Serious games

Serious games are serious about reality. Either in their modelling or their projection, serious games want to have players believe that they are playing a game when actually they are interacting with real world variables.

This becomes a dangerous way to process reality because your game-world interactions do not pass through the same process of deliberation as your outside-game-world actions. Your potential actions in both contexts are sandboxed in different environments.

This has bred laziness which has not allowed us to see our actions with enough distance to be able to reflect on the consequences of dealing with them like game-world actions.

Perception of our outside-game-world actions happens at the rate of seconds or even minutes for humans. Software can deal with changes in the value of variables at the rate of micro-seconds. Fluctuations in values that happen in micro-seconds can be tracked by code. The human mind can only track fluctuations that happen in seconds or minutes.

In some settings the cooperation between human and machine agents can be strategised. Humans can monitor the macro set of fluctuations and machines can monitor the micro set of fluctuations.

To allow the parallel processing of multiple sets of information, the macro limit can be set in the most comfortable parameters. Let's say for the sake of this argument, we set this macro limit to five minutes. Only fluctuations that occur every five minutes will be reported to human monitors now. Fluctuations that occur within five minutes will be reported only to machine monitors.

Now let's apply this setting to a specific world. A commonly known unstable world is the stock market. For now, we will only think in terms of the stock market.

So this stock market has two agents. Humans and machines. Human agents monitor macro changes and machine agents monitor micro changes.

Machine agents are instructed to respond in a way to the micro-monitoring data that profits are maximised. Humans are instructed to respond in a way to the macro monitoring data so that risk is minimised.

Machine agents maximise profits by taking massive bets on micro-fluctuations. This works most of the time.

Sometimes when the simultaneous chain-linking of the five minute windows of time happens, then there is a unmonitored chunk of time in the system when anything can happen. When bad news gets synched with this chain-linking, then the machine agents get fooled into taking bets on the down trend hoping in vain for it to correct itself. But it does not happen and there is a big crash.

Serious games, at least in their imagination, allow such crashes to happen.

We are not indicting the style of gaming or the school of thought. We are identifying scopes of error that can get amplified and great disjunctures. If models for machine-human cooperation have to be built, can they be less prone to error? Or do we have to recalibrate our conception of eventualities and possibilities and include in them an inherent facility of dealing with noise and error?

Is the future smooth and error-free or is it as bumpy, error-prone and unstable as the here-and-now?

Should serious games imagine themselves to have a facility to solve problems or a facility to imagine possible variations and alternate choices. Who should take serious games seriously?

The possibility for serious games to become confused for the serious business of making real choices and enacting real roles is a risk and is really an attempt only at fast-tracking the slow process of living life.

Serious games can also be treated as whole-scale fun and not be taken seriously at all? They could be modelled as a space for comedy to be able to laugh at the serious roles we are forced to play by the situations that we are placed in.