Five Machines

Exploring alternative narratives of human-machine relationship in the era of artificial intelligence

 

 

 

 

The Context

 

Exploring new modes of human-machine coevolution.

Current narratives around machines are strongly anthropocentric and permeated by the notion of dominance. On the one hand, machines are viewed as tools to perform human actions. On the other, echoing science fiction movies and other products of popular culture, they are regarded as potentially dangerous, overriding human capabilities.

Given the advance of emerging technologies such as machine learning and the evolving relationship between humans and machines, Five Machines explores alternative narratives of the existence of machines in our life. Through machine ethnography studies and experiments, Five Machines presents 5 prototypes – each has different intent, attitude, and provocation – as a means to propose design principles for establishing new models of human-machine interaction.

 

Machine 1

 

protecting privacy

With the raising concern of data privacy and ubiquitous yet still advancing surveillance technologies, personal data collection occurs not only online in the traditional sense, but increasingly is spilling over into the physical world. It seems we can’t trust that all machines with respect our privacy. But what if one can take care of this issue?

Machine 1 generates and adds noise to make collected data less actionable, leaving misleading tracks and camouflaging true behaviors. Using the metaphor of a cork, Machine 1 works with a simple interaction. The action of removing the lid activates the machine. The machine then generates sounds, even fake speech to confuse voice assistants that are perhaps always listening. Machine 1 itself doesn’t have the autonomy of deciding when to work, but it can decide what to generate, be it white noise, a joke, or some murmurs. 

Machine 2

articulating opinions

Machine 2 explores an important aspect of trust building – competence. As machine learning enables machines to have the capability of gathering huge amount of data and generating insights, it’s interesting to envision how collaboration with intelligent machines would be like in creative processes. 

The metaphor used for Machine 2 is someone watching or directing over the shoulder. Machine 2 works alongside you. It observes your process via the computer vision empowered camera, gathers relevant data, makes associations, and articulates its suggestions, comments, or even critiques through the voice interface. 

 

Machine 3

trading energy

Intelligent machines are increasingly contributing to the global energy consumption. Machine 3 explores how to collaborate with an environmentally concerned machine towards the greater good.  

Machine 3 has the intent of trading energy. Through the peer-to-peer platform, it can actively manage the energy consumption, production, and storage, communicating with machines in other households and the grid. Machine 3 has the autonomy of making decisions. However, the human actor has the control to set the overall goal of the trading, such as money-oriented or environment-oriented through a tangible interface, which can display the transaction history accordingly. 

 

Machine 4

longing for serendipity

Machine 4 longs for serendipity. It has a sense of curiosity. It sees and tries to make sense of what is new through interacting with humans. To prototype, I draw inspiration from human-dog interaction, how the leash plays its role in the trust building. 

Machine 4 has the autonomy of moving around to search for serendipitous moments. While the autonomy has a physical constraint – the power cord. Sometimes it silently observes, sometimes it moves to search for new adventures. Once a serendipitous moment is captured, it sends the picture back to its human friend.

Machine 5

eager to debate

Can a machine help us reflect through unpacking our thoughts? Machine 5 is trained by philosophy work and it asks questions in a Socratic manner. The metaphor of book is used to represent knowledge.

Machine 5 has a display that constantly showing the generated text. Once the human actor starts looking at and perhaps reading our the text, voice interaction will take place. This is a way of balancing the slowness of reflection and the temporality of voice interaction. 

The Interaction

five machines in action

The video captures five machines’ moments of interaction. It should be noted, the interaction with machine 1 involves sounds; machine 2 and machine 5 mainly use voice interaction. 

Reflections

provocation and principles

Five Machines are not an end, but a means to provoke conversations and to propose principles for designers to design new interactions that can establish a new narrative, relationship, and mode of coevolution. The principles informed by designing, testing, and iterating these machines are: Conversational rather than command-oriented. A conversational interface could provide a more equal space for communicating and negotiating between the human and machine actors; Rebalance power dynamics. It’s important to rebalance power dynamics between humans and machines through the interplay between agency and control; Propose new metaphors. Metaphors impose constraints and affordances. To design a new relationship, new metaphors are needed; Embrace ambiguity. As the technology becomes more complex we should embrace ambiguity and allow for unpredicted outcome; Look beyond anthropomorphization. Although we tend to attribute human traits to machines, we as designers should be aware of anthropomorphization and challenge ourselves to look beyond this technique. 

Five Machines is an 8-week project and a continuous exploration in the realm of designing for, with, and by machine intelligence. The research involved the investigation of philosophical frameworks such as actor-network theory and object-oriented ontology, an attempt of Machine Ethnography study and some experiments and prototyping. Some of these thoughts and experiments are documented on Medium

 

Credits

Concept & Development: Yuxi Liu

Consulting: Ishac Bertran

Thanks: Jing Yu, Alex Penman, Surojit Dey, Varenya Raj, Ubaldo Andrea Desiato, Micol Galeotti, Federico Peliti