<html><head><meta http-equiv="Content-Type" content="text/html; charset=utf-8"></head><body style="word-wrap: break-word; -webkit-nbsp-mode: space; line-break: after-white-space;" class=""><div class="">Hi empyre--</div><br class=""><div><blockquote type="cite" class=""><div class="">On Nov 16, 2020, at 4:17 PM, Daniel Lichtman <<a href="mailto:danielp73@gmail.com" class="">danielp73@gmail.com</a>> wrote:</div><br class="Apple-interchange-newline"><div class=""><span style="caret-color: rgb(0, 0, 0); font-family: Helvetica; font-size: 12px; font-style: normal; font-variant-caps: normal; font-weight: normal; letter-spacing: normal; text-align: start; text-indent: 0px; text-transform: none; white-space: normal; word-spacing: 0px; -webkit-text-stroke-width: 0px; text-decoration: none; float: none; display: inline !important;" class="">how you see the relation between human and AI generated poetry? What happens when visual references that draw on our own, personal associations with (for example braided hair and snake curled around a stick in the entry for “curled”), are collected and remixed by the algorithm?</span><br style="caret-color: rgb(0, 0, 0); font-family: Helvetica; font-size: 12px; font-style: normal; font-variant-caps: normal; font-weight: normal; letter-spacing: normal; text-align: start; text-indent: 0px; text-transform: none; white-space: normal; word-spacing: 0px; -webkit-text-stroke-width: 0px; text-decoration: none;" class=""></div></blockquote></div><br class=""><div class="">Thanks for the thoughtful question, Dan.</div><div class=""><br class=""></div><div class="">This piece started with the list of relational terms you see on the wiki page. I was really drawn to the poetics of it, and the complication of its purpose. The list of terms is used by computer vision systems to describe relationships between objects in images, the the terms themselves were written by people and compiles into this dataset. </div><div class=""><br class=""></div><div class="">In the piece there’s this strange feedback loop--people define the things that the system can recognize as relationships, and the image search results tries to piece together a number of images that expresses that relation. The image search doesn’t actually use this type of image recognition system, so it looks for the relationship in metadata and we infer some other meaning in the collage of returned images. … which in turn is fluid and responding to the structure of the web via the search ranking algorithm. … so there are a number of layers of feedback between human input/activity and machine algorithms/ways of seeing. Ultimately the machine doesn’t know what a braid is, or even what an image is… it identifies patterns of pixels and metadata and supplies us with material from which we can try to make meaning.</div><div class=""><br class=""></div><div class="">You’re right to see the relationship between this and the types of image assemblages we encounter daily—instagram, twitter, image search, tiktok … they are all different types of algorithmically aligned images (based on our mostly passive input as behaviour and relational metadata (what Yuk Hui calls a “digital object)). With “I’m Feeling Lucky” we were really trying to expose and mine the poetics of metadata itself, as well as the resulting images that are often both strange and compelling.</div><div class=""><br class=""></div><div class=""><br class=""></div><div class=""><br class=""></div></body></html>