2023-12-18 09:56:07 +00:00
|
|
|
|
<!DOCTYPE html>
|
|
|
|
|
|
<html xmlns="http://www.w3.org/1999/xhtml" lang="" xml:lang="">
|
|
|
|
|
|
|
|
|
|
|
|
<head>
|
|
|
|
|
|
<meta charset="utf-8" />
|
|
|
|
|
|
<meta name="generator" content="pandoc" />
|
|
|
|
|
|
<meta name="viewport" content="width=device-width, initial-scale=1.0, user-scalable=yes" />
|
|
|
|
|
|
<meta name="author" content="Ruben van de Ven, Ildikó Zonga Plájás, Cyan Bae, Francesco Ragazzi" />
|
|
|
|
|
|
<title>Algorithmic Security Vision: Diagrams of Computer Vision Politics</title>
|
|
|
|
|
|
<style>
|
|
|
|
|
|
/* div[data-custom-style='Body Text']{
|
|
|
|
|
|
background: rgba(255,255,255,.5)
|
|
|
|
|
|
} */
|
|
|
|
|
|
code {
|
|
|
|
|
|
white-space: pre-wrap;
|
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
|
|
span.smallcaps {
|
|
|
|
|
|
font-variant: small-caps;
|
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
|
|
span.underline {
|
|
|
|
|
|
text-decoration: underline;
|
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
|
|
div.column {
|
|
|
|
|
|
display: inline-block;
|
|
|
|
|
|
vertical-align: top;
|
|
|
|
|
|
width: 50%;
|
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
|
|
div.hanging-indent {
|
|
|
|
|
|
margin-left: 1.5em;
|
|
|
|
|
|
text-indent: -1.5em;
|
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
|
|
ul.task-list {
|
|
|
|
|
|
list-style: none;
|
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
|
|
.display.math {
|
|
|
|
|
|
display: block;
|
|
|
|
|
|
text-align: center;
|
|
|
|
|
|
margin: 0.5rem auto;
|
|
|
|
|
|
}
|
|
|
|
|
|
|
2023-12-19 07:35:00 +00:00
|
|
|
|
.anchor {
|
2023-12-18 14:28:52 +00:00
|
|
|
|
cursor: pointer;
|
2023-12-19 10:29:16 +00:00
|
|
|
|
/* TODO investigate scroll-snap-align: center; having scroll-snap-type: y proximity; on html*/
|
2023-12-18 14:28:52 +00:00
|
|
|
|
}
|
|
|
|
|
|
|
2023-12-18 09:56:07 +00:00
|
|
|
|
/*Filenames with code blocks: https://stackoverflow.com/a/58199362*/
|
|
|
|
|
|
div.sourceCode::before {
|
|
|
|
|
|
content: attr(data-filename);
|
|
|
|
|
|
display: block;
|
|
|
|
|
|
background-color: #cfeadd;
|
|
|
|
|
|
font-family: monospace;
|
|
|
|
|
|
font-weight: bold;
|
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
|
|
#collage {
|
|
|
|
|
|
position: fixed;
|
|
|
|
|
|
z-index: -1;
|
|
|
|
|
|
background-color: white;
|
|
|
|
|
|
left: 0;
|
|
|
|
|
|
top: 0;
|
|
|
|
|
|
right: 0;
|
|
|
|
|
|
bottom: 0;
|
|
|
|
|
|
overflow: hidden;
|
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
|
|
#collage_window {
|
|
|
|
|
|
position: absolute;
|
|
|
|
|
|
top: -1000px;
|
|
|
|
|
|
left: -1000px;
|
|
|
|
|
|
}
|
2023-12-18 14:28:52 +00:00
|
|
|
|
|
|
|
|
|
|
#collage_window svg {
|
|
|
|
|
|
position: absolute;
|
|
|
|
|
|
left: 0;
|
|
|
|
|
|
top: 0;
|
|
|
|
|
|
|
|
|
|
|
|
}
|
2023-12-19 07:35:00 +00:00
|
|
|
|
|
|
|
|
|
|
div[data-custom-style='Body Text'] p {
|
2023-12-18 14:28:52 +00:00
|
|
|
|
padding: 1em 0;
|
|
|
|
|
|
margin: 0;
|
2023-12-19 07:35:00 +00:00
|
|
|
|
background-color: rgba(255, 255, 255, 0.8);
|
|
|
|
|
|
}
|
|
|
|
|
|
|
2023-12-19 10:29:16 +00:00
|
|
|
|
.anchor {
|
2023-12-19 07:35:00 +00:00
|
|
|
|
position: relative;
|
|
|
|
|
|
}
|
|
|
|
|
|
|
2023-12-19 10:29:16 +00:00
|
|
|
|
.anchor.active:not(.playing)::before {
|
|
|
|
|
|
content: '⏵';
|
2023-12-19 07:35:00 +00:00
|
|
|
|
position: absolute;
|
|
|
|
|
|
width: 40px;
|
|
|
|
|
|
height: 40px;
|
2023-12-19 10:29:16 +00:00
|
|
|
|
background: gray;
|
2023-12-19 07:35:00 +00:00
|
|
|
|
left: calc(50% - 20px);
|
|
|
|
|
|
top: calc(50% - 20px);
|
|
|
|
|
|
vertical-align: middle;
|
|
|
|
|
|
line-height: 35px;
|
|
|
|
|
|
border-radius: 5px;
|
2023-12-19 10:29:16 +00:00
|
|
|
|
color: white;
|
2023-12-19 07:35:00 +00:00
|
|
|
|
}
|
2023-12-19 10:29:16 +00:00
|
|
|
|
|
|
|
|
|
|
.anchor.active:not(.playing):hover::before {
|
|
|
|
|
|
background: black
|
2023-12-19 07:35:00 +00:00
|
|
|
|
}
|
2023-12-19 10:29:16 +00:00
|
|
|
|
|
|
|
|
|
|
.anchor.playing:hover::before {
|
|
|
|
|
|
content: '⏸︎';
|
2023-12-19 07:35:00 +00:00
|
|
|
|
position: absolute;
|
|
|
|
|
|
width: 40px;
|
|
|
|
|
|
height: 40px;
|
2023-12-19 10:29:16 +00:00
|
|
|
|
background: black;
|
2023-12-19 07:35:00 +00:00
|
|
|
|
left: calc(50% - 20px);
|
|
|
|
|
|
top: calc(50% - 20px);
|
|
|
|
|
|
vertical-align: middle;
|
|
|
|
|
|
line-height: 35px;
|
|
|
|
|
|
border-radius: 5px;
|
2023-12-19 10:29:16 +00:00
|
|
|
|
color: white;
|
2023-12-18 14:28:52 +00:00
|
|
|
|
}
|
2023-12-18 09:56:07 +00:00
|
|
|
|
</style>
|
|
|
|
|
|
<link rel="stylesheet" href="paper.css" />
|
|
|
|
|
|
<script src="assets/wNumb-1.2.0.min.js"></script>
|
|
|
|
|
|
<script src="assets/annotate.js"></script>
|
|
|
|
|
|
<script>
|
|
|
|
|
|
const centerPoints = [
|
|
|
|
|
|
[2759, 6452],
|
|
|
|
|
|
[14335, 5364],
|
|
|
|
|
|
[5757, 10084],
|
|
|
|
|
|
[7137, 3869], // left in practice is -5746px;, top: -2988px;:
|
|
|
|
|
|
]
|
|
|
|
|
|
|
2023-12-18 14:28:52 +00:00
|
|
|
|
// test with FPR
|
2023-12-18 09:56:07 +00:00
|
|
|
|
const canvasCenter = [20077 / 2, 10331 / 2]
|
|
|
|
|
|
|
|
|
|
|
|
let scale = .5;
|
2023-12-18 10:50:20 +00:00
|
|
|
|
const sheet = new CSSStyleSheet
|
|
|
|
|
|
sheet.replaceSync(
|
|
|
|
|
|
`
|
2023-12-18 14:28:52 +00:00
|
|
|
|
:host{
|
|
|
|
|
|
--override-color: gray;
|
2023-12-18 10:50:20 +00:00
|
|
|
|
}
|
|
|
|
|
|
:host(.active){
|
|
|
|
|
|
--override-color: blue;
|
|
|
|
|
|
}
|
2023-12-18 14:28:52 +00:00
|
|
|
|
|
2023-12-18 10:50:20 +00:00
|
|
|
|
:host(.ending){
|
|
|
|
|
|
--override-color: blue;
|
2023-12-18 14:28:52 +00:00
|
|
|
|
}
|
|
|
|
|
|
div.controls{display:none !important;}`
|
|
|
|
|
|
);
|
2023-12-18 09:56:07 +00:00
|
|
|
|
|
2023-12-19 10:29:16 +00:00
|
|
|
|
function easeInOutSine(x) {
|
|
|
|
|
|
return -(Math.cos(Math.PI * x) - 1) / 2;
|
|
|
|
|
|
|
|
|
|
|
|
}
|
2023-12-18 09:56:07 +00:00
|
|
|
|
|
|
|
|
|
|
function easeInOutQuart(x) {
|
|
|
|
|
|
return x < 0.5 ? 8 * x * x * x * x : 1 - Math.pow(-2 * x + 2, 4) / 2;
|
|
|
|
|
|
|
|
|
|
|
|
}
|
2023-12-19 07:35:00 +00:00
|
|
|
|
function easeInOutBack(x) {
|
|
|
|
|
|
const c1 = 1.70158;
|
|
|
|
|
|
const c2 = c1 * 1.525;
|
|
|
|
|
|
|
|
|
|
|
|
return x < 0.5
|
|
|
|
|
|
? (Math.pow(2 * x, 2) * ((c2 + 1) * 2 * x - c2)) / 2
|
|
|
|
|
|
: (Math.pow(2 * x - 2, 2) * ((c2 + 1) * (x * 2 - 2) + c2) + 2) / 2;
|
|
|
|
|
|
|
|
|
|
|
|
}
|
2023-12-18 09:56:07 +00:00
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
let scroll_offsets = []
|
|
|
|
|
|
|
|
|
|
|
|
function calculateScrollOffsets() {
|
|
|
|
|
|
const anchorEls = document.getElementsByClassName('anchor');
|
|
|
|
|
|
|
|
|
|
|
|
offsets = []
|
|
|
|
|
|
|
|
|
|
|
|
for (let anchorEl of anchorEls) {
|
|
|
|
|
|
const align_pos = centerPoints[anchorEl.dataset.i];
|
|
|
|
|
|
const bbox = anchorEl.getBoundingClientRect()
|
|
|
|
|
|
const scroll_y = bbox.top + (bbox.height / 2) + window.scrollY;
|
|
|
|
|
|
offsets.push([scroll_y, anchorEl.dataset.i])
|
|
|
|
|
|
}
|
|
|
|
|
|
return offsets.sort((a, b) => a[0] - b[0]);
|
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
window.addEventListener('DOMContentLoaded', () => {
|
|
|
|
|
|
|
|
|
|
|
|
scroll_offsets = calculateScrollOffsets()
|
|
|
|
|
|
|
|
|
|
|
|
const windowEl = document.getElementById('collage_window')
|
2023-12-18 10:50:20 +00:00
|
|
|
|
const anchorEls = document.getElementsByClassName('anchor')
|
2023-12-18 14:28:52 +00:00
|
|
|
|
const playerEls = document.getElementsByTagName('annotation-player')
|
|
|
|
|
|
|
|
|
|
|
|
const paths = [document.getElementById('path1'), document.getElementById('path2'), document.getElementById('path3')]
|
|
|
|
|
|
paths.forEach((el) => el.style.strokeDasharray = Math.ceil(el.getTotalLength()) + 'px');
|
2023-12-18 10:50:20 +00:00
|
|
|
|
|
|
|
|
|
|
const lastAnchorEl = anchorEls[anchorEls.length - 1];
|
|
|
|
|
|
|
2023-12-18 14:28:52 +00:00
|
|
|
|
for (const anchorEl of anchorEls) {
|
|
|
|
|
|
anchorEl.addEventListener('click', ev => playerEls[anchorEl.dataset.i].annotator.playPause());
|
2023-12-19 07:35:00 +00:00
|
|
|
|
playerEls[anchorEl.dataset.i].annotator.addEventListener('play', ev => anchorEl.classList.add('playing'));
|
|
|
|
|
|
playerEls[anchorEl.dataset.i].annotator.addEventListener('pause', ev => anchorEl.classList.remove('playing'));
|
2023-12-18 14:28:52 +00:00
|
|
|
|
}
|
|
|
|
|
|
for (const player of playerEls) {
|
2023-12-18 10:50:20 +00:00
|
|
|
|
player.shadowRoot.adoptedStyleSheets = [sheet];
|
|
|
|
|
|
}
|
2023-12-18 09:56:07 +00:00
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
function updateScroll() {
|
2023-12-18 10:50:20 +00:00
|
|
|
|
// calculate the zooming & positioning of the plot
|
2023-12-18 09:56:07 +00:00
|
|
|
|
center_y = window.scrollY + window.innerHeight / 2
|
|
|
|
|
|
prev = null;
|
|
|
|
|
|
next = null;
|
2023-12-18 14:28:52 +00:00
|
|
|
|
step_idx = null;
|
|
|
|
|
|
for (let idx in scroll_offsets) {
|
|
|
|
|
|
const offset = scroll_offsets[idx]
|
2023-12-18 09:56:07 +00:00
|
|
|
|
if (offset[0] > center_y) {
|
|
|
|
|
|
next = offset
|
2023-12-18 14:28:52 +00:00
|
|
|
|
step_idx = idx;
|
2023-12-18 09:56:07 +00:00
|
|
|
|
break;
|
|
|
|
|
|
}
|
|
|
|
|
|
prev = offset
|
|
|
|
|
|
}
|
|
|
|
|
|
|
2023-12-19 10:29:16 +00:00
|
|
|
|
|
|
|
|
|
|
const sticky_dy = 200;
|
|
|
|
|
|
const intro_outro_dy = window.innerHeight + sticky_dy;
|
|
|
|
|
|
|
2023-12-18 14:28:52 +00:00
|
|
|
|
let source_pos, target_pos, source_scale, target_scale, source_color, target_color, source_x_offset, target_x_offset;
|
|
|
|
|
|
|
2023-12-19 07:35:00 +00:00
|
|
|
|
const x_column_width = window.innerWidth - document.body.getBoundingClientRect().width + 200; // for some reason the 200 is neccesary
|
2023-12-18 14:28:52 +00:00
|
|
|
|
const x_center_map = x_column_width / 2;
|
|
|
|
|
|
const x_center_column = document.body.getBoundingClientRect().left + document.body.getBoundingClientRect().width / 2;
|
|
|
|
|
|
|
|
|
|
|
|
const fit_scale = x_column_width / (canvasCenter[0] * 1.7)
|
2023-12-18 09:56:07 +00:00
|
|
|
|
|
2023-12-19 10:29:16 +00:00
|
|
|
|
let sticky_start = true;
|
|
|
|
|
|
let sticky_end = true;
|
|
|
|
|
|
|
2023-12-18 09:56:07 +00:00
|
|
|
|
if (prev === null) {
|
2023-12-19 10:29:16 +00:00
|
|
|
|
prev = [next[0] - intro_outro_dy, null]
|
2023-12-18 09:56:07 +00:00
|
|
|
|
|
2023-12-18 14:28:52 +00:00
|
|
|
|
source_scale = fit_scale
|
2023-12-18 09:56:07 +00:00
|
|
|
|
target_scale = .45
|
|
|
|
|
|
source_pos = canvasCenter
|
|
|
|
|
|
target_pos = centerPoints[next[1]]
|
|
|
|
|
|
|
2023-12-18 14:28:52 +00:00
|
|
|
|
source_color = 100;
|
|
|
|
|
|
target_color = 220;
|
|
|
|
|
|
|
|
|
|
|
|
source_x_offset = x_center_map;
|
|
|
|
|
|
target_x_offset = x_center_column;
|
|
|
|
|
|
|
2023-12-19 10:29:16 +00:00
|
|
|
|
sticky_start = false; // no sticky before first item
|
|
|
|
|
|
|
2023-12-18 09:56:07 +00:00
|
|
|
|
} else if (next === null) {
|
2023-12-19 10:29:16 +00:00
|
|
|
|
next = [prev[0] + intro_outro_dy, null]
|
2023-12-18 09:56:07 +00:00
|
|
|
|
|
|
|
|
|
|
source_scale = .45
|
2023-12-18 14:28:52 +00:00
|
|
|
|
target_scale = fit_scale
|
2023-12-18 09:56:07 +00:00
|
|
|
|
source_pos = centerPoints[prev[1]]
|
|
|
|
|
|
target_pos = canvasCenter
|
2023-12-18 14:28:52 +00:00
|
|
|
|
|
|
|
|
|
|
source_color = 220;
|
|
|
|
|
|
target_color = 50;
|
|
|
|
|
|
|
|
|
|
|
|
source_x_offset = x_center_column;
|
|
|
|
|
|
target_x_offset = x_center_map;
|
|
|
|
|
|
|
2023-12-19 10:29:16 +00:00
|
|
|
|
sticky_end = false; // no sticky after last item
|
|
|
|
|
|
|
2023-12-18 09:56:07 +00:00
|
|
|
|
} else {
|
|
|
|
|
|
source_pos = centerPoints[prev[1]]
|
|
|
|
|
|
target_pos = centerPoints[next[1]]
|
|
|
|
|
|
target_scale = .45
|
|
|
|
|
|
source_scale = .45
|
2023-12-18 14:28:52 +00:00
|
|
|
|
|
|
|
|
|
|
source_color = target_color = 220;
|
|
|
|
|
|
|
|
|
|
|
|
source_x_offset = target_x_offset = x_center_column;
|
|
|
|
|
|
|
2023-12-18 09:56:07 +00:00
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
|
|
|
2023-12-19 10:29:16 +00:00
|
|
|
|
const t_old = Math.min(1, Math.max(0, (center_y - prev[0]) / (next[0] - prev[0])))
|
|
|
|
|
|
const s = (center_y - prev[0] - (sticky_dy * sticky_start)) / (next[0] - prev[0] - (sticky_start + sticky_end) * sticky_dy);
|
|
|
|
|
|
const t = Math.min(1, Math.max(0, s))
|
|
|
|
|
|
// console.log(t_old, t)
|
|
|
|
|
|
t_ease = easeInOutSine(t)
|
|
|
|
|
|
// t_ease = easeInOutQuart(t) // use this if not snapping
|
|
|
|
|
|
|
|
|
|
|
|
let sticky_offset = 0;
|
|
|
|
|
|
if (s > 0 && s < 1) {
|
|
|
|
|
|
// scrolling from one item to the next
|
|
|
|
|
|
sticky_offset = t_ease * (sticky_start + sticky_end) * sticky_dy - (sticky_dy * sticky_start);
|
|
|
|
|
|
} else {
|
|
|
|
|
|
// sticky item
|
|
|
|
|
|
if (sticky_end && center_y > next[0] - sticky_dy) {
|
|
|
|
|
|
sticky_offset = sticky_dy - (center_y - next[0] + sticky_dy)
|
|
|
|
|
|
} else if (sticky_start && s <= 0) {
|
|
|
|
|
|
sticky_offset = ((center_y - prev[0]) / sticky_dy) * (- sticky_dy);
|
|
|
|
|
|
}
|
|
|
|
|
|
}
|
2023-12-18 09:56:07 +00:00
|
|
|
|
|
|
|
|
|
|
const dx = target_pos[0] - source_pos[0];
|
|
|
|
|
|
const dy = target_pos[1] - source_pos[1];
|
|
|
|
|
|
const ds = target_scale - source_scale
|
|
|
|
|
|
|
|
|
|
|
|
// console.log('twean from', source_pos, 'to', target_pos, 't', t_ease)
|
|
|
|
|
|
// console.log('twean scale', source_scale, 'to', target_scale, 't', t_ease)
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
scale = source_scale + t_ease * ds;
|
2023-12-18 14:28:52 +00:00
|
|
|
|
x_offset = (target_x_offset - source_x_offset) * t_ease + source_x_offset
|
|
|
|
|
|
x = -1 * (source_pos[0] + dx * t_ease) * scale + x_offset;
|
2023-12-19 10:29:16 +00:00
|
|
|
|
y = -1 * (source_pos[1] + dy * t_ease) * scale + window.innerHeight / 2 + sticky_offset;
|
2023-12-18 14:28:52 +00:00
|
|
|
|
|
|
|
|
|
|
const color = (target_color - source_color) * t_ease + source_color
|
|
|
|
|
|
// sheet.rules[0].style.setProperty('--override-color', `rgba(${color},${color},${color},0.7)`);
|
|
|
|
|
|
sheet.rules[0].style.setProperty('--disactive-path', `rgba(${color},${color},${color},0.7)`);
|
|
|
|
|
|
|
|
|
|
|
|
// draw the line
|
|
|
|
|
|
|
|
|
|
|
|
if (step_idx === null) {
|
|
|
|
|
|
// full paths
|
|
|
|
|
|
paths.forEach(el => el.style.strokeDashoffset = 0)
|
|
|
|
|
|
}
|
|
|
|
|
|
else {
|
|
|
|
|
|
// no paths
|
|
|
|
|
|
paths.forEach((el, idx) => {
|
2023-12-19 07:35:00 +00:00
|
|
|
|
if (idx >= step_idx) {
|
2023-12-18 14:28:52 +00:00
|
|
|
|
el.style.strokeDashoffset = Math.ceil(el.getTotalLength()) + 'px';
|
2023-12-19 07:35:00 +00:00
|
|
|
|
} else if (idx == step_idx - 1) {
|
2023-12-18 14:28:52 +00:00
|
|
|
|
// console.log('anim', el)
|
2023-12-19 07:35:00 +00:00
|
|
|
|
el.style.strokeDashoffset = Math.ceil(el.getTotalLength() - el.getTotalLength() * t_ease) + 'px';
|
2023-12-18 14:28:52 +00:00
|
|
|
|
} else {
|
|
|
|
|
|
el.style.strokeDashoffset = 0;
|
|
|
|
|
|
}
|
|
|
|
|
|
});
|
|
|
|
|
|
// paths.forEach((el) => stroke)
|
|
|
|
|
|
|
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
|
|
// console.log('x', x, 'y', y, 'scale', scale, 'color', color)
|
2023-12-18 09:56:07 +00:00
|
|
|
|
|
|
|
|
|
|
// console.log(x, y);
|
|
|
|
|
|
|
|
|
|
|
|
windowEl.style.transform = `scale(${scale})`
|
|
|
|
|
|
windowEl.style.left = `${x}px`
|
|
|
|
|
|
windowEl.style.top = `${y}px`
|
2023-12-18 10:50:20 +00:00
|
|
|
|
|
|
|
|
|
|
// calculate whether we're nearing the conlusion, and color accordingly
|
|
|
|
|
|
const last = Math.max(...Array.from(anchorEls).map((e) => e.getBoundingClientRect().bottom))
|
|
|
|
|
|
if (last < 0) {
|
2023-12-18 14:28:52 +00:00
|
|
|
|
for (const playerEl of playerEls) {
|
2023-12-18 10:50:20 +00:00
|
|
|
|
playerEl.classList.add('ending')
|
|
|
|
|
|
}
|
|
|
|
|
|
} else {
|
2023-12-18 14:28:52 +00:00
|
|
|
|
for (const playerEl of playerEls) {
|
2023-12-18 10:50:20 +00:00
|
|
|
|
playerEl.classList.remove('ending')
|
|
|
|
|
|
}
|
|
|
|
|
|
}
|
2023-12-18 09:56:07 +00:00
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
|
|
windowEl.style.transform = `scale(${scale})`
|
|
|
|
|
|
|
|
|
|
|
|
window.addEventListener('resize', (ev) => {
|
|
|
|
|
|
scroll_offsets = calculateScrollOffsets()
|
|
|
|
|
|
updateScroll()
|
|
|
|
|
|
})
|
|
|
|
|
|
|
|
|
|
|
|
window.addEventListener('scroll', updateScroll)
|
|
|
|
|
|
|
|
|
|
|
|
updateScroll()
|
|
|
|
|
|
|
|
|
|
|
|
let options = {
|
|
|
|
|
|
// root: document.querySelector("#scrollArea"), // viewport by default
|
2023-12-19 10:29:16 +00:00
|
|
|
|
rootMargin: `${-Math.floor((window.innerHeight - 10) / 2)}px 0px`, //"0px",
|
2023-12-18 09:56:07 +00:00
|
|
|
|
threshold: 0,
|
|
|
|
|
|
};
|
|
|
|
|
|
|
|
|
|
|
|
let observer = new IntersectionObserver((entries, observer) => {
|
|
|
|
|
|
entries.forEach((entry) => {
|
|
|
|
|
|
index = entry.target.dataset.i;
|
|
|
|
|
|
console.log(entry)
|
2023-12-18 14:28:52 +00:00
|
|
|
|
if (index >= playerEls.length) {
|
2023-12-18 09:56:07 +00:00
|
|
|
|
return;
|
|
|
|
|
|
}
|
|
|
|
|
|
playerEl = windowEl.children[index];
|
2023-12-18 10:50:20 +00:00
|
|
|
|
if (entry.isIntersecting) {
|
2023-12-19 07:35:00 +00:00
|
|
|
|
entry.target.classList.add('active');
|
2023-12-18 09:56:07 +00:00
|
|
|
|
playerEl.classList.add('active')
|
|
|
|
|
|
} else {
|
2023-12-19 07:35:00 +00:00
|
|
|
|
entry.target.classList.remove('active');
|
2023-12-18 09:56:07 +00:00
|
|
|
|
playerEl.classList.remove('active')
|
2023-12-19 07:35:00 +00:00
|
|
|
|
if (typeof playerEl.annotator.paused !== 'undefined' && !playerEl.annotator.paused) {
|
2023-12-18 14:28:52 +00:00
|
|
|
|
console.log('pause', playerEl.annotator, playerEl.annotator.paused)
|
|
|
|
|
|
playerEl.annotator.pause()
|
|
|
|
|
|
}
|
2023-12-18 09:56:07 +00:00
|
|
|
|
}
|
|
|
|
|
|
})
|
|
|
|
|
|
}, options);
|
|
|
|
|
|
|
2023-12-18 10:50:20 +00:00
|
|
|
|
// const anchorEls = document.getElementsByClassName('anchor');
|
2023-12-18 09:56:07 +00:00
|
|
|
|
for (const anchorEl of anchorEls) {
|
|
|
|
|
|
observer.observe(anchorEl)
|
|
|
|
|
|
}
|
2023-12-19 07:35:00 +00:00
|
|
|
|
// console.log(anchorEls)
|
2023-12-18 09:56:07 +00:00
|
|
|
|
// .forEach(el => observer.observe());
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
// console.log(anchorEl.dataset.title);
|
|
|
|
|
|
// const toSelect = typeof anchorEl.dataset.title == 'undefined' || anchorEl.dataset.title == 'none' ? null : frameEl.contentWindow.getIdForTitle(anchorEl.dataset.title);
|
|
|
|
|
|
// // navItemEl.hash url-encodes
|
|
|
|
|
|
// // let targetEl = document.getElementById(navItemEl.attributes.href.value.substr(1));
|
|
|
|
|
|
// // let wrapperEl = targetEl.parentNode;
|
|
|
|
|
|
// let intersectionObserver = new IntersectionObserver(function (entries) {
|
|
|
|
|
|
// console.log(entries);
|
|
|
|
|
|
// // If intersectionRatio is 0, the target is out of view
|
|
|
|
|
|
// // and we do not need to do anything.
|
|
|
|
|
|
// // if (entries[0].intersectionRatio <= 0) {
|
|
|
|
|
|
// // // navItemEl.classList.remove('active');
|
|
|
|
|
|
// // } else {
|
|
|
|
|
|
// // if (toSelect === null) {
|
|
|
|
|
|
// // frameEl.contentWindow.mapGraph.triggerReset();
|
|
|
|
|
|
// // // frameEl.contentWindow.mapGraph.deselectNode();
|
|
|
|
|
|
// // // frameEl.contentWindow.mapGraph.resetZoom();
|
|
|
|
|
|
// // } else {
|
|
|
|
|
|
// // frameEl.contentWindow.mapGraph.triggerSelect(toSelect);
|
|
|
|
|
|
// // // frameEl.contentWindow.mapGraph.selectNode(node);
|
|
|
|
|
|
// // }
|
|
|
|
|
|
// // // navItemEl.classList.add('active');
|
|
|
|
|
|
// // }
|
|
|
|
|
|
|
|
|
|
|
|
// });
|
|
|
|
|
|
// // start observing
|
|
|
|
|
|
// intersectionObserver.observe(anchorEl);
|
|
|
|
|
|
// }
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
// const linkEls = document.getElementsByClassName('maplink');
|
|
|
|
|
|
// for (let linkEl of linkEls) {
|
|
|
|
|
|
// linkEl.addEventListener('click', (ev) => {
|
|
|
|
|
|
// const toSelect = typeof linkEl.dataset.title == 'undefined' || linkEl.dataset.title == 'none' ? null : frameEl.contentWindow.getIdForTitle(linkEl.dataset.title);
|
|
|
|
|
|
|
|
|
|
|
|
// if (toSelect === null) {
|
|
|
|
|
|
// frameEl.contentWindow.mapGraph.deselectNode();
|
|
|
|
|
|
// frameEl.contentWindow.mapGraph.resetZoom();
|
|
|
|
|
|
// } else {
|
|
|
|
|
|
// const node = frameEl.contentWindow.mapGraph.graph.nodes.filter(n => n.id == toSelect)[0]
|
|
|
|
|
|
// frameEl.contentWindow.mapGraph.selectNode(node);
|
|
|
|
|
|
// }
|
|
|
|
|
|
|
|
|
|
|
|
// })
|
|
|
|
|
|
// linkEl.addEventListener('mouseover', (ev) => {
|
|
|
|
|
|
// const toSelect = typeof linkEl.dataset.title == 'undefined' || linkEl.dataset.title == 'none' ? null : frameEl.contentWindow.getIdForTitle(linkEl.dataset.title);
|
|
|
|
|
|
// if (toSelect) {
|
|
|
|
|
|
|
|
|
|
|
|
// const node = frameEl.contentWindow.mapGraph.graph.nodes.filter(n => n.id == toSelect)[0]
|
|
|
|
|
|
// frameEl.contentWindow.mapGraph.hoverNode(false, node);
|
|
|
|
|
|
// }
|
|
|
|
|
|
|
|
|
|
|
|
// })
|
|
|
|
|
|
// linkEl.addEventListener('mouseout', (ev) => {
|
|
|
|
|
|
// const toSelect = typeof linkEl.dataset.title == 'undefined' || linkEl.dataset.title == 'none' ? null : frameEl.contentWindow.getIdForTitle(linkEl.dataset.title);
|
|
|
|
|
|
// if (toSelect) {
|
|
|
|
|
|
// const node = frameEl.contentWindow.mapGraph.graph.nodes.filter(n => n.id == toSelect)[0]
|
|
|
|
|
|
// frameEl.contentWindow.mapGraph.endHoverNode(node);
|
|
|
|
|
|
// }
|
|
|
|
|
|
|
|
|
|
|
|
// })
|
|
|
|
|
|
|
|
|
|
|
|
// }
|
|
|
|
|
|
|
|
|
|
|
|
});
|
|
|
|
|
|
|
|
|
|
|
|
</script>
|
|
|
|
|
|
</head>
|
|
|
|
|
|
|
|
|
|
|
|
<body>
|
|
|
|
|
|
<header id="title-block-header">
|
|
|
|
|
|
<h1 class="title">Algorithmic Security Vision: Diagrams of Computer
|
|
|
|
|
|
Vision Politics</h1>
|
|
|
|
|
|
<p class="author"><em>Ruben van de Ven, Ildikó Zonga Plájás, Cyan Bae,
|
|
|
|
|
|
Francesco Ragazzi</em></p>
|
|
|
|
|
|
<p class="date">December 2023</p>
|
|
|
|
|
|
</header>
|
|
|
|
|
|
<div id='collage'>
|
|
|
|
|
|
<div id="collage_window">
|
|
|
|
|
|
<!--data-poster-url="annotation-BIXG4VTL.svg"-->
|
|
|
|
|
|
<annotation-player style="position:absolute;width:3243px; height:2635px;left:514px;top:6329px;"
|
|
|
|
|
|
data-url-prefix="assets" stroke="blue" data-crop='whole'
|
|
|
|
|
|
data-annotation-url="annotation-F19O9PGE.json"></annotation-player>
|
|
|
|
|
|
<annotation-player style="position:absolute;width:11867px;height:2753px;left:3905px;top:4333px;"
|
|
|
|
|
|
data-url-prefix="assets" stroke="blue" data-crop='whole'
|
|
|
|
|
|
data-annotation-url="annotation-XYGE65SB.json"></annotation-player>
|
|
|
|
|
|
<annotation-player style="position:absolute;width:4450px;height:3250px;left:5056px;top:7081px;"
|
|
|
|
|
|
data-url-prefix="assets" stroke="blue" data-crop='whole'
|
|
|
|
|
|
data-annotation-url="annotation-NKOUGNWE.json"></annotation-player>
|
|
|
|
|
|
<annotation-player style="position:absolute;width:2547px; height:2710px; left:5690px;top:1584px;"
|
|
|
|
|
|
data-url-prefix="assets" stroke="blue" data-crop='whole'
|
|
|
|
|
|
data-annotation-url="annotation-J4AOBZCJ.json"></annotation-player>
|
|
|
|
|
|
<annotation-player style="position:absolute;width:2952px; height:5043px;left:0;top:0;"
|
|
|
|
|
|
data-url-prefix="assets" stroke="blue" data-crop='whole'
|
|
|
|
|
|
data-annotation-url="annotation-BIXG4VTL.json"></annotation-player>
|
2023-12-18 14:28:52 +00:00
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
<svg height="10331.54" version="1.1" viewBox="61.650009 -1201.8501 20077.92 10331.539" width="20077.92"
|
|
|
|
|
|
id="svg1410" xml:space="preserve" xmlns="http://www.w3.org/2000/svg"
|
|
|
|
|
|
xmlns:svg="http://www.w3.org/2000/svg">
|
|
|
|
|
|
<defs id="defs4">
|
|
|
|
|
|
<marker style="overflow:visible" id="marker39470" refX="0" refY="0" orient="auto-start-reverse"
|
|
|
|
|
|
markerWidth="5.3244081" markerHeight="6.155385" viewBox="0 0 5.3244081 6.1553851"
|
|
|
|
|
|
preserveAspectRatio="xMidYMid">
|
|
|
|
|
|
<path transform="scale(0.5)"
|
|
|
|
|
|
style="fill:context-stroke;fill-rule:evenodd;stroke:context-stroke;stroke-width:1pt"
|
|
|
|
|
|
d="M 5.77,0 -2.88,5 V -5 Z" id="path39468-6" />
|
|
|
|
|
|
</marker>
|
|
|
|
|
|
</defs>
|
|
|
|
|
|
<g id="layer1">
|
|
|
|
|
|
<path
|
|
|
|
|
|
style="fill:none;stroke:#00f;stroke-width:5;stroke-linecap:butt;stroke-linejoin:miter;stroke-dasharray:20, 40;stroke-dashoffset:0;stroke-opacity:1;marker-end:url(#marker39470)"
|
|
|
|
|
|
d="M 3153.037,4991.1869 C 3627.9651,3806.502 10134,2080.0386 13783.189,4095.2221" id="path1" />
|
|
|
|
|
|
<path
|
|
|
|
|
|
style="fill:none;stroke:#00f;stroke-width:5;stroke-linecap:butt;stroke-linejoin:miter;stroke-dasharray:20, 40;stroke-dashoffset:0;stroke-opacity:1;marker-end:url(#marker39470)"
|
|
|
|
|
|
d="M 14473.211,4826.0987 C 14487.638,6297.2524 9146.0135,8823.4797 5997.8383,8868.5177"
|
|
|
|
|
|
id="path2" />
|
|
|
|
|
|
<path
|
|
|
|
|
|
style="fill:none;stroke:#00f;stroke-width:5;stroke-linecap:butt;stroke-linejoin:miter;stroke-dasharray:20, 40;stroke-dashoffset:0;stroke-opacity:1;marker-end:url(#marker39470)"
|
|
|
|
|
|
d="M 5562.416,8572.101 C 5561.5237,7310.7009 7556.3295,6911.6966 7557.7371,3111.5328"
|
|
|
|
|
|
id="path3" />
|
|
|
|
|
|
</g>
|
|
|
|
|
|
</svg>
|
|
|
|
|
|
|
2023-12-18 09:56:07 +00:00
|
|
|
|
<!--data-poster-url="annotation-F19O9PGE.svg"-->
|
|
|
|
|
|
<!--data-poster-url="annotation-XYGE65SB.svg"-->
|
|
|
|
|
|
<!--data-poster-url="annotation-NKOUGNWE.svg"-->
|
|
|
|
|
|
<!--data-poster-url="annotation-J4AOBZCJ.svg"-->
|
|
|
|
|
|
</div>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<section id="part1">
|
2023-12-19 07:35:00 +00:00
|
|
|
|
<p> .... this is a demo to showcase how the chronodiagramming looks like in its interactive form. Please note
|
|
|
|
|
|
that this demo of the interface is not compatible with mobile devices ...</p>
|
2023-12-18 09:56:07 +00:00
|
|
|
|
<section id="managing-error-from-the-sublime-to-the-risky-algorithm" class="level2">
|
|
|
|
|
|
<h2>3. Managing error: from the sublime to the risky algorithm</h2>
|
|
|
|
|
|
<div data-custom-style="Body Text">
|
|
|
|
|
|
<p>Our third emerging figuration concerns the place of the error. A
|
|
|
|
|
|
large body of literature examines actual and speculative cases of
|
|
|
|
|
|
algorithmic prediction based on self-learning systems (Azar et al.,
|
|
|
|
|
|
2021). Central to these analyses is the boundary-drawing performed by
|
|
|
|
|
|
such algorithmic devices, enacting (in)security by rendering their
|
|
|
|
|
|
subjects as more- or less-risky others (Amicelle et al., 2015: 300;
|
|
|
|
|
|
Amoore and De Goede, 2005; Aradau et al., 2008; Aradau and Blanke, 2018)
|
|
|
|
|
|
based on a spectrum of individual and environmental features (Calhoun,
|
|
|
|
|
|
2023). In other words, these predictive devices conceptualize risk as
|
|
|
|
|
|
something produced by, and thus external to, security technologies.</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Body Text">
|
|
|
|
|
|
<p>In this critical literature on algorithmic practices, practitioners
|
|
|
|
|
|
working with algorithmic technologies are often critiqued for
|
|
|
|
|
|
understanding software as “sublime” (e.g. Wilcox, 2017: 3). However, in
|
|
|
|
|
|
our diagrams, algorithmic vision appears as a practice of managing
|
|
|
|
|
|
error. The practitioners we interviewed are aware of the error-prone
|
|
|
|
|
|
nature of their systems but know it will never be perfect, and see it as
|
|
|
|
|
|
a key metric that needs to be acted upon.</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Body Text">
|
|
|
|
|
|
<p>The most prominent way in which error figures in the diagrams is in
|
|
|
|
|
|
its quantified form of the true positive and false positive rates, TPR
|
|
|
|
|
|
and FPR. The significance and definition of these metrics is stressed by
|
|
|
|
|
|
CTO Gerwin van der Lugt (Diagram 6). In camera surveillance, the false
|
|
|
|
|
|
positive rate could be described as the number of fales positive
|
|
|
|
|
|
classifications relative to the number of video frames being analyzed.
|
|
|
|
|
|
Upon writing down these definitions, van der Lugt corrected his initial
|
|
|
|
|
|
definitions, as these definitions determine the work of his development
|
|
|
|
|
|
team, the ways in which his clients — security operators — engage with
|
|
|
|
|
|
the technology, and whether they perceive the output of the system as
|
|
|
|
|
|
trustworthy.</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Figure">
|
|
|
|
|
|
<div class="anchor" data-i="0" style="height:2.3in"></div>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Caption">
|
|
|
|
|
|
<p>Diagram 6. Gerwin van der Lugt corrects his initial definitions of
|
|
|
|
|
|
the true positive and false positive rates, and stresses the importance
|
|
|
|
|
|
of their precise definition.</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Body Text">
|
|
|
|
|
|
<p>The figuration of algorithmic security vision as inherently imprecise
|
|
|
|
|
|
affects the operationalization of security practices. Van der Lugt’s
|
|
|
|
|
|
example concerns whether the violence detection algorithm developed by
|
|
|
|
|
|
Oddity.ai should be trained to categorize friendly fighting
|
|
|
|
|
|
(<em>stoeien</em>) between friends as “violence” or not. In this
|
|
|
|
|
|
context, van der Lugt finds it important to differentiate what counts as
|
|
|
|
|
|
false positive in the algorithm’s evaluation metric from an error in the
|
|
|
|
|
|
algorithm’s operationalization of a security question.</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Body Text">
|
|
|
|
|
|
<p>He gives two reasons to do so. First, he anticipates that the
|
|
|
|
|
|
exclusion of <em>stoeien</em> from the category of violence would
|
|
|
|
|
|
negatively impact TPR. In the iterative development of self-learning
|
|
|
|
|
|
systems, the TPR and FPR, together with the true and false
|
|
|
|
|
|
<em>negative</em> rates must perform a balancing act. Van der Lugt
|
|
|
|
|
|
outlines that with their technology they aim for fewer than 100 false
|
|
|
|
|
|
positives per 100 million frames per week. The FPR becomes indicative of
|
|
|
|
|
|
the algorithm’s quality, as too many faulty predictions will desensitize
|
|
|
|
|
|
the human operator to system alerts.
|
|
|
|
|
|
</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Body Text">
|
|
|
|
|
|
<p>This leads to van der Lugt’s second point: He fears that the
|
|
|
|
|
|
exclusion of <em>stoeien</em> from the violence category might cause
|
|
|
|
|
|
unexpected biases in the system. For example, instead of distinguishing
|
|
|
|
|
|
violence from <em>stoeien</em> based on people’s body movements, the
|
|
|
|
|
|
algorithm might make the distinction based on their age. For van der
|
|
|
|
|
|
Lugt, this would be an undesirable and hard to notice form of
|
|
|
|
|
|
discrimination. In developing algorithmic (in)security, error is figured
|
|
|
|
|
|
not merely as a mathematical concept but (as shown in Diagram 6) as a
|
|
|
|
|
|
notion that invites pre-emption — a mitigation of probable failure — for
|
|
|
|
|
|
which the developer is responsible. The algorithmic condition of
|
|
|
|
|
|
security vision is figured as the pre-emption of error.</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Figure">
|
|
|
|
|
|
<div class="anchor" data-i="1" style="height:6in"></div>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Caption">
|
|
|
|
|
|
<p>Diagram 7. By drawing errors on a timeline, van Rest calls attention
|
|
|
|
|
|
to the pre-emptive nature of error in the development process of
|
|
|
|
|
|
computer vision technologies.</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Body Text">
|
|
|
|
|
|
<p>According to critical AI scholar Matteo Pasquinelli, “machine
|
|
|
|
|
|
learning is technically based on formulas for error correction” (2019:
|
|
|
|
|
|
2). Therefore, any critical engagement with such algorithmic processes
|
|
|
|
|
|
needs to go beyond citing errors, “for it is precisely through these
|
|
|
|
|
|
variations that the algorithm learns what to do” (Amoore, 2019: 164),
|
|
|
|
|
|
pushing us to reconsider any argument based on the inaccuracy of the
|
|
|
|
|
|
systems.</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Body Text">
|
|
|
|
|
|
<p>The example of <em>stoeien</em> suggests that it is not so much a
|
|
|
|
|
|
question if, or how much, these algorithms err, but how these errors are
|
|
|
|
|
|
anticipated and negotiated. Thus, taking error as a hallmark of machine
|
|
|
|
|
|
learning we can see how practices of (in)security become shaped by the
|
|
|
|
|
|
notion of mathematical error well beyond their development stages. Error
|
|
|
|
|
|
figures centrally in the development, acquisition and deployment of such
|
|
|
|
|
|
devices. As one respondent indicated, predictive devices are inherently
|
|
|
|
|
|
erroneous, but the quantification of their error makes them amenable to
|
|
|
|
|
|
"risk management.”</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Body Text">
|
|
|
|
|
|
<p>While much has been written about security technologies as a device
|
|
|
|
|
|
<em>for</em> risk management, little is known about how security
|
|
|
|
|
|
technologies are conceptualized as objects <em>of</em> risk management.
|
|
|
|
|
|
What happens then in this double relation of risk? The figure of the
|
|
|
|
|
|
error enters the diagrams as a mathematical concept, throughout the
|
|
|
|
|
|
conversations we see its figure permeate the discourse around
|
|
|
|
|
|
algorithmic security vision. By figuring algorithmic security vision
|
|
|
|
|
|
through the notion of error, risk is placed at the heart of the security
|
|
|
|
|
|
apparatus.
|
|
|
|
|
|
</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
</section>
|
|
|
|
|
|
</section>
|
|
|
|
|
|
<section id="con-figurations-of-algorithmic-security-vision-fragmenting-accountability-and-expertise"
|
|
|
|
|
|
class="level1">
|
|
|
|
|
|
<h1>Con-figurations of algorithmic security vision: fragmenting
|
|
|
|
|
|
accountability and expertise</h1>
|
|
|
|
|
|
<div data-custom-style="Body Text">
|
|
|
|
|
|
<p>In the previous section we explored the changing <em>figurations</em>
|
|
|
|
|
|
of key dimensions of algorithmic security vision, in this section we
|
|
|
|
|
|
examine how these figurations <em>configure</em>. For Suchman, working
|
|
|
|
|
|
with configurations highlights “the histories and encounters through
|
|
|
|
|
|
which things are figured <em>into meaningful existence</em>, fixing them
|
|
|
|
|
|
through reiteration but also always engaged in ‘the perpetuity of coming
|
|
|
|
|
|
to be’ that characterizes the biographies of objects as well as
|
|
|
|
|
|
subjects” (Suchman, 2012: 50, emphasis ours) In other words, we are
|
|
|
|
|
|
interested in the practices and tensions that emerge as figurations
|
|
|
|
|
|
become embedded in material practices. We focus on two con-figurations
|
|
|
|
|
|
that emerged in the interviews: the delegation of accountability to
|
|
|
|
|
|
externally managed benchmarks, and the displacement of responsibility
|
|
|
|
|
|
through the reconfiguration of the human-in-the-loop.</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<section id="delegating-accountability-to-benchmarks" class="level2">
|
|
|
|
|
|
<h2>Delegating accountability to benchmarks</h2>
|
|
|
|
|
|
<div data-custom-style="Body Text">
|
|
|
|
|
|
<p>The first configuration is related to the evaluation of the error
|
|
|
|
|
|
rate in the training of algorithmic vision systems: it involves
|
|
|
|
|
|
datasets, benchmark institutions, and the idea of fairness as equal
|
|
|
|
|
|
representation among different social groups. Literature on the ethical
|
|
|
|
|
|
and political effects of algorithmic vision has notoriously focused on
|
|
|
|
|
|
the distribution of errors, raising questions of ethnic and racial bias
|
|
|
|
|
|
(e.g. Buolamwini and Gebru, 2018). Our interviews reflect the concerns
|
|
|
|
|
|
of much of this literature as the pre-emption of error figured
|
|
|
|
|
|
repeatedly in relation to the uneven distribution of error across
|
|
|
|
|
|
minorities or groups. In Diagram 8, Ádám Remport draws how different
|
|
|
|
|
|
visual traits have often led to different error rates. While the general
|
|
|
|
|
|
error metric of an algorithmic system might seem "acceptable," it
|
|
|
|
|
|
actually privileges particular groups, which is invisible when only the
|
|
|
|
|
|
whole is considered. Jeroen van Rest distinguishes such errors from the
|
|
|
|
|
|
inherent algorithmic imprecision in deep machine learning models, as
|
|
|
|
|
|
systemic biases (Diagram 7), as they perpetuate inequalities in the
|
|
|
|
|
|
society in which the product is being developed.</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Figure">
|
|
|
|
|
|
<div class="anchor" data-i="2" style="height:4in"></div>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Caption">
|
|
|
|
|
|
<p>Diagram 8. Ádám Remport describes that facial recognition
|
|
|
|
|
|
technologies are often most accurate with white male adult faces,
|
|
|
|
|
|
reflecting the datasets they are trained with. The FPR is higher with
|
|
|
|
|
|
people with darker skin, children, or women, which may result in false
|
|
|
|
|
|
flagging and false arrests.</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Body Text">
|
|
|
|
|
|
<p>To mitigate these concerns and manage their risk, many of our
|
|
|
|
|
|
interviewees who develop and implement these technologies, externalize
|
|
|
|
|
|
the reference against which the error is measured. They turn to a
|
|
|
|
|
|
benchmark run by the American National Institute of Standards and
|
|
|
|
|
|
Technology (NIST), which ranks facial recognition technologies by
|
|
|
|
|
|
different companies by their error metric across groups. John Riemen,
|
|
|
|
|
|
who is responsible for the use of forensic facial recognition technology
|
|
|
|
|
|
at the Center for Biometrics of the Dutch police, describes how their
|
|
|
|
|
|
choice for software is driven by a public tender that demands a "top-10"
|
|
|
|
|
|
score on the NIST benchmark. The mitigation of bias is thus outsourced
|
|
|
|
|
|
to an external, and in this case foreign, institution.</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Body Text">
|
|
|
|
|
|
<p>We see in this outsourcing of error metrics a form of delegation that
|
|
|
|
|
|
brings about a specific regime of (in)visibility. While a particular
|
|
|
|
|
|
kind of algorithmic bias is rendered central to the NIST benchmark, the
|
|
|
|
|
|
mobilization of this reference obfuscates questions on how that metric
|
|
|
|
|
|
was achieved. That is to say, questions about training data are
|
|
|
|
|
|
invisibilized, even though that data is a known site of contestation.
|
|
|
|
|
|
For example, the NIST benchmark datasets are known to include faces of
|
|
|
|
|
|
wounded people (Keyes, 2019). The Clearview company is known to use
|
|
|
|
|
|
images scraped illegally from social media, and IBM uses a dataset that
|
|
|
|
|
|
is likely in violation of European GDPR legislation (Bommasani et al.,
|
|
|
|
|
|
2022: 154). Pasquinelli (2019) argued that machine learning models
|
|
|
|
|
|
ultimately act as data compressors: enfolding and operationalizing
|
|
|
|
|
|
imagery of which the terms of acquisition are invisibilized.</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Body Text">
|
|
|
|
|
|
<p>Attention to this invisibilization reveals a discrepancy between the
|
|
|
|
|
|
developers and the implementers of these technologies. On the one hand,
|
|
|
|
|
|
the developers we interviewed expressed concerns about how their
|
|
|
|
|
|
training data is constituted to gain a maximum false positive rate/true
|
|
|
|
|
|
positive rate (FPR/TPR) ratio, while showing concern for the legality of
|
|
|
|
|
|
the data they use to train their algorithms. On the other hand,
|
|
|
|
|
|
questions about the constitution of the dataset have been virtually
|
|
|
|
|
|
non-existent in our conversations with those who implement software that
|
|
|
|
|
|
relies on models trained with such data. Occasionally this knowledge was
|
|
|
|
|
|
considered part of the developers' intellectual property that had to be
|
|
|
|
|
|
kept a trade secret. A high score on the benchmark is enough to pass
|
|
|
|
|
|
questions of fairness, legitimizing the use of the algorithmic model.
|
|
|
|
|
|
Thus, while indirectly relying on the source data, it is no longer
|
|
|
|
|
|
deemed relevant in the consideration of an algorithm. This illustrates
|
|
|
|
|
|
well how the invisibilization of the “compressed” dataset, in
|
|
|
|
|
|
Pasquinelli’s terms, into a model, with the formalization of guiding
|
|
|
|
|
|
metrics into a benchmark, permits a bracketing of accountability. One
|
|
|
|
|
|
does not need to know how outcomes are produced, as long as the
|
|
|
|
|
|
benchmarks are in order.</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Body Text">
|
|
|
|
|
|
<p>The configuration of algorithmic vision’s bias across a complex
|
|
|
|
|
|
network of fragmented locations and actors, from the dataset, to the
|
|
|
|
|
|
algorithm, to the benchmark institution reveals the selective processes
|
|
|
|
|
|
of (in)visibilization. This opens up fruitful alleys for new empirical
|
|
|
|
|
|
research: What are the politics of the benchmark as a mechanism of
|
|
|
|
|
|
legitimization? How does the outsourcing of assessing the error
|
|
|
|
|
|
distribution impact attention to bias? How has the critique of bias been
|
|
|
|
|
|
institutionalized by the security industry, resulting in the
|
|
|
|
|
|
externalization of accountability, through dis-location and
|
|
|
|
|
|
fragmentation?</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
</section>
|
|
|
|
|
|
<section id="reconfiguring-the-human-in-the-loop" class="level2">
|
|
|
|
|
|
<h2>Reconfiguring the human-in-the-loop</h2>
|
|
|
|
|
|
<div data-custom-style="Body Text">
|
|
|
|
|
|
<p>A second central question linked to the delegation of accountability
|
|
|
|
|
|
is the configuration in which the security operator is located. The
|
|
|
|
|
|
effects of delegation and fragmentation in which the mitigation of
|
|
|
|
|
|
algorithmic errors is outsourced to an external party, becomes visible
|
|
|
|
|
|
in the ways in which the role of the security operator is configured in
|
|
|
|
|
|
relation to the institution they work for, the software’s assessment,
|
|
|
|
|
|
and the affected publics.</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Body Text">
|
|
|
|
|
|
<p>The public critique of algorithms has often construed the
|
|
|
|
|
|
<em>human-in-the loop</em> as one of the last lines of defense in the
|
|
|
|
|
|
resistance to automated systems, able to filter and correct erroneous
|
|
|
|
|
|
outcomes (Markoff, 2020). The literature in critical security studies
|
|
|
|
|
|
has however problematized the representation of the security operator in
|
|
|
|
|
|
algorithmic assemblages by discussing how the algorithmic predictions
|
|
|
|
|
|
appear on their screen (Aradau and Blanke, 2018), and how the embodied
|
|
|
|
|
|
decision making of the operator is entangled with the algorithmic
|
|
|
|
|
|
assemblage (Wilcox, 2017). Moreover, the operator is often left guessing
|
|
|
|
|
|
at the working of the device that provides them with information to make
|
|
|
|
|
|
their decision (Møhl, 2021).
|
|
|
|
|
|
</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Body Text">
|
|
|
|
|
|
<p>What our participants’ diagrams emphasized is how a whole spectrum of
|
|
|
|
|
|
system designs emerges in response to similar questions, for example the
|
|
|
|
|
|
issue of algorithmic bias. A primary difference can be found in the
|
|
|
|
|
|
degree of understanding of the systems that is expected of security
|
|
|
|
|
|
operators, as well as their perceived autonomy. Sometimes, the human
|
|
|
|
|
|
operator is central to the system’s operation, forming the interface
|
|
|
|
|
|
between the algorithmic systems and surveillance practices. Gerwin van
|
|
|
|
|
|
der Lugt, developer of software at Oddity.ai that detects criminal
|
|
|
|
|
|
behavior argues that “the responsibility for how to deal with the
|
|
|
|
|
|
violent incidents is always [on a] human, not the algorithm. The
|
|
|
|
|
|
algorithm just detects violence—that’s it—but the human needs to deal
|
|
|
|
|
|
with it.”</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Body Text">
|
|
|
|
|
|
<p>Dirk Herzbach, chief of police at the Police Headquarters Mannheim,
|
|
|
|
|
|
adds that when alerted to an incident by the system, the operator
|
|
|
|
|
|
decides whether to deploy a police car. Both Herzbach and Van der Lugt
|
|
|
|
|
|
figure the human-in-the-loop as having full agency and responsibility in
|
|
|
|
|
|
operating the (in)security assemblage (cf. Hoijtink and Leese,
|
|
|
|
|
|
2019).</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Body Text">
|
|
|
|
|
|
<p>Some interviewees drew a diagram in which the operator is supposed to
|
|
|
|
|
|
be aware of the ways in which the technology errs, so they can address
|
|
|
|
|
|
them. Several other interviewees considered the technical expertise of
|
|
|
|
|
|
the human-in-the-loop to be unimportant, even a hindrance.</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Body Text">
|
|
|
|
|
|
<p>Chief of police Herzbach prefers an operator to have patrol
|
|
|
|
|
|
experience to assess which situations require intervention. He is
|
|
|
|
|
|
concerned that knowledge about algorithmic biases might interfere with
|
|
|
|
|
|
such decisions. In the case of the Moscow metro, in which a facial
|
|
|
|
|
|
recognition system has been deployed to purchase tickets and open access
|
|
|
|
|
|
gates, the human-in-the-loop is reconfigured as an end user who needs to
|
|
|
|
|
|
be shielded from the algorithm’s operation (c.f. Lorusso, 2021). On
|
|
|
|
|
|
these occasions, expertise on the technological creation of the suspect
|
|
|
|
|
|
becomes fragmented.</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Body Text">
|
|
|
|
|
|
<p>These different figurations of the security operator are held
|
|
|
|
|
|
together by the idea that the human operator is the expert of the
|
|
|
|
|
|
subject of security, and is expected to make decisions independent from
|
|
|
|
|
|
the information that the algorithmic system provides.</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Figure">
|
|
|
|
|
|
<div class="anchor" data-i="3" style="height:6in"></div>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Caption">
|
|
|
|
|
|
<p>Diagram 9. Riemen explains the process of information filtering that
|
|
|
|
|
|
is involved in querying the facial recognition database of the Dutch
|
|
|
|
|
|
police.</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Body Text">
|
|
|
|
|
|
<p>Other drivers exist, however, to shield the operator from the
|
|
|
|
|
|
algorithm’s functioning, challenging individual expertise and
|
|
|
|
|
|
acknowledging the fallibility of human decision making. In Diagram 9,
|
|
|
|
|
|
John Riemen outlines the use of facial recognition by the Dutch police.
|
|
|
|
|
|
He describes how data from the police case and on the algorithmic
|
|
|
|
|
|
assessment is filtered out as much as possible from the information
|
|
|
|
|
|
provided to the operator. This, Riemen suggests, might reduce bias in
|
|
|
|
|
|
the final decision. He adds that there should be no fewer than three
|
|
|
|
|
|
humans-in-the-loop who operate independently to increase the accuracy of
|
|
|
|
|
|
the algorithmic security vision.</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Body Text">
|
|
|
|
|
|
<p>Instead of increasing their number, there is another configuration of
|
|
|
|
|
|
the human-in-the-loop that responds to the fallibility of the operator.
|
|
|
|
|
|
For the Burglary-Free Neighborhood project in Rotterdam, project manager
|
|
|
|
|
|
Guido Delver draws surveillance as operated by neighborhood residents,
|
|
|
|
|
|
through a system that they own themselves. By involving different
|
|
|
|
|
|
stakeholders, Delver hopes to counter government hegemony over the
|
|
|
|
|
|
surveillance apparatus. However, residents are untrained in assessing
|
|
|
|
|
|
algorithmic predictions raising new challenges. Delver illustrates a
|
|
|
|
|
|
scenario in which the algorithmic signaling of a potential burglary may
|
|
|
|
|
|
have dangerous consequences: “Does it invoke the wrong behavior from the
|
|
|
|
|
|
citizen? [They could] go out with a bat and look for the guy who has
|
|
|
|
|
|
done nothing [because] it was a false positive.” In this case, the worry
|
|
|
|
|
|
is that the erroneous predictions will not be questioned. Therefore, in
|
|
|
|
|
|
Delver’s project the goal was to actualize an autonomous system, “with
|
|
|
|
|
|
as little interference as possible.” Human participation or
|
|
|
|
|
|
“interference” in the operation are potentially harmful. Thus, figuring
|
|
|
|
|
|
the operator — whether police officer or neighborhood resident — as
|
|
|
|
|
|
risky, can lead to the relegation of direct human intervention.</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Body Text">
|
|
|
|
|
|
<p>By looking at the figurations of the operator that appear in the
|
|
|
|
|
|
diagrams we see multiple and heterogeneous configurations of
|
|
|
|
|
|
regulations, security companies, and professionals. In each
|
|
|
|
|
|
configuration, the human-in-the-loop appears in different forms. The
|
|
|
|
|
|
operator often holds the final responsibility in the ethical functioning
|
|
|
|
|
|
of the system. At times they are configured as an expert in
|
|
|
|
|
|
sophisticated but error-prone systems; at others they are figured as end
|
|
|
|
|
|
users who are activated by the alerts generated by the system, and who
|
|
|
|
|
|
need not understand how the software works and errs, or who can be left
|
|
|
|
|
|
out.</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Body Text">
|
|
|
|
|
|
<p>These configurations remind us that there cannot be any theorization
|
|
|
|
|
|
of “algorithmic security vision,” both of its empirical workings and its
|
|
|
|
|
|
ethical and political consequences without close attention to the
|
|
|
|
|
|
empirical contexts in which the configurations are arranged. Each
|
|
|
|
|
|
organization of datasets, algorithms, benchmarks, hardware and operators
|
|
|
|
|
|
has specific problems. And each contains specific politics of
|
|
|
|
|
|
visibilization, invisibilization, responsibility and accountability.</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
</section>
|
2023-12-19 07:35:00 +00:00
|
|
|
|
</section>
|
|
|
|
|
|
<section id="a-diagram-of-research" class="level1">
|
|
|
|
|
|
<h1>A diagram of research</h1>
|
|
|
|
|
|
<div data-custom-style="Body Text">
|
|
|
|
|
|
<p>In this conclusion, we reflect upon a final dimension of the method
|
|
|
|
|
|
of diagraming in the context of figurations and configurations: its
|
|
|
|
|
|
potential as an alternative to the conventional research program.</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Body Text">
|
|
|
|
|
|
<p>While writing this text, indeed, the search for a coherent structure
|
|
|
|
|
|
through which we could map the problems that emerged from analyzing the
|
|
|
|
|
|
diagrams in a straightforward narrative proved elusive. We considered
|
|
|
|
|
|
various organizational frameworks, but consistently encountered
|
|
|
|
|
|
resistance from one or two sections. It became evident that our
|
|
|
|
|
|
interviews yielded a rhizome of interrelated problems, creating a
|
|
|
|
|
|
multitude of possible inquiries and overlapping trajectories. Some
|
|
|
|
|
|
dimensions of these problems are related, but not to every problem.</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Body Text">
|
|
|
|
|
|
<p>If we take for example the understanding of algorithmic security
|
|
|
|
|
|
vision as practices of error management as a starting point, we see how
|
|
|
|
|
|
the actors we interviewed have incorporated the societal critique of
|
|
|
|
|
|
algorithmic bias. This serves as a catalyst for novel strategies aimed
|
|
|
|
|
|
at mitigating the repercussions of imperfect systems. The societal
|
|
|
|
|
|
critique has driven the development of synthetic datasets, which promise
|
|
|
|
|
|
equitable representation across diverse demographic groups. It has also
|
|
|
|
|
|
been the reason for the reliance on institutionalized benchmarks to
|
|
|
|
|
|
assess the impartiality of algorithms. Moreover, different
|
|
|
|
|
|
configurations of the human-in-the-loop emerge, all promised to rectify
|
|
|
|
|
|
algorithmic fallibility. We see a causal chain there.</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Body Text">
|
|
|
|
|
|
<p>But how does the question of algorithmic error relate to the shift
|
|
|
|
|
|
from photographic to cinematic vision that algorithmic security vision
|
|
|
|
|
|
brings about? Certainly, there are reverberations. The relegation of
|
|
|
|
|
|
stable identity that we outlined, could be seen as a way to mitigate the
|
|
|
|
|
|
impact of those errors. But it would be a leap to identify these
|
|
|
|
|
|
questions of error as the central driver for the increased incorporation
|
|
|
|
|
|
of moving images in algorithmic security vision.</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Body Text">
|
|
|
|
|
|
<p>However, if we take as our starting point the formidable strides in
|
|
|
|
|
|
computing power and the advancements in camera technologies, we face
|
|
|
|
|
|
similar problems. These developments make the analysis of movement
|
|
|
|
|
|
possible while helping to elucidate the advances in the real-time
|
|
|
|
|
|
analysis that are required to remove the human-in-the-loop, as trialed
|
|
|
|
|
|
in the Burglary-Free Neighborhood. These developments account for the
|
|
|
|
|
|
feasibility of the synthetic data generation, a computing-intense
|
|
|
|
|
|
process which opens a vast horizon of possibilities for developers to
|
|
|
|
|
|
detect objects or actions. Such an account, however, does not address
|
|
|
|
|
|
the need for such a synthetic dataset. A focus on the computation of
|
|
|
|
|
|
movement, however, would highlight how a lack of training data
|
|
|
|
|
|
necessitates many of the practices described. Synthetic data is
|
|
|
|
|
|
necessitated by the glaring absence of pre-existing security datasets
|
|
|
|
|
|
that contain moving bodies. While facial recognition algorithms could be
|
|
|
|
|
|
trained and operated on quickly repurposed photographic datasets of
|
|
|
|
|
|
national identity cards or drivers’ license registries, no dataset for
|
|
|
|
|
|
moving bodies has been available to be repurposed by states or
|
|
|
|
|
|
corporations. This absence of training data requires programmers to
|
|
|
|
|
|
stage scenes for the camera. Thus, while one issue contains echoes of
|
|
|
|
|
|
the other, the network of interrelated problematizations cannot be
|
|
|
|
|
|
flattened into a single narrative.</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Body Text">
|
|
|
|
|
|
<p>The constraints imposed by the linear structure of an academic
|
|
|
|
|
|
article certainly necessitate a specific ordering of sections. Yet the
|
|
|
|
|
|
different research directions we highlight form something else. The
|
|
|
|
|
|
multiple figurations analyzed here generate fresh tensions when put in
|
|
|
|
|
|
relation with security and political practices. What appears from the
|
|
|
|
|
|
diagrams is a network of figurations in various configurations. Instead
|
|
|
|
|
|
of a research <em>program</em>, our interviews point toward a larger
|
|
|
|
|
|
research <em>diagram</em> of interrelated questions, which invites us to
|
|
|
|
|
|
think in terms of pathways through this dynamic and evolving network of
|
|
|
|
|
|
relations.</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
</section>
|
|
|
|
|
|
<section id="references" class="level1">
|
|
|
|
|
|
<h1>References</h1>
|
|
|
|
|
|
<div data-custom-style="Bibliography">
|
|
|
|
|
|
<p>Ajana B (2013) <em>Governing Through Biometrics</em>. London:
|
|
|
|
|
|
Palgrave Macmillan UK. DOI: <a href="https://doi.org/10.1057/9781137290755"><span
|
|
|
|
|
|
data-custom-style="Hyperlink">10.1057/9781137290755</span></a>.</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Bibliography">
|
|
|
|
|
|
<p>Amicelle A, Aradau C and Jeandesboz J (2015) Questioning security
|
|
|
|
|
|
devices: Performativity, resistance, politics. <em>Security
|
|
|
|
|
|
Dialogue</em> 46(4): 293–306. DOI: <a href="https://doi.org/10.1177/0967010615586964"><span
|
|
|
|
|
|
data-custom-style="Hyperlink">10.1177/0967010615586964</span></a>.</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Bibliography">
|
|
|
|
|
|
<p>Amoore L (2014) Security and the incalculable. <em>Security
|
|
|
|
|
|
Dialogue</em> 45(5). SAGE Publications Ltd: 423–439. DOI: <a
|
|
|
|
|
|
href="https://doi.org/10.1177/0967010614539719"><span
|
|
|
|
|
|
data-custom-style="Hyperlink">10.1177/0967010614539719</span></a>.</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Bibliography">
|
|
|
|
|
|
<p>Amoore L (2019) Doubt and the algorithm: On the partial accounts of
|
|
|
|
|
|
machine learning. <em>Theory, Culture & Society</em> 36(6). SAGE
|
|
|
|
|
|
Publications Ltd: 147–169. DOI: <a href="https://doi.org/10.1177/0263276419851846"><span
|
|
|
|
|
|
data-custom-style="Hyperlink">10.1177/0263276419851846</span></a>.</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Bibliography">
|
|
|
|
|
|
<p>Amoore L (2021) The deep border. <em>Political Geography</em>.
|
|
|
|
|
|
Elsevier: 102547.</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Bibliography">
|
|
|
|
|
|
<p>Amoore L and De Goede M (2005) Governance, risk and dataveillance in
|
|
|
|
|
|
the war on terror. <em>Crime, Law and Social Change</em> 43(2): 149–173.
|
|
|
|
|
|
DOI: <a href="https://doi.org/10.1007/s10611-005-1717-8"><span
|
|
|
|
|
|
data-custom-style="Hyperlink">10.1007/s10611-005-1717-8</span></a>.</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Bibliography">
|
|
|
|
|
|
<p>Andersen RS (2015) <em>Remediating Security</em>. 1. oplag.
|
|
|
|
|
|
Ph.d.-serien / københavns universitet, institut for statskundskab. Kbh.:
|
|
|
|
|
|
Københavns Universitet, Institut for Statskundskab.</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Bibliography">
|
|
|
|
|
|
<p>Andersen RS (2018) The art of questioning lethal vision: Mosse’s
|
|
|
|
|
|
infra and militarized machine vision. In: <em>_Proceeding of EVA
|
|
|
|
|
|
copenhagen 2018_</em>, 2018.</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Bibliography">
|
|
|
|
|
|
<p>Andrejevic M and Burdon M (2015) Defining the sensor society.
|
|
|
|
|
|
<em>Television & New Media</em> 16(1): 19–36. DOI: <a
|
|
|
|
|
|
href="https://doi.org/10.1177/1527476414541552"><span
|
|
|
|
|
|
data-custom-style="Hyperlink">10.1177/1527476414541552</span></a>.
|
|
|
|
|
|
</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Bibliography">
|
|
|
|
|
|
<p>Aradau C and Blanke T (2015) The (big) data-security assemblage:
|
|
|
|
|
|
Knowledge and critique. <em>Big Data & Society</em> 2(2):
|
|
|
|
|
|
205395171560906. DOI: <a href="https://doi.org/10.1177/2053951715609066"><span
|
|
|
|
|
|
data-custom-style="Hyperlink">10.1177/2053951715609066</span></a>.</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Bibliography">
|
|
|
|
|
|
<p>Aradau C and Blanke T (2018) Governing others: Anomaly and the
|
|
|
|
|
|
algorithmic subject of security. <em>European Journal of International
|
|
|
|
|
|
Security</em> 3(1). Cambridge University Press: 1–21. DOI: <a
|
|
|
|
|
|
href="https://doi.org/10.1017/eis.2017.14"><span
|
|
|
|
|
|
data-custom-style="Hyperlink">10.1017/eis.2017.14</span></a>.</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Bibliography">
|
|
|
|
|
|
<p>Aradau C, Lobo-Guerrero L and Van Munster R (2008) Security,
|
|
|
|
|
|
technologies of risk, and the political: Guest editors’ introduction.
|
|
|
|
|
|
<em>Security Dialogue</em> 39(2-3): 147–154. DOI: <a
|
|
|
|
|
|
href="https://doi.org/10.1177/0967010608089159"><span
|
|
|
|
|
|
data-custom-style="Hyperlink">10.1177/0967010608089159</span></a>.
|
|
|
|
|
|
</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Bibliography">
|
|
|
|
|
|
<p>Azar M, Cox G and Impett L (2021) Introduction: Ways of machine
|
|
|
|
|
|
seeing. <em>AI & SOCIETY</em>. DOI: <a href="https://doi.org/10.1007/s00146-020-01124-6"><span
|
|
|
|
|
|
data-custom-style="Hyperlink">10.1007/s00146-020-01124-6</span></a>.</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Bibliography">
|
|
|
|
|
|
<p>Bae G, de La Gorce M, Baltrušaitis T, et al. (2023) DigiFace-1M: 1
|
|
|
|
|
|
million digital face images for face recognition. In: <em>2023 IEEE
|
|
|
|
|
|
Winter Conference on Applications of Computer Vision (WACV)</em>, 2023.
|
|
|
|
|
|
IEEE.</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Bibliography">
|
|
|
|
|
|
<p>Barad KM (2007) <em>Meeting the Universe Halfway: Quantum Physics and
|
|
|
|
|
|
the Entanglement of Matter and Meaning</em>. Durham: Duke University
|
|
|
|
|
|
Press.</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Bibliography">
|
|
|
|
|
|
<p>Bellanova R, Irion K, Lindskov Jacobsen K, et al. (2021) Toward a
|
|
|
|
|
|
critique of algorithmic violence. <em>International Political
|
|
|
|
|
|
Sociology</em> 15(1): 121–150. DOI: <a href="https://doi.org/10.1093/ips/olab003"><span
|
|
|
|
|
|
data-custom-style="Hyperlink">10.1093/ips/olab003</span></a>.</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Bibliography">
|
|
|
|
|
|
<p>Bigo D (2002) Security and immigration: Toward a critique of the
|
|
|
|
|
|
governmentality of unease. <em>Alternatives</em> 27. SAGE Publications
|
|
|
|
|
|
Inc: 63–92. DOI: <a href="https://doi.org/10.1177/03043754020270S105"><span
|
|
|
|
|
|
data-custom-style="Hyperlink">10.1177/03043754020270S105</span></a>.</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Bibliography">
|
|
|
|
|
|
<p>Bigo D and Guild E (2005) Policing at a distance: Schengen visa
|
|
|
|
|
|
policies. In: <em>Controlling Frontiers. Free Movement into and Within
|
|
|
|
|
|
Europe</em>. Routledge, pp. 233–263.</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Bibliography">
|
|
|
|
|
|
<p>Bommasani R, Hudson DA, Adeli E, et al. (2022) On the opportunities
|
|
|
|
|
|
and risks of foundation models. Available at: <a href="http://arxiv.org/abs/2108.07258"><span
|
|
|
|
|
|
data-custom-style="Hyperlink">http://arxiv.org/abs/2108.07258</span></a>
|
|
|
|
|
|
(accessed 2 June 2023).</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Bibliography">
|
|
|
|
|
|
<p>Bousquet AJ (2018) <em>The Eye of War</em>. Minneapolis: University
|
|
|
|
|
|
of Minnesota Press.</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Bibliography">
|
|
|
|
|
|
<p>Bucher T (2018) <em>If...Then: Algorithmic Power and Politics</em>.
|
|
|
|
|
|
New York: Oxford University Press.</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Bibliography">
|
|
|
|
|
|
<p>Buolamwini J and Gebru T (2018) Gender shades: Intersectional
|
|
|
|
|
|
accuracy disparities in commercial gender classification.
|
|
|
|
|
|
<em>Proceedings of Machine Learning Research</em> 81.
|
|
|
|
|
|
</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Bibliography">
|
|
|
|
|
|
<p>Calhoun L (2023) Latency, uncertainty, contagion: Epistemologies of
|
|
|
|
|
|
risk-as-reform in crime forecasting software. <em>Environment and
|
|
|
|
|
|
Planning D: Society and Space</em>. SAGE Publications Ltd STM:
|
|
|
|
|
|
02637758231197012. DOI: <a href="https://doi.org/10.1177/02637758231197012"><span
|
|
|
|
|
|
data-custom-style="Hyperlink">10.1177/02637758231197012</span></a>.</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Bibliography">
|
|
|
|
|
|
<p>Carraro V (2021) Grounding the digital: A comparison of Waze’s ‘avoid
|
|
|
|
|
|
dangerous areas’ feature in Jerusalem, Rio de Janeiro and the US.
|
|
|
|
|
|
<em>GeoJournal</em> 86(3): 1121–1139. DOI: <a href="https://doi.org/10.1007/s10708-019-10117-y"><span
|
|
|
|
|
|
data-custom-style="Hyperlink">10.1007/s10708-019-10117-y</span></a>.
|
|
|
|
|
|
</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Bibliography">
|
|
|
|
|
|
<p>Dawson-Howe K (2014) <em>A Practical Introduction to Computer Vision
|
|
|
|
|
|
with OpenCV</em>. 1st edition. Chichester, West Sussex, United Kingdon;
|
|
|
|
|
|
Hoboken, NJ: Wiley.</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Bibliography">
|
|
|
|
|
|
<p>Dijstelbloem H, van Reekum R and Schinkel W (2017) Surveillance at
|
|
|
|
|
|
sea: The transactional politics of border control in the Aegean.
|
|
|
|
|
|
<em>Security Dialogue</em> 48(3): 224–240. DOI: <a href="https://doi.org/10.1177/0967010617695714"><span
|
|
|
|
|
|
data-custom-style="Hyperlink">10.1177/0967010617695714</span></a>.
|
|
|
|
|
|
</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Bibliography">
|
|
|
|
|
|
<p>Farocki H (2004) Phantom images. <em>Public</em>. Available at: <a
|
|
|
|
|
|
href="https://public.journals.yorku.ca/index.php/public/article/view/30354"><span
|
|
|
|
|
|
data-custom-style="Hyperlink">https://public.journals.yorku.ca/index.php/public/article/view/30354</span></a>
|
|
|
|
|
|
(accessed 6 March 2023).</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Bibliography">
|
|
|
|
|
|
<p>Fisher DXO (2018) Situating border control: Unpacking Spain’s SIVE
|
|
|
|
|
|
border surveillance assemblage. <em>Political Geography</em> 65: 67–76.
|
|
|
|
|
|
DOI: <a href="https://doi.org/10.1016/j.polgeo.2018.04.005"><span
|
|
|
|
|
|
data-custom-style="Hyperlink">10.1016/j.polgeo.2018.04.005</span></a>.</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Bibliography">
|
|
|
|
|
|
<p>Fourcade M and Gordon J (2020) Learning like a state: Statecraft in
|
|
|
|
|
|
the digital age32.</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Bibliography">
|
|
|
|
|
|
<p>Fourcade M and Johns F (2020) Loops, ladders and links: The
|
|
|
|
|
|
recursivity of social and machine learning. <em>Theory and Society</em>:
|
|
|
|
|
|
1–30. DOI: <a href="https://doi.org/10.1007/s11186-020-09409-x"><span
|
|
|
|
|
|
data-custom-style="Hyperlink">10.1007/s11186-020-09409-x</span></a>.</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Bibliography">
|
|
|
|
|
|
<p>Fraser A (2019) Curating digital geographies in an era of data
|
|
|
|
|
|
colonialism. <em>Geoforum</em> 104. Elsevier: 193–200.</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Bibliography">
|
|
|
|
|
|
<p>Galton F (1879) Composite portraits, made by combining those of many
|
|
|
|
|
|
different persons into a single resultant figure. <em>The Journal of the
|
|
|
|
|
|
Anthropological Institute of Great Britain and Ireland</em> 8. [Royal
|
|
|
|
|
|
Anthropological Institute of Great Britain; Ireland, Wiley]: 132–144.
|
|
|
|
|
|
DOI: <a href="https://doi.org/10.2307/2841021"><span
|
|
|
|
|
|
data-custom-style="Hyperlink">10.2307/2841021</span></a>.</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Bibliography">
|
|
|
|
|
|
<p>Gandy OH (2021) <em>The Panoptic Sort: A Political Economy of
|
|
|
|
|
|
Personal Information</em>. Oxford University Press. Available at: <a
|
|
|
|
|
|
href="https://books.google.com?id=JOEsEAAAQBAJ"><span
|
|
|
|
|
|
data-custom-style="Hyperlink">https://books.google.com?id=JOEsEAAAQBAJ</span></a>.</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Bibliography">
|
|
|
|
|
|
<p>Gillespie T (2018) <em>Custodians of the Internet: Platforms, Content
|
|
|
|
|
|
Moderation, and the Hidden Decisions That Shape Social Media</em>.
|
|
|
|
|
|
Illustrated edition. Yale University Press.</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Bibliography">
|
|
|
|
|
|
<p>Goodwin C (1994) Professional vision. <em>American
|
|
|
|
|
|
Anthropologist</em> 96(3).</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Bibliography">
|
|
|
|
|
|
<p>Graham S (1998) Spaces of surveillant simulation: New technologies,
|
|
|
|
|
|
digital representations, and material geographies. <em>Environment and
|
|
|
|
|
|
Planning D: Society and Space</em> 16(4). SAGE Publications Sage UK:
|
|
|
|
|
|
London, England: 483–504.</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Bibliography">
|
|
|
|
|
|
<p>Graham SD (2005) Software-sorted geographies. <em>Progress in human
|
|
|
|
|
|
geography</em> 29(5). Sage Publications Sage CA: Thousand Oaks, CA:
|
|
|
|
|
|
562–580.</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Bibliography">
|
|
|
|
|
|
<p>Grasseni C (2004) Skilled vision. An apprenticeship in breeding
|
|
|
|
|
|
aesthetics. <em>Social Anthropology</em> 12(1): 41–55. DOI: <a
|
|
|
|
|
|
href="https://doi.org/10.1017/S0964028204000035"><span
|
|
|
|
|
|
data-custom-style="Hyperlink">10.1017/S0964028204000035</span></a>.</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Bibliography">
|
|
|
|
|
|
<p>Grasseni C (2018) Skilled vision. In: Callan H (ed.) <em>The
|
|
|
|
|
|
International Encyclopedia of Anthropology</em>. 1st ed. Wiley, pp. 1–7.
|
|
|
|
|
|
DOI: <a href="https://doi.org/10.1002/9781118924396.wbiea1657"><span
|
|
|
|
|
|
data-custom-style="Hyperlink">10.1002/9781118924396.wbiea1657</span></a>.</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Bibliography">
|
|
|
|
|
|
<p>Haraway D (1988) Situated knowledges: The science question in
|
|
|
|
|
|
feminism and the privilege of partial perspective. <em>Feminist
|
|
|
|
|
|
Studies</em> 14(3). Feminist Studies, Inc.: 575–599. DOI: <a
|
|
|
|
|
|
href="https://doi.org/10.2307/3178066"><span
|
|
|
|
|
|
data-custom-style="Hyperlink">10.2307/3178066</span></a>.</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Bibliography">
|
|
|
|
|
|
<p>Hoijtink M and Leese M (2019) How (not) to talk about technology
|
|
|
|
|
|
international relations and the question of agency. In: Hoijtink M and
|
|
|
|
|
|
Leese M (eds) <em>Technology and Agency in International Relations</em>.
|
|
|
|
|
|
Emerging technologies, ethics and international affairs. London ; New
|
|
|
|
|
|
York: Routledge, pp. 1–24.</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Bibliography">
|
|
|
|
|
|
<p>Hopman R and M’charek A (2020) Facing the unknown suspect: Forensic
|
|
|
|
|
|
DNA phenotyping and the oscillation between the individual and the
|
|
|
|
|
|
collective. <em>BioSocieties</em> 15(3): 438–462. DOI: <a
|
|
|
|
|
|
href="https://doi.org/10.1057/s41292-020-00190-9"><span
|
|
|
|
|
|
data-custom-style="Hyperlink">10.1057/s41292-020-00190-9</span></a>.</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Bibliography">
|
|
|
|
|
|
<p>Hunger F (2023) <em>Unhype artificial ’intelligence’! A proposal to
|
|
|
|
|
|
replace the deceiving terminology of AI.</em> 12 April. Zenodo. DOI: <a
|
|
|
|
|
|
href="https://doi.org/10.5281/zenodo.7524493"><span
|
|
|
|
|
|
data-custom-style="Hyperlink">10.5281/zenodo.7524493</span></a>.</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Bibliography">
|
|
|
|
|
|
<p>Huysmans J (2022) Motioning the politics of security: The primacy of
|
|
|
|
|
|
movement and the subject of security. <em>Security Dialogue</em> 53(3):
|
|
|
|
|
|
238–255. DOI: <a href="https://doi.org/10.1177/09670106211044015"><span
|
|
|
|
|
|
data-custom-style="Hyperlink">10.1177/09670106211044015</span></a>.</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Bibliography">
|
|
|
|
|
|
<p>Isin E and Ruppert E (2020) The birth of sensory power: How a
|
|
|
|
|
|
pandemic made it visible? <em>Big Data & Society</em> 7(2). SAGE
|
|
|
|
|
|
Publications Ltd: 2053951720969208. DOI: <a href="https://doi.org/10.1177/2053951720969208"><span
|
|
|
|
|
|
data-custom-style="Hyperlink">10.1177/2053951720969208</span></a>.</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Bibliography">
|
|
|
|
|
|
<p>Jasanoff S (2004) <em>States of Knowledge: The Co-Production of
|
|
|
|
|
|
Science and Social Order</em>. Routledge Taylor & Francis Group.</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Bibliography">
|
|
|
|
|
|
<p>Ji Z, Lee N, Frieske R, et al. (2023) Survey of hallucination in
|
|
|
|
|
|
natural language generation. <em>ACM Computing Surveys</em> 55(12):
|
|
|
|
|
|
1–38. DOI: <a href="https://doi.org/10.1145/3571730"><span
|
|
|
|
|
|
data-custom-style="Hyperlink">10.1145/3571730</span></a>.</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Bibliography">
|
|
|
|
|
|
<p>Keyes O (2019) The gardener’s vision of data: Data science reduces
|
|
|
|
|
|
people to subjects that can be mined for truth. <em>Real Life Mag</em>.
|
|
|
|
|
|
Available at: <a href="https://reallifemag.com/the-gardeners-vision-of-data/"><span
|
|
|
|
|
|
data-custom-style="Hyperlink">https://reallifemag.com/the-gardeners-vision-of-data/</span></a>.
|
|
|
|
|
|
</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Bibliography">
|
|
|
|
|
|
<p>Latour B (2005) <em>Reassembling the Social: An Introduction to
|
|
|
|
|
|
Actor-Network-Theory</em>. Clarendon Lectures in Management Studies.
|
|
|
|
|
|
Oxford; New York: Oxford University Press.</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Bibliography">
|
|
|
|
|
|
<p>Leese M (2015) ‘We were taken by surprise’: Body scanners, technology
|
|
|
|
|
|
adjustment, and the eradication of failure. <em>Critical Studies on
|
|
|
|
|
|
Security</em> 3(3). Routledge: 269–282. DOI: <a
|
|
|
|
|
|
href="https://doi.org/10.1080/21624887.2015.1124743"><span
|
|
|
|
|
|
data-custom-style="Hyperlink">10.1080/21624887.2015.1124743</span></a>.</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Bibliography">
|
|
|
|
|
|
<p>Leese M (2019) Configuring warfare: Automation, control, agency. In:
|
|
|
|
|
|
Hoijtink M and Leese M (eds) Technology and Agency in International
|
|
|
|
|
|
Relations. Emerging technologies, ethics and international affairs.
|
|
|
|
|
|
London ; New York: Routledge, pp. 42–65.</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Bibliography">
|
|
|
|
|
|
<p>Lorusso S (2021) The user condition. Available at: <a href="https://theusercondition.computer/"><span
|
|
|
|
|
|
data-custom-style="Hyperlink">https://theusercondition.computer/</span></a>
|
|
|
|
|
|
(accessed 18 February 2021).</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Bibliography">
|
|
|
|
|
|
<p>Lyon D (2003) <em>Surveillance as Social Sorting: Privacy, Risk, and
|
|
|
|
|
|
Digital Discrimination</em>. Psychology Press. Available at: <a
|
|
|
|
|
|
href="https://books.google.com?id=yCLFBfZwl08C"><span
|
|
|
|
|
|
data-custom-style="Hyperlink">https://books.google.com?id=yCLFBfZwl08C</span></a>.</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Bibliography">
|
|
|
|
|
|
<p>Mackenzie A (2017) <em>Machine Learners: Archaeology of a Data
|
|
|
|
|
|
Practice</em>. The MIT Press. DOI: <a href="https://doi.org/10.7551/mitpress/10302.001.0001"><span
|
|
|
|
|
|
data-custom-style="Hyperlink">10.7551/mitpress/10302.001.0001</span></a>.</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Bibliography">
|
|
|
|
|
|
<p>Maguire M, Frois C and Zurawski N (eds) (2014) <em>The Anthropology
|
|
|
|
|
|
of Security: Perspectives from the Frontline of Policing,
|
|
|
|
|
|
Counter-Terrorism and Border Control</em>. Anthropology, culture and
|
|
|
|
|
|
society. London: Pluto Press.</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Bibliography">
|
|
|
|
|
|
<p>Mahony M (2021) Geographies of science and technology 1: Boundaries
|
|
|
|
|
|
and crossings. <em>Progress in Human Geography</em> 45(3): 586–595. DOI:
|
|
|
|
|
|
<a href="https://doi.org/10.1177/0309132520969824"><span
|
|
|
|
|
|
data-custom-style="Hyperlink">10.1177/0309132520969824</span></a>.
|
|
|
|
|
|
</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Bibliography">
|
|
|
|
|
|
<p>Markoff J (2020) Robots will need humans in future. <em>The New York
|
|
|
|
|
|
Times: Section B</em>, 22 May. New York. Available at: <a
|
|
|
|
|
|
href="https://www.nytimes.com/2020/05/21/technology/ben-shneiderman-automation-humans.html"><span
|
|
|
|
|
|
data-custom-style="Hyperlink">https://www.nytimes.com/2020/05/21/technology/ben-shneiderman-automation-humans.html</span></a>
|
|
|
|
|
|
(accessed 31 October 2023).</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Bibliography">
|
|
|
|
|
|
<p>McCosker A and Wilken R (2020) <em>Automating Vision: The Social
|
|
|
|
|
|
Impact of the New Camera Consciousness</em>. 1st edition. Routledge.</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Bibliography">
|
|
|
|
|
|
<p>Møhl P (2021) Seeing threats, sensing flesh: Human–machine ensembles
|
|
|
|
|
|
at work. <em>AI & SOCIETY</em> 36(4): 1243–1252. DOI: <a
|
|
|
|
|
|
href="https://doi.org/10.1007/s00146-020-01064-1"><span
|
|
|
|
|
|
data-custom-style="Hyperlink">10.1007/s00146-020-01064-1</span></a>.</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Bibliography">
|
|
|
|
|
|
<p>Muller B (2010) <em>Security, Risk and the Biometric State</em>.
|
|
|
|
|
|
Routledge. DOI: <a href="https://doi.org/10.4324/9780203858042"><span
|
|
|
|
|
|
data-custom-style="Hyperlink">10.4324/9780203858042</span></a>.</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Bibliography">
|
|
|
|
|
|
<p>O’Sullivan S (2016) On the diagram (and a practice of diagrammatics).
|
|
|
|
|
|
In: Schneider K, Yasar B, and Lévy D (eds) <em>Situational Diagram</em>.
|
|
|
|
|
|
New York: Dominique Lévy, pp. 13–25.</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Bibliography">
|
|
|
|
|
|
<p>Olwig KF, Grünenberg K, Møhl P, et al. (2019) <em>The Biometric
|
|
|
|
|
|
Border World: Technologies, Bodies and Identities on the Move</em>. 1st
|
|
|
|
|
|
ed. Routledge. DOI: <a href="https://doi.org/10.4324/9780367808464"><span
|
|
|
|
|
|
data-custom-style="Hyperlink">10.4324/9780367808464</span></a>.</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Bibliography">
|
|
|
|
|
|
<p>Pasquinelli M (2015) Anomaly detection: The mathematization of the
|
|
|
|
|
|
abnormal in the metadata society. Panel presentation.</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Bibliography">
|
|
|
|
|
|
<p>Pasquinelli M (2019) How a machine learns and fails – a grammar of
|
|
|
|
|
|
error for artificial intelligence. Available at: <a
|
|
|
|
|
|
href="https://spheres-journal.org/contribution/how-a-machine-learns-and-fails-a-grammar-of-error-for-artificial-intelligence/"><span
|
|
|
|
|
|
data-custom-style="Hyperlink">https://spheres-journal.org/contribution/how-a-machine-learns-and-fails-a-grammar-of-error-for-artificial-intelligence/</span></a>
|
|
|
|
|
|
(accessed 13 January 2021).</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Bibliography">
|
|
|
|
|
|
<p>Pugliese J (2010) <em>Biometrics: Bodies, Technologies,
|
|
|
|
|
|
Biopolitics</em>. New York: Routledge. DOI: <a href="https://doi.org/10.4324/9780203849415"><span
|
|
|
|
|
|
data-custom-style="Hyperlink">10.4324/9780203849415</span></a>.</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Bibliography">
|
|
|
|
|
|
<p>Schurr C, Marquardt N and Militz E (2023) Intimate technologies:
|
|
|
|
|
|
Towards a feminist perspective on geographies of technoscience.
|
|
|
|
|
|
<em>Progress in Human Geography</em>. SAGE Publications Ltd:
|
|
|
|
|
|
03091325231151673. DOI: <a href="https://doi.org/10.1177/03091325231151673"><span
|
|
|
|
|
|
data-custom-style="Hyperlink">10.1177/03091325231151673</span></a>.
|
|
|
|
|
|
</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Bibliography">
|
|
|
|
|
|
<p>Soon W and Cox G (2021) <em>Aesthetic Programming: A Handbook of
|
|
|
|
|
|
Software Studies</em>. London: Open Humanities Press. Available at: <a
|
|
|
|
|
|
href="http://www.openhumanitiespress.org/books/titles/aesthetic-programming/"><span
|
|
|
|
|
|
data-custom-style="Hyperlink">http://www.openhumanitiespress.org/books/titles/aesthetic-programming/</span></a>
|
|
|
|
|
|
(accessed 9 March 2021).</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Bibliography">
|
|
|
|
|
|
<p>Srnicek N and De Sutter L (2017) <em>Platform Capitalism</em>. Theory
|
|
|
|
|
|
redux. Cambridge, UK ; Malden, MA: Polity.</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Bibliography">
|
|
|
|
|
|
<p>Stevens N and Keyes O (2021) Seeing infrastructure: Race, facial
|
|
|
|
|
|
recognition and the politics of data. <em>Cultural Studies</em> 35(4-5):
|
|
|
|
|
|
833–853. DOI: <a href="https://doi.org/10.1080/09502386.2021.1895252"><span
|
|
|
|
|
|
data-custom-style="Hyperlink">10.1080/09502386.2021.1895252</span></a>.</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Bibliography">
|
|
|
|
|
|
<p>Suchman L (2006) <em>Human-Machine Reconfigurations: Plans and
|
|
|
|
|
|
Situated Actions</em>. 2nd edition. Cambridge University Press.</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Bibliography">
|
|
|
|
|
|
<p>Suchman L (2012) Configuration. In: <em>Inventive Methods</em>.
|
|
|
|
|
|
Routledge, pp. 48–60.</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Bibliography">
|
|
|
|
|
|
<p>Suchman L (2020) Algorithmic warfare and the reinvention of accuracy.
|
|
|
|
|
|
<em>Critical Studies on Security</em> 8(2). Routledge: 175–187. DOI: <a
|
|
|
|
|
|
href="https://doi.org/10.1080/21624887.2020.1760587"><span
|
|
|
|
|
|
data-custom-style="Hyperlink">10.1080/21624887.2020.1760587</span></a>.
|
|
|
|
|
|
</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Bibliography">
|
|
|
|
|
|
<p>Sudmann A (2021) Artificial neural networks, postdigital
|
|
|
|
|
|
infrastructures and the politics of temporality. In: Volmar A and Stine
|
|
|
|
|
|
K (eds) <em>Media Infrastructures and the Politics of Digital Time</em>.
|
|
|
|
|
|
Amsterdam University Press, pp. 279–294. DOI: <a href="https://doi.org/10.1515/9789048550753-017"><span
|
|
|
|
|
|
data-custom-style="Hyperlink">10.1515/9789048550753-017</span></a>.</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Bibliography">
|
|
|
|
|
|
<p>Tazzioli M (2018) Spy, track and archive: The temporality of
|
|
|
|
|
|
visibility in Eurosur and Jora. <em>Security Dialogue</em> 49(4):
|
|
|
|
|
|
272–288. DOI: <a href="https://doi.org/10.1177/0967010618769812"><span
|
|
|
|
|
|
data-custom-style="Hyperlink">10.1177/0967010618769812</span></a>.</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Bibliography">
|
|
|
|
|
|
<p>Thatcher J, O’Sullivan D and Mahmoudi D (2016) Data colonialism
|
|
|
|
|
|
through accumulation by dispossession: New metaphors for daily data.
|
|
|
|
|
|
<em>Environment and Planning D: Society and Space</em> 34(6). SAGE
|
|
|
|
|
|
Publications Ltd STM: 990–1006. DOI: <a href="https://doi.org/10.1177/0263775816633195"><span
|
|
|
|
|
|
data-custom-style="Hyperlink">10.1177/0263775816633195</span></a>.
|
|
|
|
|
|
</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Bibliography">
|
|
|
|
|
|
<p>Uliasz R (2020) Seeing like an algorithm: Operative images and
|
|
|
|
|
|
emergent subjects. <em>AI & SOCIETY</em>. DOI: <a
|
|
|
|
|
|
href="https://doi.org/10.1007/s00146-020-01067-y"><span
|
|
|
|
|
|
data-custom-style="Hyperlink">10.1007/s00146-020-01067-y</span></a>.</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Bibliography">
|
|
|
|
|
|
<p>van de Ven R and Plájás IZ (2022) Inconsistent projections:
|
|
|
|
|
|
Con-figuring security vision through diagramming. <em>A Peer-Reviewed
|
|
|
|
|
|
Journal About</em> 11(1): 50–65. DOI: <a href="https://doi.org/10.7146/aprja.v11i1.134306"><span
|
|
|
|
|
|
data-custom-style="Hyperlink">10.7146/aprja.v11i1.134306</span></a>.</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Bibliography">
|
|
|
|
|
|
<p>Wilcox L (2017) Embodying algorithmic war: Gender, race, and the
|
|
|
|
|
|
posthuman in drone warfare. <em>Security Dialogue</em> 48(1): 11–28.
|
|
|
|
|
|
DOI: <a href="https://doi.org/10.1177/0967010616657947"><span
|
|
|
|
|
|
data-custom-style="Hyperlink">10.1177/0967010616657947</span></a>.</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<div data-custom-style="Bibliography">
|
|
|
|
|
|
<p>Zuboff S (2019) <em>The Age of Surveillance Capitalism: The Fight for
|
|
|
|
|
|
a Human Future at the New Frontier of Power</em>. First edition. New
|
|
|
|
|
|
York: Public Affairs.</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
</section>
|
|
|
|
|
|
<section class="footnotes footnotes-end-of-document" role="doc-endnotes">
|
|
|
|
|
|
<hr />
|
|
|
|
|
|
<ol>
|
|
|
|
|
|
<li id="fn1" role="doc-endnote">
|
|
|
|
|
|
<div data-custom-style="Footnote Text">
|
|
|
|
|
|
<p><span data-custom-style="Footnote Characters"></span> The interface
|
|
|
|
|
|
software and code is available at <a
|
|
|
|
|
|
href="https://git.rubenvandeven.com/security_vision/svganim"><span
|
|
|
|
|
|
data-custom-style="Hyperlink">https://git.rubenvandeven.com/security_vision/svganim</span></a>
|
|
|
|
|
|
and <a href="https://gitlab.com/security-vision/chronodiagram"><span
|
|
|
|
|
|
data-custom-style="Hyperlink">https://gitlab.com/security-vision/chronodiagram</span></a>
|
|
|
|
|
|
</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<a href="#fnref1" class="footnote-back" role="doc-backlink">↩︎</a>
|
|
|
|
|
|
</li>
|
|
|
|
|
|
<li id="fn2" role="doc-endnote">
|
|
|
|
|
|
<div data-custom-style="Footnote Text">
|
|
|
|
|
|
<p><span data-custom-style="Footnote Characters"></span> The interviews
|
|
|
|
|
|
were conducted in several European countries: the majority in the
|
|
|
|
|
|
Netherlands, but also in Belgium, Hungary and Poland. Based on an
|
|
|
|
|
|
initial survey of algorithmic security vision practices in Europe we
|
|
|
|
|
|
identified various roles that are involved in such practices. Being a
|
|
|
|
|
|
rather small group of people, these interviewees do not serve as
|
|
|
|
|
|
“illustrative representatives” (Mol & Law 2002, 16-17) of the field
|
|
|
|
|
|
they work in. However, as the interviewees have different cultural and
|
|
|
|
|
|
institutional affiliations, and hold different positions in working with
|
|
|
|
|
|
algorithms, vision and security, they cover a wide spectrum of
|
|
|
|
|
|
engagements with our research object.</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<a href="#fnref2" class="footnote-back" role="doc-backlink">↩︎</a>
|
|
|
|
|
|
</li>
|
|
|
|
|
|
<li id="fn3" role="doc-endnote">
|
|
|
|
|
|
<div data-custom-style="Footnote Text">
|
|
|
|
|
|
<p><span data-custom-style="Footnote Characters"></span> The interviews
|
|
|
|
|
|
were conducted by the first two authors, and at a later stage by Clemens
|
|
|
|
|
|
Baier. The conversations were largely unstructured, but began with two
|
|
|
|
|
|
basic questions. First, we asked the interviewees if they use diagrams
|
|
|
|
|
|
in their daily practice. We then asked: “when we speak of ‘security
|
|
|
|
|
|
vision’ we speak of the use of computer vision in a security context.
|
|
|
|
|
|
Can you explain from your perspective what these concepts mean and how
|
|
|
|
|
|
they come together?” After the first few interviews, we identified some
|
|
|
|
|
|
recurrent themes, which we then specifically asked later interviewees to
|
|
|
|
|
|
discuss.</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<a href="#fnref3" class="footnote-back" role="doc-backlink">↩︎</a>
|
|
|
|
|
|
</li>
|
|
|
|
|
|
<li id="fn4" role="doc-endnote">
|
|
|
|
|
|
<div data-custom-style="Footnote Text">
|
|
|
|
|
|
<p><span data-custom-style="Footnote Characters"></span> Using
|
|
|
|
|
|
anthropomorphizing terms such as “neural networks,” “learning” and
|
|
|
|
|
|
“training” to denote algorithmic configurations and processes is
|
|
|
|
|
|
suggested to hype “artificial intelligence.” While we support the need
|
|
|
|
|
|
for an alternative terminology as proposed by Hunger (2023), here we
|
|
|
|
|
|
preserve the language of our interviewees.</p>
|
|
|
|
|
|
</div>
|
|
|
|
|
|
<a href="#fnref4" class="footnote-back" role="doc-backlink">↩︎</a>
|
|
|
|
|
|
</li>
|
|
|
|
|
|
</ol>
|
|
|
|
|
|
</section>
|
2023-12-18 09:56:07 +00:00
|
|
|
|
</body>
|
|
|
|
|
|
|
|
|
|
|
|
</html>
|
