Consider a near-future reality of making things in which every digital production process, material technique and construction method is fully automated, seamlessly connected and remotely organised. Let’s call this Easy Production.
At the same time the sophistication of our interfaces to control technology starts to simplify another order of magnitude. Machine learning systems graduate from helpful gimmick to becoming fundamental middle management in the way we engage with technology. Interactions become sufficiently ‘intelligent’that our statements and actions are richly interpreted and complex decisions can be made on our behalf – in real time. Let’s call this Easy Communication.
Finally consider a software platform which has a fully semantic relationship to data. Services like Google Images or Facebook and it’s social models are attempts at realising this for specific types of data, but anticipate the extensions of these structures as they become entirely interoperable. Images, sounds, text, news, social profiles, videos, 3D models, networks, faces, products, voices, purchasing preferences, meta-data, time and space become fully interchangeable components. Like a seamless road-trip from Rainbow Road, Mario Kart to Liberty City, Grand Theft Auto – digital descriptions of objects, concepts or the relationships between them flow effortlessly across all platforms – in real time. Let’s call this Easy Data.
The fact that the current state of technology is not too far away from any of these three pitches being realised is fascinating. We must consider though the relationships that develop as all three paradigms begin to collide.
If Easy Communication controls Easy Production fed by Easy Data, our relationship with digital systems - and creative practices which engaged with them - may become entirely conversational. During such a conversation is it clear when are speaking and when we are listening? When does such a system start to talk about itself? When does it ask us for help?