aarons@cvaxa.sussex.ac.uk (Aaron Sloman) (02/03/89)
[Re-posting. First attempt seems to have failed.] Hi Don, I've only just seen this >From: norman@cogsci.ucsd.EDU (Donald A Norman-UCSD Cog Sci Dept) >Subject: Re: replacing the desktop metaphor (Why any metaphor?) >Message-ID: <673@cogsci.ucsd.EDU> >Date: 25 Dec 88 17:34:01 GMT >Subject: Re: replacing the desktop metaphor (Why any metaphor?) >I suspect that metaphors are useful in keeping consistency. But >now Jonathan Grudin is about to present a paper in CHI 89 arguing about >the foolishness of consistency: systems are often improved by >violations. I was pleased to see this. I have often annoyed people interested in programming languages and learning environments, by attempting to defend the following slogan: "Power is more important than consistency" The most obvious example of the trade-off is the comparison between any natural language (all of which, I believe, are very powerful but riddled with inconsistencies) and either predicate calculus or any other formalism that logicians and mathematicians have devised. For reasons which I do not fully understand <but see below>, natural languages, despite all their complexity and inconsistencies, seem to be things that all (or should I say most?) human beings learn with far less resistance than the simpler, more consistent, artificial formalisms. Let's call the former "scruffy" formalisms, the latter "neat" formalisms, following Bob Abelson's labelling of AI types. (Clearly there's a whole spectrum of cases, with most programming languages a curious mixture of neatness and scruffiness.) Neat formalisms, including Predicate calculus, BNF and number notations are learnt, and put to very good use, by a subset of the population, for a subset of their activities. So this is not an all-or-nothing issue. (I've never met a logician or mathematician who attempts to communicate with her children solely using a neat formalism.) Also, although it is probably clear that overall natural languages are more powerful and general than any artificial and neat formalism so far devised (e.g. natural languages, or at least the ones I know about, contain their meta-languages, and allow creative deployment using metaphor and other devices) there are specific kinds of power that they don't have. E.g. try to explain in English what it means for something to be increasing its speed while decreasing its acceleration, then explain it using the notation of differential calculus. So further development of this topic would require a taxonomy of kinds of power of formalisms. I suspect that one reason why the scruffy more powerful natural systems are more suited to the human mind is that they handle far more special cases directly e.g. using particular words, phrases, idioms, etc., that just have to be memorised, rather than interpreted on the basis of general rules. By contrast, the neat artificial systems require you to do some problem-solving to find the right construction, or some analysis and interpretation to understand one produced by someone else. (The best way to explain how 'Can you pass the salt?' is interpreted as a request rather than a question, is probably by saying that people simply remember that that is how it is used. Of course, it is possible to derive the interpretation using very general principles and assumptions, but nobody need bother to derive this if they simply learn the usage along with all the other bizarre special forms of expression encountered in natural languages. E.g. I can do something for your sake whether you have a sake or not. Of course, general principles may explain how something got into the language in the first place, even if they play no role in the particular uses of the construct.) A common observation may explain all this: Human brains appear to contain very powerful and fast associative storage mechanisms with very large storage capacity. They also appear to have relatively slow and incomplete problem solving mechanisms. This suits the learning and use of large numbers of particular cases, rather than the derivation of particular cases using powerful generative principles. Moreover, I don't think this is simply a feature of the human brain - pressures toward this kind of imbalance are probably a result of design requirements for any physical implementation of an intelligent system that generally has to act within severe time constraints. This is because (almost) all symbolic derivational processes are inherently combinatorially explosive. However, any formalism that copes directly with lots of special cases, i.e. has constructs defined specifically to deal with them, is far more likely to exhibit inconsistencies than a formalism that has a relatively small and powerful set of primitives which can be combined to generate all the special cases in a principled way. This is because checking for consistency is also an inherently combinatorially explosive process: the number of things to check is an alarmingly fast-growing function of the number of items in the system when the inconsistencies can involve relationships between arbitrarily large sets of items. Of course there are all sorts of exceptions, including the case of people using a system that is inherently simple and therefore needs only a relatively simple formalism (e.g. arithmetic?) or people using a system only infrequently, so that they can't be expected to remember all the special cases. Perhaps if human languages were not used so frequently in daily life they'd have evolved different characteristics? If, for the reasons indicated, scruffy and powerful systems are generally easier for people to learn and use (on a regular basis) than neat consistent systems that obtain their power from generative rules, then people designing learning environments (and increasingly ALL computing systems will be learning environments for their users), will be under strong pressure to sacrifice the requirement of consistency. Dare I say QED? Incidentally, all this is one reason why I favour Pop-11 over Lisp (or LOGO) as a programming language for beginners. The syntax of Lisp is elegant and is very powerful if you can parse it, whereas that of Pop-11 has lots of special case constructs, and is highly redundant, and apparently simpler for people to parse (though not simpler for computers to parse). I think the redundancy helps to make it easier for human brains to take in, despite the greater surface complexity such as the use of matching pairs of opening and closing keywords until ... enduntil for .. endfor define .... enddefine if .... endif etc. [This needs systematic research] Returning to Macs and the like: The desktop metaphor may be a simple and consistent one for a range of tasks, that are relatively simple. But what about 'show me all the files in folders A and B that have the substring "prog" in their names' 'Move everything that I haven't looked at for at least 5 days to folder OLD' 'Whenever anyone else looks at any of my files, please add their names to my nosey file' When I'm getting near my disc quota send me a mail message. If any mail message arrives mentioning grants tell me immediately. "Direct manipulation" analogous to shoving things around on desk-tops or rooms etc is only relevant to a tiny subset of the things most of us really want to do with information systems. Maybe only the first few things we want to do... > Where consistency and mepaphor and consistent > system images-mental models help and where they hinder is not yet > properly understood. > Time for some more research, folks. > don norman I agree! Aaron Sloman, School of Cognitive and Computing Sciences, Univ of Sussex, Brighton, BN1 9QN, England ARPANET : aarons%uk.ac.sussex.cogs@nss.cs.ucl.ac.uk aarons%uk.ac.sussex.cogs%nss.cs.ucl.ac.uk@relay.cs.net JANET aarons@cogs.sussex.ac.uk BITNET: aarons%uk.ac.sussex.cogs@uk.ac or aarons%uk.ac.sussex.cogs%ukacrl.bitnet@cunyvm.cuny.edu UUCP: ...mcvax!ukc!cogs!aarons or aarons@cogs.uucp IN CASE OF DIFFICULTY use "syma" instead of "cogs"
dykimber@phoenix.Princeton.EDU (Daniel Yaron Kimberg) (02/05/89)
[I've lost the attribution line, but >> prefaces the remarks of Donald Norman] In article <548@cvaxa.sussex.ac.uk> aarons@cvaxa.sussex.ac.uk (Aaron Sloman) writes: >>I suspect that metaphors are useful in keeping consistency. But >>now Jonathan Grudin is about to present a paper in CHI 89 arguing about >>the foolishness of consistency: systems are often improved by >>violations. > "Power is more important than consistency" I wonder if it might not also be worthwhile developing the idea that consistency is important, but misunderstood. Of course, I'm speaking from relative ignorance since I haven't read Grudin's paper. But take, for instance, a set of options displayed to the user. Does consistency require that all the buttons look the same, or different? [ugly example, but you get the idea] Should the user interface be internally consistent? or should it be consistent in its relationship to the system as a whole? Not having seen Grudin's work, I tend towards the idea that the interface should be made consistent with the functioning of the system (different looking menus for different sorts of options, perhaps), and only then made internally consistent towards the goal of simplicity. Two similar looking buttons for different functions is a form of interface-function inconsistency. I suspect that interface-interface consistency (same look/feel for all buttons) is only appropriate in situations where it doesn't reduce the salience of the important relation between the interface and the system itself, but instead serves to reduce the number of potentially confusing inconsistencies which are equally salient but are not indicative in any useful (e.g. non-redundant) way of state differences. This is somewhat echoed in the literature in the concern that visual representations of internal state variables be availalble on-screen. I wonder if someone who's familiar with Grudin's work could mention whether or not there's any indication as to which of these sorts of consistency are covered, or if he makes this sort of distinction explicitly. >(The best way to explain how 'Can you pass the salt?' is interpreted as >a request rather than a question, is probably by saying that people >simply remember that that is how it is used. Of course, it is possible >to derive the interpretation using very general principles and... It would be a good thing to note at this point that "remember" as you've used it above probably doesn't represent memory in the traditional sense, but rather (and more in the spirit of Dr. Norman's work) in the sense of instantiating a certain schema. We would have no more trouble deriving the same interpretation from "might you pass the salt?" or "do you think you could get me a glass of water?" >If, for the reasons indicated, scruffy and powerful systems are >generally easier for people to learn and use (on a regular basis) than >neat consistent systems that obtain their power from generative rules, >then people designing learning environments (and increasingly ALL >computing systems will be learning environments for their users), will >be under strong pressure to sacrifice the requirement of consistency. > >Dare I say QED? I hope not. As Dr. Norman wrote: >> Where consistency and mepaphor and consistent >> system images-mental models help and where they hinder is not yet >> properly understood. And then he said something like "Time for more research" [i lost the line]. Not a bad idea. -Dan