Last night a couple of us from work went to a presentation by Jonathan Harris at the Apple Store in SoHo. Jonathan talked about his interest in creating and finding stories, showing examples of his impressive data mining visualization projects like We Feel Fine, harvesting human feelings from blogs, and Universe , a project built off of Day Life technology to “reveal our modern mythology.” He previewed a piece that is currently up at the MoMa built with Processing, that visualizes information extracted from online dating site profiles, and attempts to find commonalities and connections within that dataset: the most common interests, first lines, closing lines, and potential matches.
While Harris is best known for his elegant visualizations of information from the internet, drawing connections and patterns, he sees more meaning in his recent work like Whale Hunt, and a yet to be completed project based on his 15 day trip to Bhutan. These works differ from his earlier pieces in that he is an active narrator and traveller, photographing, and interviewing his subjects directly while experiencing their environments. As such, this work is inherently more personal, which fits well with his professed egocentric world view.
Harris’s better known pieces, such as We Feel Fine, draw parallels to Learning to Love You More, a project by Harrell Fletcher & Miranda July. LTLYM is an on-going project in which participants submit “reports” completing “assignments” defined by Fletcher & July to the website. Assignments vary from the humorous “#57 Lipsync to shy neighbor’s Garth Brooks cover” to the self-reflective “#52 Write the phone call you wish you could have” and have been exhibited in musuems, galleries, and in print.
As a participatory art project, LTLYM’s character comes from both the constraints of the assignments Fletcher & July define for participants, and the reports submitted by participants. These constraints are much more transparent and recursive (#44 Make a LTLYM assignment”) than the constraints in Harris’s data-mining visualizations. But with Harris’s shift in interest away from data-mining projects towards a more personal narrative structure, approaching his work with the same method of defined constraints does little to draw out meaningful insights that speak to the human condition. Fletcher & July have succeeded in balancing their artistic voice with a system that opens up the creative process to its participants, while drawing out these type of deeper insights Harris seems to be searching for.
Note to Harris: it might not have been a good idea to tell a packed audience at the Apple Store that you don’t like technology and our reliance on the iPhone and other Apple products.
