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The Trust Spectrum

Cooperative gameplay is growing in popularity. Based on extensive research, prototypes, and metrics, here is a design lens and framework for designing prosocial games that build trust between players.

Today I want to share with you a design framework that I’ve been working on for a couple of years now with a team at Google’s Advanced Technology and Projects (ATAP) group, led by Aaron Cammarata. We call it “The Trust Spectrum,” and it’s a practical design lens for designing multiplayer games, particularly ones involving co-operative play.

Background

Aaron led the charge on this project; he formed a group devoted to games that could enhance social connection, and asked me to help out on the game design mechanics side of things. He spent several months reading deeply into psychology and sociology to learn what the latest science said about human connections and social behavior.

In Aaron’s research on social structures, a few things popped out rather quickly.

 

  1. Play is fundamentally social. Science used to believe that the reason play existed across the entire mammal kingdom was because it served as a form of practice for skills. But it turns out that if you separate and prevent tiger cubs, say, from playing, they grow up quite able to hunt, fight, stalk, and so on (this is from a study by Tim Caro cited in Play: How it Shapes the Brain). They pick up these skills in other ways. What they don’t learn to do — and can never learn — is how to get along with others of their kind. (This doesn’t mean that play doesn’t help skill-building; there’s plenty of science on that too). Play is fundamental to learning social skills, and social skills are a key survival trait because they are an evolutionary benefit; teams working together can accomplish things that individuals working alone cannot.
  2. Humans have a pattern to their social relationships. Simply put, it falls into a pyramid: around 5 really intimate friends, 15 that are less so, around 50 that are more distant, and then an average total of around 150 social connections. This 150 figure is known as Dunbar’s Number, and to be clear, there’s a lot more nuance to it than “you can only have 150 friends.” (Christopher Allen has some excellent writing on misapprehensions of what Dunbar’s Number means, and I’ve discussed social graphing several times on my blog). This kind of increasing intimacy has been found by Dunbar himself in a large study of tens of millions of phone records; and also by those studying games, such as Nick Yee and Nic Ducheneaut in their examinations of guild subgroups in World of Warcraft.
  3. The variable here is trust. Human relationships progress through a set of stages which are pretty well understood. We start out tentative, trying to see what we have in common, then we gradually start relying on one another, and eventually come to trust one another. This is called “Social Penetration Theory,” by the way, and comes from actual experimental data. One thing that the data showed is that high trust doesn’t necessarily mean high trust in every facet of a life. Which leads to the fourth point:
  4. Trust is domain-specific. Just because you implicitly trust your trapeze partner with your life doesn’t mean you trust them with, say, your finances. Social Penetration Theory uses the words “breadth” and “depth” to refer to the spread of domains in which you might have trust versus the degree of trust you might have. It’s a mistake to assume that we might build a game that requires incredibly high trust in your teammates, and that therefore the players of the game will come to trust one another with, say, their children’s well-being. (In fact, a huge portion of the social mechanics that I curated into my talk of that title are in fact ways of dealing with a lack of domain trust).

I’ve written about trust at great length on my blog before. Most of it, however, was focused on the dynamics of large groups, the sorts of structures that emerge when trust is absent. The Trust Spectrum is about the opposite: it’s about trusted groups, and how you design for them.

Why? Because there’s a critical fifth finding, one that sits uncomfortably with the way we live our modern lives:

 


Virtual social bonds evolve from the fictional towards real social bonds. If you have good community ties, they will be out-of-character ties, not in-character ties. In other words, friendships will migrate right out of your world into email, real-life gatherings, etc.

-Koster’s Theorem

 

Now, I’ve worked for my whole adult life with online communities, and I know that deep trusting relationships definitely do form online. But they also, as is even enshrined in the Laws of Online World Design, migrate out from the virtual setting to the personal (it’s even called “Koster’s Theorem,” and no, it wasn’t me who named it). There are plenty of studies on this going back quite a ways. We’ve seen countless guilds start to have real life weddings, in person gatherings, and much more. You can climb the ladder of trust remotely, but to get to the most trusted relationships, and keep them alive, you need to meet in person.

OK, so how do we turn this into useful design rules?

As we were nearing the end of my time working with Google, Dan Cook published an article on Lost Garden (and later again on Gamasutra) that was the output of a workgroup at Project Horseshoe. It has enormous overlap with what you’re reading, uses many of the same scientific sources, and is very complementary — I highly recommend reading it. Even though Dan and I talk game design when we can and often say very similar things, we didn’t communicate at all on this topic! Dan’s checklist for “Game design patterns for building friendships” looks like this:


  • Proximity: Put players in serendipitous situations where they regularly encounter other players. Allow them to recognize one another across multiple play sessions.
  • Similarity: Create shared identities, values, contexts, and goals that ease alignment and connection.
  • Reciprocity: Enable exchanges (not necessarily material) that are bi-directional with benefits to both parties. With repetition, this builds relationships.
  • Disclosure: Further grow trust in the relationship through disclosing vulnerability, testing boundaries, etc.

All of these pieces of advice are dead on. Most of them are about moving from strangers to friends; in other words, moving from the “orientation” stages to “exploratory affective,” from outsider to within the 150. Dan has many examples of specific mechanics that accomplish these things, in his article. Our objective, however, was slightly different from the workgroup’s. We wanted not a catalog of mechanics, but something we could measure, ways to deeply break down a game and target it precisely at an audience. Ideally, you’d be able to assess a game, and give it almost a “trust rating,” or perhaps even a spread saying “this game works from this level of trust to this level.”

We did in fact arrive at tools to do that, but I am going to walk you through the process we used to get there, because it’ll probably help understand to it more deeply.

Trust and game mechanics

The goal here is to design games that fit with how humans actually interact socially. This means two things:

  • Designing multiplayer games that make sense for particular levels of trust. In other words, a game might fail if it calls for very high trust, but people tend to play it with strangers or in large groups. Think of the issues that so many players have with pick-up groups in MMOs; think of the endless articles out there on whether to play Diplomacy with your best friends.
  • Designing games that move people up the trust spectrum. You have to be cautious about this; we started out thinking that we were going to basically make people into better friends via game design, but because of the domain-specific nature of trust, we came to realize that you have to start by building trust within the game’s domain, and from there work outwards — doable, but a much more indirect process. Plainly put – no matter how good a MOBA team we make, I’m not giving you my credit card number. Most games won’t have domains that are broad enough to really shift people’s friendships around, and the ones that do are things that turn into serious commitments: tabletop RPG campaigns, MMOs, and sports teams. And above all, it makes very little sense to try to forcibly push a relationship up into the affective range of the spectrum; odds are excellent that the game is too narrow in breadth, and if the game is broad, that the players in question already have some deep relationships. You can’t ask them to drop a best friend to make room! In many cases, it might be better to instead design a game to work with the trust level that is already there. Or to effectively work on maintaining it. At the very least, the game should only invite intimacy rather than force it.

So, one would think we could just start putting game mechanics into tiers, and indeed that was how we started out, with a list of over 200 game mechanics that we tried to sort into buckets. We used “vulnerability” as our basic sorting function, since trust is driven so strongly by the level of implied risk if trust is broken. We also just started designing games that were meant to go at different levels.

It didn’t work.

The design problem with breaking game mechanics into trust levels is that virtually all games are actually played at all levels of this spectrum; meaning, you can play competitive games with friends or strangers, a bidding system or supply chain system may exist at any point on the spectrum, etc.

Games designed specifically to leverage elements from different levels of the trust spectrum do have different sorts of characteristics, though. So a more fruitful approach is to ask, what games cannot be played unless at a given level of intimacy or trust?

For example, games exist wherein there is an implicit level of trust that permits good play. All team coordination games are of this sort. In many, there are implicit trust maneuvers which can only be carried out by the assumption that the team member will be positioned correctly in order to assist. Examples might include doubles tennis, or volleyball, particularly two-person beach volleyball. “Blind” moves where trust alone completes the pass is one of the most common features of high end team play in sports: the initiator of the move passes the ball to empty air, and simply trusts that the receiver will move into position at the exact right time.

At the highest levels of trust exist games of complex coordination involving physical risk, such as that trapeze example, or certain forms of dance, where a failure in trust will result in a significant loss. Think of ice dancing and pairs figure skating, where you have bodies in motion on hard unforgiving surfaces, literally throwing your entire body weight onto someone else who is precariously balanced on moving sharp blades which sometimes swing close to your eye. Heck, sometimes you have to grab said moving sharp blade. Talk about trust falls!

Similarly, there are games where deep knowledge of other players’ thinking patterns and knowledge base permits better play. Examples include games of limited communication, such as charades or bridge. Limiting communication allows people who know each other well to communicate using shorthand of various sorts.

A lot of these games rely on rote “plays” or extensive repetitive training, so that players are used to being in their appropriate positions and roles. This is something that turned out to be a powerful idea – subgames where people have to practice certain maneuvers, but when connected with other players’ maneuvers, they result in a beautiful dance.

A different level of trust is that manufactured purely by fixed roles, where the game effectively implies a sort of economic exchange between players. Many team games have this sort of thing going on – one thinks of soccer, for example, or basketball. These do feature implicit trust moves and blind passes and the like so they stretch to high trust. But they are functional (meaning, you can play at all) at much lower trust levels, because the role is almost parallel play, and it’s a lower trust exchange. Examples here include stuff like throwing in the ball from the sidelines in soccer.

An additional interesting observation is that in practice, most advanced social mechanics are actually about working around a lack of trust among participants. For example, LARPing systems must involve elaborate consent mechanisms and conventions; large-scale economic play in MMOs involves contracts and supply chains and other such things that are meant to ameliorate the fact that trust does not, and cannot, exist at large scales.

The research stage

Using this as a rough rubric, then we started to classify some broad groups of mechanics as higher or lower levels of trust. As source data, we surveyed gamers of all sorts with the assistance of Quantic Foundry, including several types of digital gamers as well as tabletop players. Quantic Foundry is a market research company focused on gamer motivation. They have developed an empirical model of 12 gaming motivations based on research from over 350,000 gamers. We teased out similarities and differences in play patterns across casual games, lightweight party games, pen and paper RPGs, online multiplayer shooters, clan-style mobile games, MMORPGs, and more.

Some of the findings that are worth mentioning:

  • People are actually pretty wary of “games about trust,” at least when described that way.
  • There are clear gender differences in the survey data. Self-reported women are considerably more wary than men are.
  • Women prefer social fun to conflict, and men are the reverse. But these are not the inverse of one another. You might think that conflict with your friends and light social stuff would be contrary impulses, but they’re not. Social connection happens either way, and appeals either way.
  • But either way, cooperation is not a huge driver. In board games, for example, cooperation was dead last as the main motivation for playing, for men — and “winning” was on top. It wasn’t dead last for women, but the percentage of women interested in it as a primary driver was around the same (and they liked winning just as much, but they likes accessibility and social fun more).
  • People prefer, in order, competing with friends, co-op with friends, competing with strangers — and then, trailing way behind, co-operating with strangers. And the first three were clustered pretty tightly. Meeting new people was of less interest than deepening existing friendships, and trusting new people on your team was right out.
  • There’s a strong correlation between frequency of play and social motivations. The more interested in community, competition, excitement, and destruction a player was (using Quantic Foundry‘s terms here), the more likely the player was to want to play frequently.
  • 10-30 minutes was a sweet spot for game session length, but longer was fine. And 3-4 people was a sweet spot size.

There were also a few clusters that appeared that gave a new lens on “casual” and “hardcore” via social trust.

In digital we saw

  • A group that plays more hours, tilts male, tilts towards competitive and aggressive games, and that were more willing to try co-op with strangers.
  • A group that tilts female, and is just less enthused about social play in general, and tilts towards games where you complete things.

In analog we saw something with striking similarities and differences, which likely speaks to the culture of online games:

  • A group that plays often and regularly, often with strangers, tilts towards deeper strategy games and conflict, and start to tilt older.
  • A group that plays opportunistically and less often, likes social fun and luck, drift a little bit towards games that have only two players and have shorter sessions, and are less fond of social manipulation, deep strategy, and conflict.

Everyone likes immersion, everyone likes winning and being competitive.

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