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Why should taxpayers fund HCI research?

Stephen W. Draper
GIST (Glasgow Interactive Systems cenTre)
University of Glasgow
Glasgow G12 8QQ U.K.
email: steve@psy.gla.ac.uk
WWW URL: http://www.psy.gla.ac.uk/~steve

Contents (click to jump to a section)

Prologue: why produce the arguments?

A few months ago at a committee meeting I was put in the position of being asked to justify funding for HCI relative to other fields. I was not prepared for this and did a poor job. At HCI'97, a panel (Birch; 1997) discussed the issue, but its arguments did not seem to me convincing: I may myself believe it is worthwhile, but I wouldn't have been convinced by the arguments offered there. Others in the field seemed poor at this too.

Con

Why should we be good at it? There are other academic fields that deal with this -- with the history of technology, its origins and economic impact -- but that is not our specialism. The people at the Science Policy Research Unit at Sussex University for instance certainly know better than us about the theory and evidence of effects of research. The way I mention in this document the unsystematic collection of things I do shows how much there is to understand about technological history / interactions, and how ill-qualified I, and I think most HCI researchers, are. This explains our incompetence at producing good arguments ...

Pro

... but it probably does not excuse us. If we don't justify the money we take, why should anyone else? I certainly think most other parts of society should be accountable for the public money they spend, so I guess we should be accountable for HCI research funding.

Government is asking the research councils to demonstrate the relationship between research funded and utility to other parts of society ("users"), and they in turn are asking their researchers to supply them with ammunition. If we don't do it, then at best someone else will invent a rationale, and we will have to work to it. So we had better practice this until we have a satisfactory line, preferably with specific cases and evidence. Note that it is open to us to identify kinds of users (beneficiaries of HCI research) and kinds of utility (benefit to such users): doing so is part of establishing the kind of HCI research we think best.

Introduction to the arguments for state funding

It is open to us to identify kinds of user (of HCI research) and kinds of utility (benefit to such users). However, as will be seen, our first reactions reveal what amateurs we are at this argumentation because we think first of simple ideas from popular culture (often called "commonsense": the "common" bit at least is right) that do not stand up to scrutiny. Just because Thatcher was unaware of the existence of society, thought "good" = "money", and "benefit" = "profit to industry" does not mean we have to work with those invalid notions. We should do two things: work on existing arguments to reject the invalid and refine the valid, and reflect on our experience to identify what kinds of things are valuable and do work, however unfamilar some of that may be in terms of what we read in the newspapers as common arguments.

The classic direct commercial exploitation model

The first thing everyone thinks of as justifying scientific research is the invention of something directly exploitable. On this model, government pays for research, the researchers patent something, industry pays huge royalties to use the invention.

Pro

Everyone can understand this, and it fits the spontanous conception of how research is useful.

It is a problematic issue who should control patents, and another who should make money from them. But without patents it is often hard to get much acknowledgement that there was an idea that benefitted people.

Con

  1. There is only one area in which this model clearly works: pharmaceuticals. It is so well understood there, that drug companies pay for research, even though each particular chemical is a very long shot. The trouble is, that government funding is unnecessary here because the model is so clearly applicable. It is untrue that industry is incapable of taking the long view, of funding low probability research. In this area, the statistics are clear, and private funding works.

  2. As far as I know, there are no important patents in HCI. Furthermore, the inventors have gone unrewarded e.g. Englebart's invention of the mouse. The GUI interface (Graphical User Interface) has changed everyone's daily life, but Apple has failed to sue Microsoft for doing a poor imitation of it; and Apple took a lot of it from Xerox work on the Star and maybe Smalltalk. (But then again, getting it fast and getting it cheap are very important to users: is it true that someone "invented" GUIs if they didn't achieve that? Would you use menus if they took 10 seconds to open?) Doing world-changing research that improves everyone's life has not resulted in wealth for the researchers and their sponsors. The WWW (World Wide Web) is another example: the key breakthrough was adding GUI to the existing gopher network, but no patent, and little credit.

  3. Would we want this anyway? Organising an area around patents leads to one possible social setup. Drugs are organised that way, which means governments don't have to budget for the huge research costs; but it also means that people are dying now in South Africa because they can't afford the drugs whose high price reflects the need of drug companies to exploit when they can. A quite different social organisation exists around the web, with the policy of commercial companies giving away free browsers for now.

Technology transfer of ideas or inventions

There is a huge amount of work in turning novel demonstrator software into a product robust enough for widespread use. The fact that most software is copyrighted not patented is in approximate correspondence to the fact that the expression of a good idea in robust software is where most of the person-years of work are: i.e. in the expression in code for particular platforms and its integration into software suites, not in the novelty of the original idea. The way the scientific community writes its history (giving all the credit to one early worker in the history of each idea) is not a neutral, accurate, or even sensible way of writing history (Winston; 1986), but an artificial convention of academic science. Technology transfer requires its own genius, effort, and probably funding. For instance take penicillin. Fleming did about 2 days work, if that, and that work mouldered in a journal for more than a decade. Probably millions of people died unnecessarily while it mouldered. Then a couple of people decided to work on the question, not of "what does this fungus do?" but on "are there any bacteriacidal substances worth turning into drugs?" searched the literature, found the Fleming paper, did pilots, found American factories to take on production, and made it happen. This took orders of magnitude more time and money, and it changed the world. But you probably don't know their names, do you?

It is true that discoveries or inventions of this type do not benefit end users unless someone works on technology transfer. The question is, how should this be organised and who should pay for it. It requires as well someone with an eye for what makes worthwhile applications. In HCI, that would require reasoning about what HCI ideas could make a real practical difference. There may not be academic rewards for this (no papers, no promotion). And there are probably no commercial rewards normally. Commercial reward depends on getting commercial funding, and that is unlikely to happen for new kinds of application. Penicillin was not a drug company project, but it may have started the current structure because it gave an example of how a drug could go from academic literature into profit making production: if you were to offer a drug company an idea of this kind now they would recognise it. There are no such precedents in HCI.

To get this to work in an HCI context might require:

  1. Fund people (probably academics) to research needs, not techniques first.
  2. Fund people then to develop application software for that need.
  3. Demonstrate its value to the target users in their lives (not just in demos or short lab. experiments).

After that, companies would probably build imitative software into their own product suites, and the idea would be launched into practice, with the takeup as evidence of value to society. It would take a lot of time and money, would not generate new ideas (only establish the transfer of an existing idea).

In summary: Fleming's academic research did benefit end users, but only after a delay of decades. Furthermore this benefit was wholly dependent on a different kind of work by others. On the one hand, funding researchers like Fleming is cheap and eventually brings rewards. On the other hand, who is attending to the rest of the chain of benefit-delivery and paying for it?

Another case: It is fundamentally unattractive on a short term view for industry to fund basic research, because everyone (their competitors) get to use it. A paradigm case of this (as Pavitt, 1996, mentions) is agriculture. A technological advance in crop varieties, pesticides, or farm machinery can do and has made big advances in productivity for all the farms in a country: but it is not in any one farm's interest to do this. Actually some of this research is now done privately, relying on the patent system to make it worthwhile for individual researchers / inventors rather than farmers.

Essentially, if the benefits of research are quantifiable, then industry is likely to fund it provided a patent system allows them to profit from inventions. If someone is convinced some research would be profitable, but can't make an argument to anyone else then the patent system allows mad inventors who turn out to be right to profit eventually. But mostly they can't afford this. But the essence of research is that you don't know what will be discovered until after you have discovered it. That is why publically funded research is necessary, but also why it's payoff is unpredictable. Furthermore, there is very substantial work to be done in discovering applications: that is, linking needs to what happens to have been discovered for other reasons.

As Whitby (1991) reminds us, this is closely related to the classic argument for universities by Newman.

The classic model: summary

The above discussed the classic model that the benefit to society of research is in direct applications. What is true is that a good argument for state or international funding of pure research in all areas including HCI is that things have been and presumably will be discovered that later lead to valuable applications. The essential feature is that research allows for, and indeed seeks out, surprises: discoveries that were not planned. Thus Fleming discovered penicillin in a botched experiment; an attempt to improve practical terrestial microwave communication led to the discovery of the universe's background microwave radiation, now taken as primary evidence for the big bang; and research in number theory, often seen as the purest of pure (i.e. useless) maths research, later came to underpin the encryption methods that are increasingly vital to the widespread use of the internet.

Pure research

But you cannot judge the value of research on these grounds on timescales much less than a century. You can't count patents or tell pure researchers to go out and make an unexpected discovery with vital commercial potential in another field. You just have to fund pure or curiosity-driven research, and it probably has to be state funded. This is a general argument, and will apply to HCI as well.

Applied research

Furthermore, developing those applications (from pure research) is a completely different business, requiring research of a different kind: applied research that begins by analysing or otherwise identifying practical problems to be solved, then tries to solve them. This is a quite different activity. Next comes an attempt to develop the arguments for it.

Technology transfer of techniques i.e. training

Probably a quite different story. To transfer a technique (e.g. rapid prototyping, design rationale) does not require fighting with an organisation about the product or what product could possibly be a worthwhile thing to bet the company on. It only requires infiltrating teams. Furthermore there are fairly soft ways in e.g. have a student do something in parallel with the team's normal practice and compare end products, feed back a report in the new notation etc.

It might be aided by HCI researchers developing ways of measuring benefits (what is a better design? a better design process?). Benefits to society presumably justified in terms of uptake of the techniques. In fact there may be considerable evidence of this kind already.

This aspect is supported by evidence that employers want to hire graduates with the latest training, as their way of tapping into the advancing research field. On this view, research (in the HCI area) is justified by allowing the researchers to keep on the cutting edge, and the benefit is in keeping the courses they teach up to date and a flow of trained students moving into industry. Evidence then would be the association of researchers with teaching, and of the uptake by industry of their students.

Researchers as living interfaces to the body of research knowledge

Kealey (1996) offers an argument I think interesting and important. In fact he was arguing for the abolition of state funding for research, but, without accepting his cause, I think his paper contains one important argument. He says that even though the published academic research literature is open to all (i.e. not classified or censored), in practice only researchers can use it. So (he argues) companies need to pay for research units so that they have their own people with access to it. (Furthermore Pavitt (1996) in a reply to Kealey essentially agrees with this point, when he too remarks on close links with academia in proportion to a company's own research strength, in order to obtain know-how not in the literature.) It is partly that it is a job to read the literature (it takes decades otherwise for published reviews and textbooks themselves to extract the few really important ideas and present them in a way that does not rely on having already read the rest of the literature). But it is even more because to find stuff out you need to talk to other researchers, and on the whole they aren't interested in talking to those who can't contribute in their turn. It's boring talking about your research to someone who has nothing to talk about either because they don't do it or because it's secret.

If you look at HCI conferences, this seems right. Quite a lot of industry people come, because they want to check out if there is anything new they should know about. But the conferences are not all that well organised for that. And there is limited informal talk with academics. Perhaps a more interesting "industry day" would feature alternate talks on "what you need to know" and "what we want to find out". Actual talks about research work in industry could go in other parts of the conference, as it is interesting in its own right.

On this view, transfer of anything from research to industry relies on these human channels. On the no-state-funding model, companies pay for research units even though they are very unlikely to generate patents that directly benefit the company, because it gives them a unit of people in contatct with world research and able to interpret it for the company, alerting it to the things that might be useful. (A prototypical "knowledge worker" job.) On a state-funding model, academics should spend some of their time as advisers, performing this function. They would need to spend some time in the company to pick up its needs and so to ask themselves the right questions, besides being available for questions asked of them.

Note how this is different from the idea of doing joint research or joint applications projects: it is giving advice, and creating a conduit from the research literature into other organisations.

Note too that hanging out together over long periods of time is probably very important. Research is, as it should be, unpredictable. It is not organised for applications. You have to build up a lot of common ground to find the worthwhile communications: neither side knows in advance the right questions and answers. Jon Oberlander's remarks at the HCI'97 panel about his experience seemed to support this. And several people made remarks about the gulf of understanding between industry and academic people: time and prolonged contact seem necessary, not precipitate attempts at common practical activities.

Other types of collaboration

  1. Joint research: probably not a good idea because goals are too different.
  2. Prolonged contact and advisory roles: good idea
  3. Academics doing case studies: a good kind of collaboration: it does evaluation which probably directly interests the company, and publishes it so more people benefit.
  4. Data sharing (Oberlander's favourite): mutual benefit and low conflict of interest.

Academics and problem areas

I think one implication is that each academic should become a specialist, not just in a research area, but in an application area. It takes a lot of effort to know an area well, and until you do you won't be in a good position to spot applications etc. Louis Pasteur is my role model here.

Applied research: summary

Developing socially valuable applications is a quite different type of activity from pure research, even though it may be best done by more or less the same people. It requires people who know or study what is wanted, but who also know the pure research literature which is organised quite differently; and who think about what the latter might offer the former. The example of penicillin gives one graphic example of the two roles. The argument about researchers as interfaces to the literature is another. It would be promoted by having pure researchers (whether academic or privately funded) spending some of their time on pure research, and some involved in industrial applications.

The specific nature of HCI

How do and don't these general arguments apply to HCI? Does it have any special features that mean different arguments should be developed for it?

HCI is an applied area, in fact an area defined by an application not a theory. So justifications and suggestions for interactions between research and practice may be different here than in many other areas of science. At first it might seem that it is an application of cognitive science and computing science (and perhaps sociology). That was the view of many in the 1980s. In my opinion that view has been pursued and found almost entirely to have failed. Applying existing pure theories has been tried and has almost always found to lead nowhere. For instance, most famously, the GOMS model attempts to use cognitive theories to predict user execution times. It can do this (at great effort), but in my view is still mostly an irrelevant failure because in only a few applications is it true a) that user exeuction time is an important aspect of overall usability b) users are observed to carry out a single predictable procedure: usually they are very variable both within and between users as to the procedure adopted. This is typical, as Landauer has commented. Psychological theories are true in the lab, and almost always turn out to be unimportant in practice because other factors swamp those lab. effects. Although it is less clear, I think the same is true in computer science. When HCI started up, software engineering was dominated by top down or "waterfall" models of design, and programming languages by functional theories. It is the area of HCI which, whether acknowledged or not, has moved software engineering into prototyping and iterative models, and underpinned the current fashion for object oriented languages.

If HCI was simply an application area, then it would not need its own pure research, but simply benefit from spinoffs from cognitive and computer science. But if, as I believe, the above view is correct, then it is the applications that are driving the theories by raising problems that existing theories cannot address. That means it is worth funding HCI research independently, although it also means we should especially promote those who attempt to develop theories purely of HCI, like the cognitive dimensions of Thomas Green, rather than applications of existing theories to HCI.

My own experience and views are of this kind. Firstly I believe attempts to apply prior theory from other fields have not proved useful. Secondly, following Landauer (1987, 1991), I believe that associated pure disciplines do make a big contribution, but from their techniques not their theories. Thirdly, the salient (if uncomfortable) feature of HCI is that it is driven by technology and invention, rather than driving it. GUIs and direct manipulation are phrases from the HCI field to describe what had already arrived, and which researchers were reacting to. The WWW is an even more striking example: it happened to HCI researchers, they didn't invent it. But in my view, we do not understand it: the role of HCI research is perhaps to try to understand the interaction of humans with computers and other machines that were invented largely without that understanding. This may seem embarrassing, but it is the position that biologists are in: studying what someone else invented, yet could be invented differently. Not to fund any academic research on it is simply to surrender more completely to an engineering driven by other concerns.

Thimbleby: public education

Harold Thimbleby offered a totally different kind of reason for supporting HCI research. Basically, HCI researchers should train the public to complain more about the quality of machine interaction i.e. public education and consciousness raising. So a direct social benefit, none of this helping industry. On the contrary, researchers should train consumers to harrass industry à la Ralph Nader, forcing them to raise standards (I mean, benefitting industry by training consumers to give them better feedback about their products).

I think there is a lot in this. It is a quite different kind of benefit; it has a plausible story relating research, tax payers, and industry; it relates to the fact that Microsoft and others really do get very few complaints, and so are not motivated to improve (unlike, say, the railways).

It might imply funding rather different research to Harold's. It should mean paying a lot more attention to social contexts of use; and doing a lot of basic (but interesting) empirical studies on what costs really are to users. Still, I guess Harold could try to promote attitudes like those in food hygiene, where tiny lapses that affect hardly anyone cause enormous uproar.

It should also be pointed out that although almost all the money and almost all the glory in medical research goes and always has gone into doctors and hi-tech remedies, but almost all the life saving historically has come from public health measures: sewage systems, clean mains water supply, public health education, vaccination. Thimbley may be more right than we would wish to recognise.

Extra points

Time scale

Many people remark on resistance to uptake of HCI ideas by companies. This does not make it different from other areas of science: long lead times are the norm. And there is a good reason for this: any commercial project must satisfy many constraints about time and resources, and the HCI is at most only one aspect. The point of academic research is to find what can be discovered when those other constraints are ignored; but applications are about finding cases where findings can be re-integrated with other constraints. This normally takes time. The start of projects not the middle is obviously a better time; when team members are being re-trained, not when they have been redeployed for a quick new job with no training time. Just like the stock market, commercial success in the short term has huge fluctuations unrelated to underlying quality, but in the long run it is the other way round: companies with some real competitive advantage tend to win out. If we are looking for benefits from HCI research, we can only expect a long time scale to show them.

Credit

However there may still be a problem in identifying credit. Because most practical results of benefit are the effect of many factors and constraints, how can we show that HCI research was an important one of those factors? If someone says they don't use HCI research, that doesn't prove they haven't benefitted: just that they are not aware of any such influence. But then most people getting on the plane for a holiday would not say that it is all thanks to Frank Whittle's research, even though it is.

Assigning credit for innovation is done badly, probably because it is hard to understand the interplay of all the contributions. Academic conventions make assigning some credit obligatory in science, but it is probably not done well there either. Winston (1986) shows just how complex the story is for a few major inventions such as the telephone.

Summary

In the end I have only dealt with 5 arguments.
  1. The pharmaceutical model of direct invention, which I reject as a useful justification for HCI research.
  2. The classical tricklethrough model which I support. It is hard to gather evidence of success here; and we must expect long time scales (and HCI is still very young). It justifies the support of pure research.
    2b) Researchers as human interfaces to research knowledge. I think this is important. In the end it is mainly another argument for supporting both pure and applied research.
  3. Training: researchers create methods, and train others in them. OK, but methods are only one kind of research, although an important one in HCI.
  4. Educating the public: Thimbleby's assertiveness training model, or a "public health" version of it.
  5. HCI is the study of technology it did not itself invent. We should get used to this, and think of it as a kind of cognitive biology: the study of someone else's designs.

References

Birch,N. (1997) "What's the use of HCI?" in HCI'97 conference companion (eds.) P.Thomas & D.Withers pp.8-10 (University of the West of England: Bristol)

Kealey,T. (1996) "You've all got it wrong" New Scientist vol.150 no.2036 29 June pp.22-26

Landauer, T.K. (1987) "Relations between cognitive psychology and computer system design" ch.1 pp.1-25 in Interfacing Thought (ed.) J.M.Carroll (MIT Press: Cambridge, Mass.).

Landauer, T.K. (1991) "Let's get real: A position paper on the role of cognitive psychology in the design of humanly useful and usable systems" ch.5 pp.60-73 in Carroll J.M. (ed.) Designing Interaction: psychology at the human-computer interface (Cambridge, UK.: Cambridge University press).

Pavitt,K. (1996) "Road to ruin" New Scientist no.2041 3 Aug. pp.32-35

Whitby,B. (1991) "Alice through the high street glass: A reply to John Barker" Intelligent tutoring Media vol.2 no.2 May pp.71-74

Winston, B. (1986) Misunderstanding media (London: Routledge and Kegan Paul.)