib l e arguments, or, in the language ofsearch, how to distinguish the plausible from the merely pos-sible. 162 . I n p u t

Gardner's program-which is never given a persona with ana me -s ta rt s with a set of facts which have been entered by handinto a form acceptable to her program.3 . S t ruc ture

Legal knowledge in Gardner's program is contained in twosources: network struct ure s and legal rules. An Augment ed Tran-sition Network ( ATN ) rep res ent s the st and ard states in a con-tract situation with in terpr etatio ns of events as the links, orarcs, '17 betwe en them. Legal rules rep re se nt certain prototypi-cal legal fact pattern s and are dr awn upon to resolve whe ther anATN arc may be traversed. Legal anteced ents neces sary to con-clude whether a contract exists are formalized e.g., reasonable-certainty, exchange, may-be-willing-to-enter).Gardner's program has an ATN with twenty-three states,twe nty legal rules (of which two pairs are conflicting and thr eepairs are complementary), and approximately 100 generalizedfact patterns. Her simplified transition network is reproducedbelow: 184 . A l g o r i t h mTo produce the analysis of legal choices, Gardne r's programemploys several sources of legal, linguistic, and common senseknowledge. Common sense knowledge is repr ese nted in two ways:(1) a slot-filler langua ge is used to describe fact situations; and (2)a hi era rch y of such thi ngs as events, states, and objects, is imple-mente d through a mec han is m of Common Sense Knowledge

16. Gar dn er relies upon Llewellyn to mak e this point (p. 9): [W]hile it is possible to builda n umb er of divergent legical ladders up out of the sam e cases and down again to th e sa medispute, there are not so many th at can be built defensibly. And ofthes e few there are some,or there is one, toward which the prior cases pre tt y definitely press. (K. LLEWELLYN, THEBRAMBLE BUSH: ON OUR LAW AND ITS STUDY 73 (Oceana Publ icat ions 1960)).

17. ~rhe arcs of the n etwor k correspond to eve nts that can chan ge the legal relations be-tween the partiosZ(p. 124) There is no arc to represent the lapse of time.

18. ~State 0: No legal rel ati ons exist.State 1: One or more offers are p end ing the offeree has the power to accept.St at e 2: A con tract ex-ists.Sta te 12: A cont ract exists, and a proposal to modify is pending. {pp. 123-241


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Spring, 1988] A r t i fi c i a l I n t e ll ig e n c e 229rejection,revoking acceptance

oounteroffermodification / [o f o t h e r 4 . p t a o c e /acceptance,rejection,revocation,death

rejection, counteroffer,revoking acceptance acceptancelusproposal to modifyTra nsi tion Network for Offer and Acceptance Prob lems (p.124)rules. The rules themselves are highly structured objects withext ra components (such as e l imina te -on-fa i lure andeliminate-on-success, which prune ATN arcs from considera-tion), and secondary anteceden ts, which provide some look-ahead for information useful in resolving hard questions. 19These ideas are embodied in an algorithm which forms thebackbone of Gardner's program. This algorithm is outlined below.The mechanism s of applying CSK and legal rules to work one'sway around the ATN are in fact quite involved and are discussedat length in Chapte rs 5 and 6.

If (there is a tentat ive answer)then if (there are no opposite cases)then (the case is easy ;but if (there a r e opposite cases)then if (there are also similar ly aligned cases)then (the law is unsett led and the question is hard ;otherwise (let the technical legal rule override theconfilicting CSK rule; the answer is easy .

If (there is no tentative answer)then if(no cases match)or if (two or more cases match bu t conflict)then (the cases fail to resolve the issue and the questionis hard ;otherwise (the question is e a s y and the answer is th atindicated by the case(s) th at match.19. These CSK .'-ales are encoded in a standard fashion using Michael Genesereth's MRS

language (e.g., *one carload of salt is {carloads C1) (number C1 1) ), described in The MRSDictionary, Memo HPP-80-24, Stanford Heuristic Programming Project, Stanford University.


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2 3 0 H a r v a r d J o u r n a l o f L a w a n d T e ch n olo g y [Vol. 1

5 . O u t p u tT h e o u t p u t o f G a r d n e r ' s p r o g r a m i s a tw o - le v e l a n a l y s i s r e p -r e s e n t e d i n t w o g r a p h s ( F i g u r e s 7 . 4 a n d 7 . 5 , p p . 1 73 -7 6 ). T h eu p p e r le v e l o f F i g u r e 7 . 5 s u m m a r i z e s i n t e r p r e t a t i o n s o f h e e v e n t si n t h e f a c t s i tu a t io n . B r a n c h p o i n ts r e p r e s e n t h a r d q u e s t i o n s -p o i n ts w h e r e a l te r n a t i v e , c o m p e t i n g i n t e r p r e t a t i o n s m u s t b er e c o g n i z e d . I n e f fe c t , ~ he u p p e r l e v e l is a d e c i s io n t r e e w h o s eb r a n c h i n g n o d e s r e p r e s e n t h a r d q u e s t i o n s a n d w h o s e l e a f n o d e sc o r r e sp o n d t o s e p a r a t e s e q u e n c e s o f i n t e r p r e t a t i o n s o f t h e e v e n t s .

F r o m s u c h a r e p r e s e n t a t i o n o f i s s u e s , it i s a s h o r t i n f e r e n t i a l h o pto a n s w e r t h e b i g q u e s t i o n s o f w h e t h e r a c o n t r a c t e x is ts a n d w h a ta r e t h e a r g u a b l e i s su e s . F o r e a c h u p p e r l e ve l b r a n c h p o i n t th e r eis a l o w e r l e v el d e t a i l e d a n a l y s i s ( s u c h a s i n F i g u r e 7 .4 ) s u p p o r t -i n g t h e d i v e r g i n g in t e r p r e t a t i o n s .G a r d n e r ' s m o d e l t h u s i s a b le to a n a l y z e i s s u e s p o t t e r q u e s t i o n ss u c h a s t h a t p r e s e n t e d b y a s ty l iz e d A d a m s v. L i n d s e l l . A s s h ed i sc u s s es , h e r p r o g r a m ' s e i g h t m a j o r tw o - w a y b r a n c h p o i n ts a n dn in e c o n c o m i ta n t a n a ly s e s a r e p e r h a p s m o r e t h a n a h u m a nl a w y e r m i g h t c o n si de r , b u t th e s e b r a n c h p o i n t s c o m p a r e w e l l t oh e r e s t i m a t e o f a p o s s i b l e s e a r c h s p a c e o f f iv e t o t h e n i n t h p o w e r .T h e p r o g r a m r e p o r t e d l y p e r f o r m e d c r e d i t a b l y o n a n a s s o r t m e n to f p r o b l e m s f ro m G i lb er t s L a w S u m m a r i e s (pp . 183-88) .

I I I . C O M M E N T A N D C O N C L U S I O NA n n e G a r d n e r i s e n t i re l y c o rr e c t i n s t r e s s i n g s u c h p a r a d i g m s

a s o p e n t e x t u r e a n d '~ h a rd /e a s y. T h e s e a r e c e n t r a l t o l e g a lr e a s o n i n g a n d o p e n u p v a l u a b l e l in k a g e s t o o t h e r A I d i sc ip l in e sa s w e l l a s l e ga l p h il o s o p h y . M o r e o v e r , G a r d n e r ' s w o r k g iv e s s o m er e a l c o m p u t a t i o n a l f l e s h t o t h e p h i lo s o p h i c a l s k e l e t o n o f t h eh a r d / e a s y d i s ti n c ti o n , p r o v i d i n g a m o d e l fo r c r i t i q u e b y b o t h l e g a la n d A I p r a c t i t io n e r s .H o w e v e r , w i t h s p ec if ic r e g a r d t o G a r d n e r ' s m a n n e r o f d i st in -g u i s h i n g h a r d a n d e a s y q u e s ti o n s , I s u g g e s t t h a t a n y r e a l is t ic c a s eb a s e w i ll i n v a r i a b l y p r o v i d e c o n t r a r y , o p p o s i te c a se s . C o n s e q u e n t -ly , h e r h e u r i s t ic s w i l l c h a r a c t e r i z e n e a r l y a l l q u e s t i o n s a s h a r d .O n e a n s w e r i s t o r e c o g n iz e t h a t n o t a ll o p p o s i t e c a s e s a r e e q u a l ,a n d t h a t s o m e c o n t r a r y a r g u m e n t s a r e m o r e r o b u s t t h a n o th e rs .O f c o u r s e , t h i s r e q u i r e s o n e to r e a s o n w i t h c a s e s a n d , m o r e d if-f ic u lt ly , a b o u t a r g u m e n t s - a t r e m e n d o u s t a s k , b u t p r e f e r a b l e t oo v e r r e li a n c e u p o n r u l e s a n d g e n e r a l iz e d f a c t p a t te r n s . I n p a r -t ic u l a r , I s e e c a s e s a s p l a y i n g a m u c h m o r e c e n t r a l r01e t h a n t h e yd o i n G a r d n e r ' s m o d e l . T h e r e fo r e , I w o u l d a d d r e s s w i t h s o m e c a r et h e d e t a i l s o f n d i v i d u a l c a s e s w h i c h a r e c r it ic a l f o r i n d e x in g , a n a l -


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Spring, 1988] Artificial Intelligence 231ogy, and other aspects of case:based reasoning. However, usingcases in a more central role and not ju st as annotati ons or exis-ten tia l embodiments of concepts would require deep changes inGardner's program.Nevertheless, Anne Gardner has done landmark research inthe field of AI and legal reasoning. Not wit hsta ndin g ourjurisprudentia l differences, I feel th at Gardner has made a sub-stantial contribution to AI and legal reasoning which will havemajor impact upon both disciplines. Not only has she performedground-breaking work on such topics as issue spotting, open tex-tured predicates, and the hard/easy paradigm, she has alsopointed the way to fu rther work on case-based reasoning and ar-gumenta tion. The book is well wri tten and has served my classesat Har vard and Amherst well. In particular, her introduction andexplication of legal philosophy from the perspective of AI (Chap-ters 2 and 3) are unrivalled in the current literature. An Artificial Intelligence Approach to Legal Reasoning is essential toanyone working in the field, and invaluable to those who wish towork in the field. And th at is an easy question.


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Spring, 1988] ooks Received 233

O O K S R E C E I V E DIF WE CAN KEEP A SEVERED HEAD ALIVE..., by Chet Fleming.Polinym Press, P.O. Box 22140, St. Louis, Missouri 63116. pp. 4611987).AN INTRODUCTIONTO KOREAN INTELLECTUALPROPERTYLAW, byByong Ho Lee. Central International Law Firm, Korea Rein-surance Building, 80 Soosong-dong, Chogno-ku, Seoul, Korea. pp.453 1987).ENGINEERS AND THE LAW / AN OVERVIEW,by Bruce Schoumacher.Van Nost rand Reinhold, 115 Fifth Avenue, New York, New York,10003. pp. 337 1986).

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