MIMIC — Reid Hannaford

MIMIC

Interactive documentary. A collective portrait about the human cost of artificial intelligence.

In 2020, in the heart of the pandemic, I had the opportunity to take part in CPH:LAB, a talent development program designed to push the boundaries of documentary filmmaking. This year’s theme was Protopia; how technology might enable a better future.

Danielle Sheli Levy and I co-directed MIMIC, an interactive doc about our evolving relationship with AI. The project features an array of voices to capture how predictive algorithms affect people’s everyday lives.

MIMIC premiered at the Copenhagen International Doc Festival in April 2021.

Reflections

We are becoming more and more reliant on AI. Our societies are placing faith into a new kind of God, blindly trusting artificial intelligence to guide us. What are the long term ramifications as AI creeps into the most personal areas of our lives? When machine learning bleeds into identity and morality? When privacy is a distant memory? When algorithms govern how we live and we willingly obey?

Generations are being shaped and defined under the influence of these new technologies that we don’t even really understand. There’s a lot of misinformation and fear mongering about artificial intelligence and what it can do. In some ways it even has a life of its own. AI is one of the closest things we have to “magic.”

But, in early development, as we wrestled with how to approach a film about AI, we realized the story we wanted to tell wasn’t about the technology so much as it was about our humanity. We became entranced in conversations with people who knew nothing of artificial intelligence. Enthusiasts, ‘data nerds,’ technophobes, skeptics, and the people who encounter AI in their everyday life – by choice and not. Our aim is for people to be invigorated to challenge and proactively engage with the algorithms they confront, rather than forget what’s under the hood. MIMIC is an embrace of our collective curiosity to understand the things we don’t measure, but which we can observe.