John Hiles, unapologetic, reflects on SimHealth, what games can learn about cognition, and where Will Wright was wrong
When Maxis Software wanted to expand their line of Sim games to include professional simulation products, they tapped John Hiles and his computer modeling company Delta Logic. As the head of Maxis Business Simulations, and later when the division was spun off into the independent company Thinking Tools, Hiles pushed simulation games in new directions by combining the appealing structure and appearance of SimCity with researched, behavior-driven modeling. His team produced simulations for specific companies as well as general business and management games.
Hiles’s ideas met opposition wherever he went, both within Maxis and from clients and critics who warned how simulations with practical intent could misrepresent ideas. But Hiles maintains that his games and software had the potential to challenge orthodoxy and, at their best, inform the public discourse and help us reflect on our own values in ways where experts fail.
I spoke with John Hiles about his development process at Maxis and Thinking Tools, the controversy surrounding his work, and the future direction of simulation software. He shared stories about how multi-disciplinary learning influenced his approach to the genre – and shot back at his detractors.
(This interview was edited for length, clarity, and sensitivity about certain projects.)
The Obscuritory: From what I understand, before Maxis Business Simulations and Thinking Tools were things, you had a company called Delta Logic, and your background was in what you would call “complex adaptive system modeling.” And this was before you had adapted, sort of… the veneer, I guess is the word, of game systems. So what did your work entail before it developed into the game-focused evolution?
John Hiles: My background prior to joining Maxis was about 15 years of system software. I made a transition from college. I was in college and the Peace Corps and had a broad range of interests, and I got interested in programming. [I] was sort of self-taught on programming at first. Later on I did graduate work, but I was self-taught at first. A lot of people back then were.
And I went up the ladder as a system programmer, worked on aerospace projects, had a chance to work on Skylab, which was our first space station, and involved in computer graphics. And through computer graphics, there was a nascent interest in objects, software objects, started to reorganize the way people were thinking about computer graphics. That got me going on it. I was quite interested in that subject.
Then I moved up to Silicon Valley and joined a company right at the most interesting time of its history. This company was called Amdahl Corporation. And Amdahl competed with IBM. They sort of did the forbidden thing at that time, was to think that you could compete with IBM directly on mainframe computers. And we did! So I got in the software side supporting engineering and moved into management after a couple of years and the combination.
And at that point, another name started to surface in the company, for an operating system that could do things that IBM’s operating systems weren’t good at. And I met Ken Thompson from Bell Labs. He had been teaching at Berkeley, and one of his students came over to my department and introduced him. I ended up being a house guest back in New Jersey with Ken, and we started to lay out the plans for [a] mainframe version of Unix. And I was lucky enough to get three of his top apprentices to come out and build a team around them, and we produced the first mainframe version of Unix, and essentially gave Unix the ability to run on computers that were between 10 and 100 times more powerful than what it had been running on in the minicomputer world.
I got involved in microcomputer software and graphics and objects at Digital Research. I joined them after they had lost the battle with Microsoft over an operating system for the PC, so they were looking for something to sort of restart the company, and they brought me in as the VP of engineering. And we built a graphical user interface based on Xerox’s work in Smalltalk – very, very object-oriented, highly refined use of objects.
So I got a chance to sort of go out on my own and leave Digital Research behind, and the thing I wanted to do was to push this idea of objects that were adaptive and had some of the properties that we normally ascribe to intelligence, especially unconscious intelligence. That was sort of a turning point for me, when I started reading cognitive science and realized that over in computer science department, artificial intelligence means “Let’s teach computers how to reason. Let’s make them smart just like we are,” and that turned out to be largely be baloney, because the incredible parallel high-speed processes within the brain are mostly, they have to do with unconscious cognition and not highly self-conscious reasoning and logic and applications of abstraction, intentional applications of abstraction.
Instead, over in cognitive science, people started looking at things like “What’s the brain doing when two people are having a conversation?” And it turns out that there’s an incredible parallel set of processes that the unconscious brain is doing that sets the stage for the conscious mind in conversation. So for instance, putting the sound units together to recognize syllables and phonemes, putting the words together to recognize sentences, and at the same time projecting where the conversation could go next using the redundancy in language to anticipate where it’s going and to formulate possible responses. None of that yet has become conscious. It’s all taking place in parts of that brain that are not usually directly visible to the conscious mind. And I got very excited about this and said, “What if I learned more about these processes and bring some of them into software?”
And that’s where the Delta Logic days started. I wanted to have more intelligent and responsive software, using objects-based thought objects – really solid technology. But I was kind of going away from the work at the time on artificial intelligence, because it was really artificial conscious intelligence that they were trying to get right for computers. And in my opinion, in my humble opinion, that’s like saying, “Let’s have smooth gear-shifting before you’ve figured out how to make transmission.” And so saying that we’re gonna make computers really good at reasoning and making conscious decisions and implying that’s what our definition of what artificial intelligence is – without bringing over unconscious equivalents or representations of the unconscious processes – that’s just asking for trouble. It’s like saying “We’re gonna start building a 40-story building on the 14th floor.” And actually, when you compare them, unconscious and conscious, it’s more like saying “Let’s start building the 40-story building on the 36th floor.” Cause unconscious processes – cognitive processes – are really, really something.
So if you’re interested in that, one of the real nice sets of references on it – two of them in fact – are the books of Mark Turner and his teacher in linguistics. The people that have explored metaphors and the way allegory and metaphors work in linguistics are pretty good at communicating some of this unconscious process that intelligence is based on.
So for instance, one of the things that Mark Turner has developed is the idea that figurative speech, metaphors and the like, are not just pretty things that fit into poetry, that they are at the base, that they form the foundation for thinking. And that when you see a little kid, you know, hear a bedtime story, and in the next day, he says something like, “Hey daddy, this is just what like the cat did in the book!” he’s made a transformation and a projection using those properties of thinking and language. And we do that as a central action in thinking. We’re constantly taking a pattern and applying in another domain, and Mark Turner called that process “blending.” And so they’re very powerful process.
And I started thinking about how to apply that – and simultaneously with that, a company Maxis came along, and they said, “We have such a successful business that people are just demanding that we make more games and put the games on different platforms,” and they essentially bought my little company as a resource to help them do that, which was fine with me because it gave me a chance to work with Will Wright.
Having read some things Maxis said in the past, they had expressed – Will Wright had expressed – some skepticism about the idea that their simulation brand would have real-world applicable or even predictive value, and that they have had to turn down requests about that in the past. So I’m wondering: what was appealing about acquiring Delta Logic to them? Was it because it would just be a separate unit, or was it the way that you approached differently that was interesting? I’m curious about what made them make the leap from being dissuaded from that to embracing your company as part of their business.
Well, what they wanted from Delta Logic was the type of programming that could lead to a digital resources for them and ways to approach making the games easier to produce and easier to apply.
Now, I thought that Will was just a brilliant guy, and he still is, and if you’re doing any work in the area of computer games, you know that already. He’s a seminal person. But he was wrong about this. And I think the reason why I’ve stuck to the idea that, no, games and the real world are a lot more deeply connected then you may believe. And I’m very comfortable with arguing that side of the position.
And the reason is blending and the way our brain functions. It functions on the idea of metaphors and translating and projecting concepts from one domain into another. That’s what we have. We have a brain that’s really good at projecting what are sometimes referred to as mental spaces. Mental space in the game world – all the things that, you know, a game conversation at a conference would be talking about – we need to make it fun, we need to have this, we need to have that. And those form a mental space.
But another mental space, like how to run an oil refinery, is just right for projection from the game world into the oil refinery world. And that projection skill is the simplest… you hear a metaphor, and you say, “What an interesting way to look at that.” You start turning over the metaphor, and then you apply it to a new area. So Turner’s classic example of this is the type of stories that you see in The 1001 Nights. [Scheherazade] says, “I’ll keep him interested, I’ll tell him stories every night, but I won’t finish them. He’ll want to know what the end of that story was, and by the time he learns that, I’ll start another story.” Okay, so that projects into all sorts of other mental spaces, and that’s how it works. That’s how the brain has evolved functional centers that do that, that work with figurative language and are able to project.
So I looked at the problem, and I learned pretty quickly that that was a big belief with Will. And I didn’t… I love Will, he’s a great guy to work with, and he taught me lots and lots of things, but it didn’t phase me to have him believing that. I just know that the tools that are in the brain have evolved to project from one mental space into new mental spaces, and we call that process creativity. And he’s one of the most creative people I’ve ever worked with, so it’s odd that he didn’t get that, but he didn’t.
[NOTE: You can hear Will Wright’s take on projection and mental modeling in this interview from the special edition of SimCity 2000.]
Anyway, it was very easy to look at what was going on with SimCity – and I had the tremendous pleasure of sort of getting on the inside and looking at SimCity and how it worked and what the basic structures and notions were and how that game was put together by Will and the people around him – and I said, “What a great tool for projecting from the game world into the real world.”
So the things that we built… you know about SimHealth.
Which was really designed to help people think about the choices and to connect the choices that we had for health care to our values – as in the values that the democracy is based upon. So you had this four-point compass, and you had, right, justice on one side and liberty on the other. And you can’t have… you know, there’s a metaphor that says total justice for the sheep – as in plural sheep, a herd of sheep – is death to the wolves, and total liberty for the wolves is death to the sheep. So justice and liberty are constrained by each other, and we have to make a decision. In making a decision of policy, for instance, in health care, you have to set the strength of justice and the strength of liberty for your policy. And then on the other axis, you have other values that are working in dynamic tension with each other.
And what we showed with SimHealth was that the decisions that you used to shape your health care policy would put you on the map for those values – how much of this value, how much of that value. And so the Rush Limbaugh health care system would not help very many people who weren’t able to buy health care with their own resources, and the British or Canadian health care systems went way over in the other direction of justice. And it was then possible to do an analysis and say, “Well, what kind of disadvantages do they have in terms of liberty?” And that’s precisely how to look at the question, and that meant you were taking the notion with an expression that you find in games – you know, different controls and GUI-type tools – and then projecting it into actual health care policy. And just like the display indicators in a game’s interface give you a good view of resource management, this was a projection that said, “Let’s manage our application of values.”
One thing that I found was really interesting about the reception of the game, just reading through historical press at the time, was that there was sort of an issue with people accepting a lot of the contents at face value and not understanding what the strengths and the limitations of the software are. You put the assumptions forward, and there were a lot of disclaimers in the game and the manual explaining what the strengths of it were. There was – in the talk you gave at George Washington University in ’95 – you compared it to a hurricane simulation that would show what could happen when it hits but wouldn’t predict when a hurricane would hit, but there was still a lot of concern about people… I think it was the phrase used in the political journal The American Prospect – they called it the “abdication of authority” to the simulation. And it’s interesting because I feel like when you’re working with experts and such, they can understand the distinction, but when it’s for the public discourse, I feel like there’s often a tendency for people to kind of reduce it to a binary of “Well, this is accurate” or “This is made up.” And that was a hard enough problem they had with SimCity.
So I wonder… when you’re dealing with a general audience, how do you convey those strengths in a way that, in marketing, presentation, and so forth, without saying “Oh yeah, this game won’t be…” You have to show that it has value for modeling but isn’t, you know, won’t be predictive, won’t be able to forecast what will happen. I just wonder how you make that distinction in how you present the software when presenting it to the public.Well, look at what we just talked about, which is a pretty nice thing to put into a conversation that goes in the direction of some real problem. We were talking about health care, and I laid out how a projection of the dynamic tension between values can be associated with policy decisions. And it focuses your mind, then, on “Well that’s right! Why don’t we decide, why don’t we really have a conversation now about justice and liberty and how we’re going to balance them in a society, in a democracy?” and apply that to the policy question that we’re involved in thinking about.
It didn’t tell us what health care system to build. Certainly discussing the relation between justice and liberty doesn’t calculate the amount of money you should spend on improving Medicare. It doesn’t calculate the number of citizens that you want to cover who don’t have catastrophic disease protection in their insurance. None of that is present in the value projection. But when you project it and you keep your eye on the fact that you’re going to have to make tradeoffs between those values, it can guide your thinking.
Now, if you’re not thinking, then you’re just using the tool to either bullshit other people, make them think that you’re smart, or to just occupy your time and, you know, twiddle. So I’m not responsible for how people want to misuse human thought. I want to help them to do a better job of applying and projecting their concepts into the domain that they’re either arguing about or doing work in shaping policy craft. So I’m unapologetic about taking some of the wonderful things that are present in the world of games and translating them or projecting them into an area of real discourse and real social concern. And you’ll see when I talk about some of the other things that I’ve done, I’ve made a lot of people even more angry about the ideas of projection.
But it’s based on projection, and you always have the reality of the human brain to work with as a resource. Our brain is designed to project figurative language into all directions imaginable. And you know, the people – I think in some cases – people were threatened by the idea that laypeople could see a connection between the decisions in health care and the decisions that shaped our Constitution. I think that bothered some of them. They wanted it to stay policy wonk-y and the reserve of a small elite group that had command of the technical details, and that’s absolutely wrong!
What you want is an educated layperson that gets the idea and then projects it based on their own experience, and so: “Well I think it’s a good idea that we preserve liberty or that we extend justice,” that’s what we mean when we say “making a more perfect union.” We find new ways to do a better job of creating a society that has – not only preserves but extends – these key concepts. We want to project them. So I have no problem arguing and fighting with people that don’t like that idea.
Do you think that, especially over time, as games and software have proliferated more and everyone has, you know, app versions of whatever, do you think there’s become a better understanding that games have that potential? I think maybe it was different in ’92, ’93 as that technology was still developing, but do you think there’s a better sense now about what can be done with games and software – at least in the public sphere, understanding what things like SimHealth can do?
Well, it’s hard, and there’s not too many people that realize what games have to offer to the world of so-called “the real world.”
You see, I think that figure of speech is just as real as it can get for the brain – the ability to project figurative metaphorical concepts into new domains of discourse and domains of decision-making. I think that’s as real as it can get. And I wish that our whole education system did a better job of helping people to understand that that’s going on. We don’t want to teach people poetry so that they can grow up to the poets. We want to teach them poetry so that they can grow up to project the ideas that they’ve gained in their education, and then later in their early experiences, and to project those, powerfully, into new ideas and new plans and new programs. So, you know, I would like to see a lot better job than what we’re doing right now.
When you were working on the modeling software, you were often working with partners. You were making things – like when you did TeleSim, working with telecom companies – you were often working with companies that may not have been familiar with the sort of game-style software you were developing at the time, whether it was Harcourt Brace with The JusticeSystem, or I know you had mentioned, at least [you] were in the planning stages of a medical triage-type game with the Tripler Medical Center. And I’m curious about what the process was for taking their expertise and then translating that into a simulation that you programmed. Could you walk me through how that collaboration with those groups worked?
It’s backwards projection. So I just talked about taking key metaphorical concepts and projecting them into the real world, and for us to – that’s what our brain does – and for us to build SimRefinery or one of the other games meant that we did field research to find out how the technical details were related; what the variables were; what the incentives, goals, and objectives were; and how they were connected with the results of the process – and then project that back into the types of metaphorical concepts that you find in games, and then to use game-like interface conventions to put handles on them so that the player of the game could start to control and make decisions based on a projection into the real world.
So it’s reverse-engineering real world concepts to get them into a nice abstract set – I call it the mental space – and once you get that abstract mental space, then you sort of ladle in game interface convention and attach those levers and buttons and displays to the concepts in your mental space. Now it starts to look like the real world that you’re gonna imitate – that’s the imitative part. And then the action part is that those levers and controls and buttons that you’ve attached to the concepts that look like the real world system now give people a way to make decisions about their simulated real-world operation. And that’s the projection back into the real world mental space.
So it’s a metaphor. You have the abstract concept and the application of the abstract concepts in the real world. You take your abstract mental space and apply it with game-like interfaces, organize it, create a display that is believable, and then people in the real world can use that interface to manipulate the concepts and see the kinds of things that could happen in the real world – where the hurricanes can go.
And so… right, and you have a map, which is a metaphor – a map is a metaphor. And then let’s say you have a map of the Pacific and Atlantic Oceans and the coastline, and you say, well, here’s this meteorologist that learned that here are the paths that hurricanes use in the Atlantic, and they are born over here off the west coast of Africa, and they move along, spinning along, and they come up and hit the Antilles and Puerto Rico and Cuba, and they bend, go up along the US coast, and sometimes they hit on the coast in key places, and we have big bad hurricanes. Well, the map was the metaphor, and the understanding that meteorologists have produced is the sort of accoutrements and controls that – I’m skipping ahead, but – the map and the pathway of the hurricane are technical concepts that have been worked out by people who studied them, scientists and engineers. And what we want to do is take those principles and physical concepts, lay on game interfaces, and we can produce an interface that gave people the ability to anticipate and predict hurricanes and consequences of hurricanes that go a different place.
Now it turns out that many years later, I had graduate students in meteorology that were working with me, and we did that! They built models of prediction and whatnot that they were basing on concepts of meteorology, but we expressed it using this back-and-forth process of projection. And it was very, very powerful for them. And there were many other graduate projects where I was an advisor to master’s and PhD-level people, and that was one of the things I helped them understand to do. And the results were that their work communicated far better than the typical pro forma master’s degree thesis or PhD dissertation. They had support for the projections that a reader needs to make when they’re going through a dissertation, and those projections – that display, the game-like interfaces – made their work far more acceptable than the work that most other graduate students in their discipline.
Again, with working with the experts, I’m sure some of the companies were more in-tune with what you were doing, and I wonder what degree they were involved more with the day-to-day development of it. I feel like there may have been some who presented a broad charge to develop it, and then it sounds like your company did the research, but I wonder if there were times where they were more involved [it] as it was developing and looking at the model and making sure it met their understanding of the field as well as what you had researched.
Oh, absolutely. That was the field work that I mentioned. Our field work didn’t involve doing original chemistry or chemical engineering. When we did SimRefinery, our field work involved finding a genuine, brilliant, super-experienced guy who was patient enough to teach us all about oil refineries. And he was really, really key to it. All I did was field work. I was like a field anthropologist, out there, you know, talking to the guys that are in some tribe, and they know how to hunt in the African bush. So I got them to teach me about the work environment that they operate in and to confirm the generalizations and the abstractions that I projected back into the game space. So they were experts in the oil refinery space, and they taught me about oil refineries, and then I came up and said, “How about, these concepts, principles, and their relation?” and they say, “Oh, John, you screwed up, look at – this is wrong.” And I say, “Okay. Help me understand what to do about that.” They did, and they taught me.
And all I was doing was field work. I was asking questions and listening carefully. And I’d say, “What about this”… you know, I’d look at a photograph of their oil refinery, and I’d say, “What’s this big pile of sulfur doing here?” “Oh, well you weren’t paying attention to the chemistry, John, because we have units, very big powerful units, [that] take that sulfur. It used to be in the petroleum, and when you refine the petroleum, that’s what you get. You get this big pile of sulfur. If you’re operating your refinery efficiently, you do things with that sulfur. You don’t just throw it away, because first of all, that would be a great death for the environment, but you use it. How do you use sulfur? Well, you get industrial chemists, you say ‘Where’s sulfur used and what order does it have to be in, and how pure,’ and that’s another consideration for an output from our refinery.”
So that’s the sort of thing that they do, teaching me. I was doing field studies. And so we did that with SimHealth, we did that with each of the Thinking Tools projects, and then after I left Thinking Tools, I kept doing that.
We built another simulation called SimElection, and no one got to see because the sponsor, who I won’t name, was horrified when it came out! I made the mistake of bragging that SimElection would help people to understand that given enough money and a dog that looked like Rin Tin Tin, you could make Rin Tin Tin become the president. And they were horrified and shocked and said, “We can’t have our name associated with that!” And they actually had it destroyed, the entire stock, the entire product.
Oh my god.
No copies. No copies survived.
[NOTE: It is unclear whether SimElection was affiliated with Maxis Business Simulations or if that was a codename for a project at Thinking Tools.]
That was actually a question I had about some of the other things that happened under Maxis Business Tools. I’d seen mentions, just in some press sources, about titles that, it sounds, maybe either didn’t transpire or were very behind closed doors. I’d seen mentions about SimEnvironment, which may have been for EPA contractors, SimPower for the Electrical Power Institute, and SimSite, which was, I think, for military base closures? Did anything ever come from these? Were these things that were ever actually produced, or were they ideas that were just kicked around but not completed?
[NOTE: For this question, Hiles appeared to be discussing Maxis and Thinking Tools products interchangably.]
No, the telecommunications simulation went out. There was a simulation about projects, Project Challenge, and that not only went out, but it was used worldwide to teach project management. And again, the field research was with an expert. There was a member of that professional association, and she did a great job of teaching us project management according to the best recommendations of their certification and standard process. That’s still going. SimRefinery‘s still going. I understand that there are oil companies that use it to teach.
Wow, I had no idea.
Let’s see, what else, what other ones did you mention?
I mentioned SimEnvironment.
Yeah, we built that. And then, up in Canada – I went up to Canada and worked with a group of Canadians from across their country that came to the University of British Columbia to plan a game for Canadian schoolchildren about how to live in a sustainable city. And I taught them what I could about how you build such a game in the course of a one-week seminar. We had interactions back and forth, and then we went off and built it, and it went into use, widespread, across Canada.
[NOTE: This simulation, the Quasi-Understandable Ecosystem Scenario Tool developed by UBC’s Sustainable Development Research Institute, later evolved into the urban planning engagement software MetroQuest.]
I’m interested in the role experimentation played in these games, because I’ve found that, at least for me, the most engaging simulation games tend to be the ones that indulge your sense of curious and let you learn and reward you for kind of running the simulation off the rails. There was a wonderful education book [Engineering Play by Mizuko Ito] where they did studies where they had schoolchildren play the SimCity games, and they brought a kid in, and they explained to him, “Do you know SimCity?” and the child’s reaction was, “Yeah! That’s the game where you blow up the cities!” Which is funny, but it shows that you’re at least… you’re still learning from the model as you destroy it. You’re still seeing how the systems interact.
So I’m curious, the things that you developed under Maxis Business Simulations and Thinking Tools – they were a little less playful, I guess, than some of the other simulation titles, but I wonder if there were any intentional design choices to encourage people to experiment and to kind of run things off the rails and see what would happen if they just were curious about what happened if they prodded different parts of it.
Yeah, I have a story after Thinking Tools that applies directly to this, but in SimRefinery… the use of SimRefinery in programs for introducing people to oil refinery operations and learning about the choices and how they connect with the economics of the output, you, of course, in most of the training programs, they wanted people to do a good job of meeting their targets. But some of the more astute teachers said, “Let’s just get you started here by seeing if you can wreck the oil refinery, if you can abuse the inputs and the settings and essentially get fired.” And people… not all the teachers were smart enough to realize that that was an excellent way to tutorial for getting started with the game, and then to switch them into economic operations and compete with each other about who could solve a problem with the best results. But some of the teachers understood it real well, and the tool – the game – was agnostic. It would work for someone trying to ruin an oil refinery just as well as somebody trying to run it efficiently.
So going along to post-Thinking Tools work. You were involved in the Naval Post-Graduate School. You had mentioned some of the advising you had done with theses and doctorates. I had seen in 1998, you either advised or were involved in a proposal for a SimNavy-type series of products. When we spoke earlier, you had categorized this next stage as being… as opposed to bringing realistic models into games, of bringing game ideas into “non-games.” And so I’m wondering, if you could elaborate on what was involved after Thinking Tools and what you’ve done since then in that non-game field.
Well, there’s an intermediate step where I was interested in how simple a game you could build that would still support this… the player’s unconscious projection of concepts. And I did a demonstration game that was based on the operation – post-war operation – of Iraq, and with all the different factions and things, and I wanted to show kinetic actions, meaning killing people, and diplomatic actions, and to show, again, a set of principles that were interrelated and that I thought would be a good idea for people to understand a full gamut of choices that they had.
And so the participants in this SimIraq were the different political faction leaders, the Sunnis, the Shias, the non-government operations, the military – different people’s militaries, several militaries – and those were the players. And the range of actions that they all had with different amount of strength behind them, was diplomatic, [a] range of diplomatic choices ranging from very soft persuasion, sort of moral teaching, all the way up to threats. So there was an axis there that said, “How much choice does the recipient of your action have?” In kinetic operations, where you were applying kinetic force, meaning a rifle company with machine guns or a tank brigade, the people on the receiving end of that don’t have very much choice. If it’s street demonstrations, and carefully timed press releases, and things like that, then the people on the receiving end of that action have lots of choice. But you have much less control in terms of forcing them to do things, because it largely has to do with their well, and so you can see the values are starting to get connected.
[NOTE: Despite the name, this project was not developed under Maxis.]
Well that’s how I built this. You had a very sophisticated inner model. But then the displays and what not, meaning there were news programs and news bulletins and things like that – you could say, “I want to have an attack over here, blow up this,” and on the other hand, “I want to try to reach agreement with this faction, and together, have some kind of demonstration, a public demonstration, or something along those lines.” So you had a whole range of actions that were on the map, on this scale of values, that had to do with soft actions versus kinetic actions.
And so we built that. We took it to [an organization] and pulled people together to play the game. And it was enormously unpopular! We took two or three days to teach them how to play the game and then two days of playing the game, and among other things, there were academic experts on the Middle East who were there, and boy did they have a lot to say that was negative. “You are showing so-and-so” – and, you know, some leader of the Sunnis or leader of the Shiites – “you’re showing him with a range of choices that involve doing this and doing that, and I studied this guy for ten years, and I know that he would never do those things! He shouldn’t have those options. He shouldn’t have those buttons in your game because it’s misleading.” And, ahhhh, blah blah blah. And I just let him talk. We had a debriefing after one of the games, and he was going on about how stupid I was and how bad the game was and all this, and it’s misinformation, and it leads people to think that there’s rosy opportunities where there isn’t any. And so he went on for half an hour, laying it out.
That was on a Friday. It was a Friday afternoon debriefing after having the game for three days. Sunday morning, an email comes out, and I notice that it was addressed to all of the conference attendees, and it was to me, and it was from this academic. So when I saw it on my email list, I said, “Oh shit, he’s coming at me, he’s still coming after me!”
And he said, “Dear Professor Hiles, I was wrong. I told you that I studied this fellow and that he would never do these things. Well guess what. Friday, at his sermon, he told everybody what he wanted to do, and he decided to do one of the things in your game!” And he said, “It just hit us all blindsides. Everybody was confused, didn’t know what to do or think, and while I was analyzing it, I said ‘Wait a minute, this was in the game!'” [laughs]
To divert for a second, that’s such an interesting relationship, because you’ve mentioned the value of doing the field work and consulting the experts, but it also sounds like there’s a lot of cases where the expert opinion would lead the game astray. That just interests me. I wonder how you, when you were designing these things, chose, what opinions to consult and then what to eventually include in the products.
Well, look at it this way. I have a physics textbook here, and it’s got lots of chapters on forces. Lots and lots of chapters, different kinds of forces. That doesn’t mean that when engineers get together, and they’re going to build a car, that they’re going to use quantum dynamics, or that their car’s gonna be based on nuclear particles decaying. But those are concepts.
Well, never say never, but…
Yeah! And so what I said was, “Let’s abstract this.” There’s lots of choices that aren’t being used right now, but that doesn’t mean that they can’t be placed in a game. And I’ve gotta, I say, you know, you have to have a thick skin! You know the experts are gonna come at you, and then the engineer walks in and says, “What a crazy thing to say that one of the choices that you have when you build your car of the future is that it can use photons! Come on! Everybody knows that cars don’t use photons!”
“Yeah, but did you see the chapter where the photons are converted into electrons? Now do you want to say that you can’t use electrons to power a car? Because there are people that built streamlined, powerful locomotives in 1910 that used electrons.” He says, “Yeah, that may be true, but come on! Photons? How are you going to power a car with photons?”
Okay. These guys just flew around the world in an airplane that used photons. So if you abstract it, you don’t want… the field work that you do is to learn what the principles are and what the limitations are that practitioners currently believe. And if you’re going to try to do a game that allows people to project on a time axis into the future, you want to tear away some of those constraints and things that orthodoxy straight-jackets – in fact, I got in trouble with [a game for another client.] Their staff played it for a week, and boy did I get… you know, they brought out the blowtorches when it was time for all of the post-mortem discussions. And I just told them, “Do you want a game that says that you’re doomed to repeat orthodoxy for endless generations? Do you think that your opponents are going to be similarly tied to those constraints? Absolutely not! You better get with it!”
So SimIraq happened, the guy eventually apologized… the work after that, going towards the “non-game” stuff.
So that was sort of an intermediate phase when I first got to school. I wanted to see if I could build light games. What’s a light game? A light game is something that has [a] rich store of concepts and projections that it will support, but a very lightweight game, look, it doesn’t, you know, you don’t bring in artists and people designing layers and layers of art, sound, and all of those things, so it’s low-budget but really thoughtful. And I wanted to see what the limit was at that time – in the late 90s, the early 2000s – for a light game. And so we built several light games.
Now the next thing that I started thinking about was: why limit yourself to games? Why not have these agents doing their blending and controls over the… and the presence of the mental spaces out of which people create projections: why not use that to project, to have tools that help people understand what might happen. Given real streams of data that report what is happening, what if we look at the intentions and say, “What are some of the intentions that are capable of growing out of the stream of actual reporting?” And so we applied that. And we did tools that were game-like in the sense that they supported the fantasy and projection, but they were not games. They were tools that could be used with the interfaces that were present that allowed the agents in the game, the active objects, to speculate, and to base those speculations on facts and to give the users a little buzzer, and you could push the buzzer whenever you wanted to and say, “Hey, interface, why the hell did you do this? Explain yourself!” You push that button, and it would come back and explain to you that it would say, “Here’s the real… here’s the set of data, and these really happened, and I used this and this and this and this, and here’s a set of options and actions and combinations that have been spotted before, and I used this and this and this and this, and here is the basis for my predictions about the intent of this particular real-world object.”
And it’s based on work by Daniel Dennett that’s called “the intentional stance.” And it’s a very key concept, and [we] built tools that had intentional stances.
This is intriguing to me, because it seems in this case, the game elements you brought out were less like the trappings of the games, like advancing a level or something like that and more, again, like the projection side of it, like being able to look forward and being immersed in the simulation itself, which interests me in contrast to what other – there’s the term that’s going around now – serious games, what they would do, where they take game-y elements, like collecting points and such, and applying them towards an academic topic. There was a game recently that was supposed to teach how immune defense works, and it’s like an action game that uses actual scientific research on viruses. That seems like kind of the opposite direction. Whereas those are, you know, embracing their gameiness a little more, this seems to be embracing, again, the fantasy element of playing a game as opposed to some of its trappings. That interests me as, like, an alternate direction for serious games.
Right. Now there’s some very useful work that has come out of cognitive science and neurobiology. So with brain scans, you know, why are we putting people inside brain scanners? Cause we want to see how exposure to different stimuli excites or depresses blood flow in different parts of the brain. And by mapping that, we have found that there are modules, little regions in the human brain, that are there for purposes. They do things. And one of the little regions that does things is based on the projection of what other people do and what they may do or may not do. And one worker called this “mind reading.”
He didn’t mean mind reading as in Johnny Carson’s routine where he puts a hat on and, you know… it’s not that kind of mind reading. This is mind reading about: “See that guy over there? I think he’s about to do this!” That’s mind reading. And it’s using a part of the brain that is… it’s a genuine human part that’s been there for a long time, probably as long as we’ve been a social animal. And it’s there in the brain, and it is there for speculative projection of what another person’s intentions are.
So if you take Daniel Dennett’s concept of the intentional stance, and you take this idea of mind reading and put them together, you can build tools that make projections about what might happen, using data streams to understand the context, using field world to understand what people might do to use that data, and always have a button there that says, “Explain yourself. Why the hell did you say this was gonna happen or could happen?” and it comes back and shoots out an explanation, bar graph, that says, “Here’s the probabilities, here’s the Bayesian analysis of it.” And so, all of the hard-nose guys that want to make sure that you’re not faking people out, they’re satisfied, you know, up their ears with data, and they can come back and say, “Well, you ought to fine-tune this, you didn’t understand this variable,” and thank you very much, I’ll put it in the model tomorrow.
And… think of Nate Silver and his tools. What does he do? He says, “Here’s ten thousand or a hundred thousand looks at what might happen given these polls.” And people criticize him, and he invites them to criticize him. And they say, “Oh, what about this? You’ve overrated this?” and he says, “Oh, okay, I’ll put it in.” He’s learning how to make better projections, and the people that use these kind of tools have a support built into the tool that can help them to learn. And I really like tools. I like to think of tools that are adaptive and have a little nugget of cognitive function that allows them to read the intentions of either people – what Dennett’s intentional stance shows you is that you can also think in terms of normal, of real-world, natural things that have intentions also, even though they don’t have brains. So if you’re looking at a farmer’s field, and you can see the irrigation network, you can say that the crop has an intention, and given enough water and sunlight, fuel and a soil, that intention can be expressed, but it can be expressed in a lot of different ways, and the farmers or agricultural people play with those.
Okay, so… the idea of intelligent tools that have, that treat their world with intentional stance and use this idea of mind reading, is very, very powerful, and I think has tremendous prospects that go way beyond games. And there, there, I think, is an example of how you can project game-thinking into real-world tool building and tools that are adaptive and intuitive and predictive.
Now, one of the things to just kind of close that thought off. Imagine how I was thrilled to learn a couple of years ago that some people had trained their dogs to lie very, very still inside MRI scanners so that they could have brain scans without a lot of constraints. They found that there’s a center in the dogs’ brains that responded to the human voice. And they’d have people talk, and they could see the blood flow go right into that center, and that was there so that those dogs and their predecessors, back past the Ice Age, could get along with human beings – who are very dangerous and normally very unpredictable for animals. And these dogs had the advantage of being able to live in proximity with human beings and not get fooled all the time and have some insight into what the human beings wanted them to do or were about to do to them. And it led to the single most successful species outside of humans, in terms of populating the whole planet, that we know of. And then! While he’s writing the book, he found other people’s work that said, well, you know, when people have dogs, they have a part of their brain that’s especially active whenever the dog is interacting with them. There’s a part of the brain in humans that responds to that.
And so I thought, you know, I want software that has these types of responses built into it, so that during an operation of a system… I thought how wonderful it would be to build these in to your tools, so that the tools could anticipate what was going to happen, tell you what the prospects were, tell you what data they’d used to make those projections, and always give you a chance to understand what was behind their projection.
And then, what’s really, really, really fascinating to me is if you can build that for the tool to look out at the world that you’re investigating with your tool, you can also turn that around to build another system just like that that watches you while you’re using the tool. And it could watch you and a whole room full of other people, so if you’re monitoring, you know, if you’re monitoring air traffic, and you have ten controllers, not only is the tool telling you what this guy is intending to do and what that guy is intending to do, but they’re watching the operators, and they’re saying “Hey! John there is supposed to do something now because this guy is drifting off-course, and notice that John isn’t paying attention. Hey John, what the hell are you doing, wake up!” And the tool can not only connect the operator to the outside world that it’s trying to watch or monitor or operate on, but it also can watch the operator and say,”How effective is the operator? What are the operator’s intentions? Oh, they’re not within the boundaries of what good conduct or competence says they should be. He’s asleep, or he’s reacting slowly, or he’s paying attention to something else. Wake up, John! Get to work! Just think of a tool that could do that.”
Anyway, there’s a lot of work to do. [laughs] So there’s wonderful, wonderful things that happen when you project from [the] real world into games and equally, maybe even greater possibilities for tools that project from games out into the world of tools.