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In this episode of the Radar Podcast, I chat with David Rose, an entrepreneur, MIT Media Lab instructor, and author of Enchanted Objects. We talk about which objects we should enchant, and how to avoid being overwhelmed by object communication and cognitive overload.
Rose also weighs in on the AI debate and outlines the four potential ways he sees the Internet of Things shaking out.
Here are a few snippets from our conversation:
I’ve been a fan of magic and of studying the tropes that magicians have used to control the emotional arc of a trick, for example, and I think enchantment, for me, sort of sets a high bar for designers to consider not just the mechanism of what’s happening, but also consider how people are engaged — and are people delighted? What’s their emotional reaction to whatever the new connectivity or new sensor or new display is that’s in one of these objects?
Those phenomenon of using light and pattern and texture are all pre-attentive — meaning your brain process them in parallel; it’s non-distracting; it happens in less than 250 milliseconds. That’s the design space for the best types of interactions with objects because they don’t tend to overwhelm you, and you don’t perceive them as being a cognitive load because they aren’t a cognitive load.
In the first part of [Enchanted Objects], I talk about four futures for our relationship to technology. The first one is black glass slabs, so it’s sort of the world of apps and the world of painting pixels on more and more surfaces … Another place we could locate technology in relationship to ourselves is by embedding it in and on ourselves, this is sort of the super power fantasy, the Ironman fantasy … Another place is social robots. Rather than putting it on us, we can just put it on them. … I think the fourth way for us to interact with tech is the most promising and most desirable, which is to put a little bit of AI in lots and lots of things. That’s what I call ‘enchanted objects.’
I think there’s an important distinction to be made around the difference between big AI and incremental AI.
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