The New Relation Between Humans and Machines

“The experiences powered by machine learning are not linear or based on static business and design rules. They evolve according to human behaviors with constantly updating models fed by streams of data. Each product or service becomes almost like a living, breathing thing. Or as people at Google would say: ‘It’s a different kind of engineering’ – and a different kind of design.” – Fabien Girardin, Experience Design in the Machine Learning Era

For instance, Amazon explains Echo’s braininess as a thing that “continually learns and adds more functionality over time”. This description highlights the need to design the experience for systems to learn from human behavior.

Consequently, beyond considering the first contact and the onboarding experience, that type of product or service requires considerations on their use after 1 hour, 1 day, 1 year, etc. If you look at the promotional video of the Edyn garden sensor you will notice the evolution of the experience from creating new habits for taking care of a garden to communicating the unknown unknowns about plants, to convey peace of mind on the key metrics, and to guarantee time well spent with some level of watering automation.

That type of data product requires a responsible design that considers moments when things start to disappoint, embarrass, annoy or stop working or being useful. The design of the “offboarding experience” could become almost as important as the “onboarding experience”. For instance, allegedly a third of the Fitbit users stop wearing the device within 6 months. What happens to these millions of abandoned connected objects? What happens to the data and intelligence on the individual they produced? What are the opportunities to use them in different experiences?

There are new ways to imagine the relation after a digital break-up with a product. Digital services work on an increasingly vast ecosystem of things and channels but user data have a tendency to be more centralized. Think about the notion of portable reputation that allows people to use a service based on the relation measured with another service.

Looking a bit further into the near future, the recent breakthrough in Natural Language Processing, Knowledge Representation, Voice Recognition and Nature Language Production could create more subtle and stronger relations with machines. In a few iterations, Amazon Echo might start to be much more nurturing. A potential evolution that anthropologist Genevieve Bell foresees a shift from human-computer interactions to human-computer relationships in The next wave of AI is rooted in human culture and history:

“So the frame there is not about recommendations, which is where much of AI is now, but is actually about nurture and care. If those become the buzzwords, then you sit in this very interesting moment of being able to pivot from talking about human-computer interactions to human-computer relationships.” — Genevieve Bell

We have seen that algorithms are getting closer to our everyday lives and that data provide a context for an evolving relationship. The implications of that evolution require most intense collaboration between design and data science.