Distracted Attention, or: Mindful Algorithms and the Algorithms of Mindfulness

• In Event: Attention! - I: Human/Machine Boundaries

Abstract

In a recent New Yorker article on the phenomenon of deep fakes, (Rothman 2018) the author reports a conversation he had over dinner with two authorities in image processing, who debated the deep roots of the fake-news phenomenon. “A huge part of the solution is dealing with perverse incentives on social media,” one of the interlocutors observed. “The entire business model of these trillion-dollar companies is attention engineering. It’s poison.” Indeed, the technological manipulation of attention entails a flurry of technical remedies, devised to help us identify the important things in life. Time management tools (Gregg 2018; Wajcman 2018) attempt to reinsert structure into days spent hyperventilating in front of home screens and dashboards; creatives resort to micro dosing to regain lost focus; the burnt-out and overworked attend highly commodified mindfulness trainings or delve into the latest findings of “the new science of sleep.” (Lane 2018)
The purported virtues of mindfulness and distraction, however, have not escaped the attention of the stakeholders of contemporary information processing technologies, who have already begun to scrutinise the value of distracted algorithms for intuitive computing and machine learning. (Bruder 2018) ‘Mindful’ algorithms promise to be restless and resilient at the same time as they wander through the data wastelands of our highly connected lives. My paper provides a deep reading of how attention is computationally re-conceived, analyses on how mind wandering algorithms reinforce global Northern understandings of distraction, and elaborates on attendant developments in (neuro)psychology.

Author

• Johannes Bruder, FHNW Academy of Art and Design