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<Paper uid="P84-1090">
  <Title>Correcting Object-Related Misconceptions: How Should The System Respond? t</Title>
  <Section position="2" start_page="0" end_page="444" type="intro">
    <SectionTitle>
1. Introduction
</SectionTitle>
    <Paragraph position="0"> A meier ar,.a of Al research has been the development of &amp;quot;expert sys.tcms&amp;quot; - systems which are able to answer user's que:~titms concerning a particular domain. Studies identifying desirabl,, iutora,'tive capabilities for such systems \[Pollack et al. 82\] have ft,und that. it is not sufficient simply to allow the user to ,~k a question and Itavo the system answ~.r it. Users often want to question the system's rea-~oning,to make sure certain constraints have been taken into consideration, anti so on. Thus we must strive to provide expert systems with the ability to interact with the user in the kind of cooperative di:LIogues that we see between two bullish ctmversational partners.</Paragraph>
    <Paragraph position="1"> Allowing .,uch interactions between the system and a user raises difficulties for a Natural-Language system. Since the user is interacting with a system a.s s/he would with a human export, s/he will nizam likely exp-ct the system to b(have as a human expert.</Paragraph>
    <Paragraph position="2"> Among other things, the n:.er will expect the systenl to be adhering to the cooperative principles of conversation \[Grice 7,5, .loshi 821. If these principte~ are not followed by the system, the user is bkeiy to become confu~ed.</Paragraph>
    <Paragraph position="3"> In this paper I.focus on one a,;pect of the cooperative behavior found between two conversat, ional partners: responding to recognized differences in the beliefs of the two participants. Often when two people interact, ouc reveals-a belief or assumption that is incompatible with the b~*liefs held by the other. Failure to correct this disparity may not only implicitly confirm the disparate bcli,'f, but may even make it impos~;ibie to complete tile ongoing task. Imagine the following excilange: U. Give ll|e the ItUI.L NO of all Destroyers whose MAST_IIEIGIIT is above 190.</Paragraph>
    <Paragraph position="4"> E. All Destrt,yers that I know al)out |lave a MAbT_HEIGllT between 85 and 90. Were you thinking of the Aircraft-Carriers? in this example, the user (U) ha.s apparently ctmfused a Destroyer with an Aircraft-Carrier. This confusion has caused her to attribute a property value to Destroyers that they do not have. In this case a correct a/tswer by the expert (E} of *none&amp;quot; is likely to confuse U'. In order to continue the conver.-ation with a minimal amount of eoafu.~ion, the user's incorrect belief must first be addressed.</Paragraph>
    <Paragraph position="5"> My primary interest is in what an expert system, aspiring to human expert performance, should include in such responses. In particular, \[ am concerned with system responses to te~'ognized disparate beliefs/assumptions about cbflct.~. In the past this problem has been h, ft to the tutoring or CAI systems \[Stevens et aL 79, Steven~ &amp; ('ollins 80, Brown g:: Burton 78, Sleeman 82\], which attetupt to correct student's misconceptions concerning a particular domain. For the most part, their approach ha.~ been to list a priori :dl mi.-conceptions in a given domain. Tile futility t,f this appr,~ach is empha'.,ized in \[gleeman ,~2\]. In contrast,the approach taken hvre i~ to ,-la:,~iry. in a dolttnin independent way, obj,'ct-related di.-pariti,~s ;u:c,~rding to the l'~n.wh'dge ~:tse (l(.I~) feature involved. A nund)er of respon:~e strategies :ire associated with each resulting cla,~. Deciding which strategy to use for a given miseoncepti,m will be determined by analyzing a user model and the discourse situation.</Paragraph>
    <Paragraph position="6"> 2. What Goes Into a Correction? In this work I am making thc btllowing assunlptions: * \]:or th*, purposes .f the initial correct.ion attempt, the system is a~umed to have complet,, attd corr~'ct knowledge of the domain. Th:tt is. the system will initiMly perceive a disparity as a mise.neel,tion on the part of the u~er It willthus attempt to bring tile user's beli~,fs into line with its own.</Paragraph>
    <Paragraph position="7"> * The system's KB i~tclude-: the following fo:t~trce: an object taxonomy, knowledge of object attributes and their possible values, and intornlation about I)O.~ible relationships between ol)jects.</Paragraph>
    <Paragraph position="8"> * Tile user's KB contains similar features, llowev,'r, mneh of the information (content} in the system's !'(B may he mb-.~ing from the u~or '~ b~ll \[e.g., the us+,r's l'(\[~ may I)e ~parser ot coarser than the system's I(B, c,r various attributes (,~f c~:nccpts ma~ t;e missi:~g frets the u~,'r's I'(P,}. In additi~m. ~.me inf,~rmation ia the u.,er's KB may be wrong, in tiffs work, to say that the user's KB is u'rong means that it is i.,:'m.:i.~terJ with the ,~g.,t,m) KB (e.g., things may be c!a.'~ified differently, properties attributed differently, and ~'o on).</Paragraph>
    <Paragraph position="9"> IThiz v, ork is p~rtiMb&amp;quot; supported by the NSF gr~nt #MC~81-07200.  * Whiw the system t~\]ay n,,t km,w e:;actly what is c(m~ained in the user's l,~b', information about the user C/-:tt~ b, ~ d(,riv,'d hum two smtrcrs. First, the .~ystem can have ,q tm.h,I of a canoni,:at u,mr. (Of course this m.,h,\[ m:ty turn o.t t,, differ from any given user's model.) ~.~,,,'~,ndl)', it ,'an deriw&amp;quot; knowledge about what * the user kn.ws fr,nt the ongoing dise.urse. This l:tt,.r type of km)~h'dge eop,~titutes what the' system discer~s to bt, tits, mutual h(.liv.:s of the system attd user as defin.d iu \[.h,.hi 82\]. &amp;quot;\['he.-,e t~s,~ s,)ur(',~,s .f informati,m together r'.n~t it ul c the s)stem's model of the user's KB. ThN h,,,:t.I itself may be incompi,,te arid/or ine,,rrect witlt respect tt, t\]te system's KB.</Paragraph>
    <Paragraph position="10"> A tt,-'r'~; utterance refh.cls .ither the state of his/her KIL -r ~,,m,) re:~s..i~,g s/he ha~ just done t() fill in some mi.,sing p:;rt of ~.h:,t K,q, or both.</Paragraph>
    <Paragraph position="11"> (;lynn Ilu,~e a~suinptit,ns, we earl consider what shouhl I)e htch~d,:d in a rcsp.nse to an object-r,'htt,'d disparity. If a person exhiltit~ wh.at hi-/her conv~ r.-.ationa\] partn~,r perceives as a Inisconcellti,,n, I IH' vory least one w~mld expect from that partner is to deny t|.. fal.e inf.rmation ~ - for example -U. I th.ugh |a whale wa~ a fish.</Paragraph>
    <Paragraph position="12"> g. It's n.t.</Paragraph>
    <Paragraph position="13"> 'l'ranscript~ of &amp;quot;u:d ura\[ly ~wcurring&amp;quot; expert systems show that experts often include more informati,m in their response than a siHIpl,' d,'nial. Tit(. ,'xp~,rt Inn)' provide all alterhative true st:~tem~.nt (e.g., &amp;quot;\Vha;,.~ :,re marnnt:d';'). S/he may offer ju~.t ifb'at ion andb,r supp.rt for the rt~rr,wtion (e.g., degVChales are nt:~mln:~l~ J)r,('au~*&amp;quot; t il%V hen:/the through hmgs and h'ed their young with milk.'}. S/he nmy als. refute the faulty reasoning s/he tho~tght the ns~r had d.ne tt, ~,rrive at the misconception (e.g., &amp;quot;llaving fins and li~ ing in the water is not enough to make a whale a fish.'}. This behavior can be characterized a.s confirming the corr4.et inh,rmation which mc\]y have h'd the user to the wrong conclusion, but indi(:ating w.hy the false conclusion does no! follow by bringing in a:lditional, overriding information, s The ltroblem f,,r a computer sy,-tem is to decide what kind ~C/ ihformu!itm re:C,' I,e supporting a given misconception. What things m::y he relevant? What faulty reasoning may have been done? 1 char:~cterize -bject-relatcd misconeeptious in terms of the Kll fl,tturt inwJved. Misclgssifying an object, deg1 thought a whale was a fish', i.wAw.s the SUlwrordinate KB feature. Giving an object a pr-p.rty it doe~ not have, &amp;quot;~Vhat is the interest rate on this st,,ck?', lovely,.: the, attriltu:e KB feature. This chatactC/~ri~:di-n i. helpful in d,-termining, in terms of the structure of a K\[L what htform;\]tion may be supporting a particular mis,'onr,'ption. Thus, it is helpful in determining what to include in the r-..'ponso.</Paragraph>
    <Paragraph position="14"> 2Throtlghout this work I am as.-~tmlng that tht miseone*ption if impttrt~nt to the tlk~k at hand and should therefore be corrected. The re.q,~ases I am intcrest(,d in PSeneraVing at( the &amp;quot;full blown&amp;quot; resl, Ot;~es. if * mlsecneeption is det~,c\]rd which N n,al ilnl,or\].t.!~t to the task at hand. it is conceivable that eith,:r th,. lillSc')ll,'olltiOB tl~ ignored or a It, rlrtlllled I vPrC/~on of o/\]e t;\[' those r,,~l,Oll..,.$ |In givPii.</Paragraph>
    <Paragraph position="15"> 5'l'h~. :~r~l, ~;b' exhH.ih,.I hy *i~, '..:,r;.,u ..xp,tt~ is v,,cy Anfilar to the &amp;quot;grain of truth&amp;quot; rorr~.,'tion f,~.nd ic tu~erit~g si\]uations a~ i,t, I,';fied in tWo.If &amp; Mcl),*.ald ~3 I. &amp;quot;FhN .'trat,'gy first id,.nGSes th,, grai~; t,( truth i\[~ a student's answ~.r xlld lip-it go~.'&lt; Oil to give tit- eorrC/,t I ;,n,~or.</Paragraph>
    <Paragraph position="16"> In the foil.wing sections l will discuss the two classes of object trii~.conreptions just mentioned: superordinate misconceptions and attribute misconceptions. Examples of these classes :d.ng with correction strategies will be given. In addition, indications of how a system might choose a particular strategy will be investigated.</Paragraph>
  </Section>
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