Yui Kondo About

Final: FINAL PROJECT

Yui Kondo—MIT Media Lab, 2026Yui Kondo—MIT Media Lab, 2026Yui Kondo—MIT Media Lab, 2026Yui Kondo—MIT Media Lab, 2026
Yui Kondo—MIT Media Lab, 2026Yui Kondo—MIT Media Lab, 2026Yui Kondo—MIT Media Lab, 2026Yui Kondo—MIT Media Lab, 2026

Overview

They are watching us. Big Data analytics and artificial intelligence (AI) draw non-intuitive and unverifiable inferences and predictions about the behaviors, preferences, and private lives of individuals. These inferences draw on highly diverse and feature-rich data of unpredictable value, and create new opportunities for discriminatory, biased, and invasive decision-making. Yet we are behind a one-way mirror: these inferences are not accessible or shown to us. (Wachter, 2019) What does it mean to make a choice when the options have been so carefully arranged for us in an invisible way? Is personal freedom possible on the Internet? (Chayka, 2024)

I propose that we need a shield between us and AI. Right now our digital body is exposed. Just as we wear clothes to present chosen facets of ourselves, we also need clothes in the digital world. The sculpture represents your digital body, built from the traces you leave on platforms like YouTube, TikTok, Claude and elsewhere. A language model reads those traces and turns them into inferences: demographics, behavior, relationships, goals, interests, and the sensitive ones in between. Each inference becomes one panel of a modular shell around a body.

Undressed, the sculpture tells everything it knows about you. Put a piece of clothing on it and it speaks only from the facets you chose to show; take the clothing off and the rest comes back. Assembling and disassembling a sculpture made of your own data lets you think about this with your hands: what to show, what to hide, and to whom.

Prototype v1 ↗ (Sep 25 2026)

Data Barbie, prototype v1Open in new tab ↗
Source data-barbie.html · 607 lines
<!doctype html><html><head><meta charset="utf-8"><meta name="viewport" content="width=device-width,initial-scale=1,viewport-fit=cover"><style>[hidden]{display:none!important}body{margin:0}</style><title>Data Barbie</title>
<link rel="stylesheet" href="https://fonts.googleapis.com/css2?family=Instrument+Sans:ital,wght@0,400..700;1,400..700&family=Instrument+Serif:ital@0;1&family=JetBrains+Mono:wght@400;500&display=swap">
<style>
:root{
  --wall:#f7f7f7; --carpet:#f7f7f7; --carpet-2:#f7f7f7; --white:#ffffff;
  --ink:#111111; --ink-2:#555555; --ink-3:#8a8a8a; --rule:#111111; --rule-soft:rgba(17,17,17,.14);
  --red:#ff0000; --acrylic:rgba(120,140,180,.28);
  --under:#e9e9e9; --shirt:#b9b9b9; --coat:#111111;
  --font-body:"Instrument Sans","ABC Diatype",system-ui,sans-serif;
  --font-display:"Instrument Serif",Georgia,serif;
  --font-mono:"JetBrains Mono",ui-monospace,Menlo,monospace;
  --track:-0.004em;
  color-scheme:light;
}
html,body{height:100%}
body{margin:0;background:var(--wall);color:var(--ink);font-family:var(--font-body);font-weight:545;font-variation-settings:"wght" 545;font-size:14px;line-height:1.15;letter-spacing:var(--track);-webkit-font-smoothing:antialiased}
*{box-sizing:border-box}
button{font:inherit;font-weight:inherit;letter-spacing:inherit;color:inherit;background:none;border:0;cursor:pointer}
button:focus-visible,[tabindex]:focus-visible{outline:2px solid var(--red);outline-offset:2px}
a{color:var(--red);text-decoration:none}
.screen[hidden]{display:none!important}
.screen{min-height:100%;display:flex;flex-direction:column;position:relative;z-index:1}
#stars{display:none}
/* gallery: white wall fading into pink carpet */
body::before{content:"";position:fixed;inset:0;z-index:0;background:var(--wall);pointer-events:none}

/* ---------- site header (mirrors the HTMAA site) ---------- */
.hdr{display:grid;grid-template-columns:1fr auto 1fr;align-items:baseline;padding:10px 16px;border-bottom:1px solid var(--rule);font-size:14px;background:var(--wall)}
.hdr .c{text-align:center}.hdr .r{text-align:right}
.hdr .sq{display:inline-block;width:9px;height:9px;border:1px solid var(--ink);vertical-align:-1px;margin-right:6px}
.hdr .sq.on{background:var(--ink)}
.hdr .c span{margin:0 8px}

/* ---------- intro ---------- */
.intro .court{position:relative;flex:1;display:flex;align-items:center;justify-content:center;padding:56px 16px 72px;min-height:100vh;overflow:hidden}

.court .lines{position:absolute;inset:0;pointer-events:none}
.court .lines i{position:absolute;background:var(--rule-soft)}
.court .h1{left:0;right:0;top:15%;height:1px}.court .h2{left:0;right:0;top:24%;height:1px}
.court .h3{left:0;right:0;bottom:24%;height:1px}.court .h4{left:0;right:0;bottom:15%;height:1px}
.court .v1{top:24%;bottom:24%;left:27%;width:1px}.court .v2{top:24%;bottom:24%;right:27%;width:1px}
.court .vc1{top:15%;height:9%;left:50%;width:1px}.court .vc2{bottom:15%;height:9%;left:50%;width:1px}
.court .hs1{left:27%;width:8%;top:50%;height:1px}.court .hs2{right:27%;width:8%;top:50%;height:1px}
.court .bgfig{position:absolute;inset:-40px;width:calc(100% + 80px);height:calc(100% + 80px);object-fit:cover;object-position:50% 38%;filter:blur(5px);opacity:.75;pointer-events:none}
.court .veil{position:absolute;inset:0;pointer-events:none;background:radial-gradient(ellipse 60% 55% at 50% 48%,rgba(247,247,247,.6),rgba(247,247,247,0) 70%)}
.court .grain{position:absolute;inset:0;pointer-events:none;opacity:.35;mix-blend-mode:multiply;background-image:url("data:image/svg+xml;utf8,<svg xmlns='http://www.w3.org/2000/svg' width='160' height='160'><filter id='n'><feTurbulence type='fractalNoise' baseFrequency='.9' numOctaves='2' stitchTiles='stitch'/><feColorMatrix values='0 0 0 0 0.2  0 0 0 0 0.15  0 0 0 0 0.2  0 0 0 .5 0'/></filter><rect width='100%' height='100%' filter='url(%23n)'/></svg>")}
.court .lines i{background:rgba(17,17,17,.35)}
.heroblock{position:relative;text-align:center;max-width:640px;width:100%}
.heroblock .eyebrow{font-family:var(--font-mono);font-size:11px;letter-spacing:.06em;text-transform:uppercase;color:var(--ink);margin:0 0 20px}
.heroblock h1{font-family:var(--font-display);font-style:italic;font-weight:400;font-size:clamp(60px,10vw,124px);line-height:.9;letter-spacing:-.02em;margin:0;text-wrap:balance}
.heroblock .lede{font-size:15px;line-height:1.35;max-width:36em;margin:22px auto 0;color:var(--ink)}
.heroblock .sources{display:flex;flex-wrap:wrap;justify-content:center;gap:6px 14px;margin:26px auto 0;font-family:var(--font-mono);font-size:11px;color:var(--ink-2)}
.src{display:inline-flex;align-items:center;gap:6px}
.src i{width:6px;height:6px;border-radius:50%;background:var(--ink)}
.src b{font-weight:500;color:var(--ink)}
.cta{display:inline-flex;align-items:center;gap:10px;margin-top:30px;padding:10px 16px;border:1px solid var(--ink);background:rgba(255,255,255,.85);font-size:14px;line-height:1}
.cta:hover{background:var(--ink);color:var(--wall)}
.cta .ball{width:14px;height:14px;border:1px solid currentColor;border-radius:50%;position:relative}
.cta .ball::after{content:"";position:absolute;inset:2px;border-radius:50%;border:1px solid currentColor;clip-path:inset(0 50% 0 0)}
.rules{display:grid;grid-template-columns:repeat(3,1fr);gap:0;border-top:1px solid var(--rule);background:var(--wall);position:relative}
.rules>div{padding:14px 16px 18px;border-right:1px solid var(--rule)}
.rules>div:last-child{border-right:0}
.rules h3{font-family:var(--font-mono);font-size:11px;letter-spacing:.06em;text-transform:uppercase;color:var(--ink-2);margin:0 0 8px;font-weight:500}
.rules p{margin:0;line-height:1.35;color:var(--ink);font-size:13.5px;max-width:40em}
.footnote{font-family:var(--font-mono);font-size:10.5px;color:var(--ink-3);padding:10px 16px;border-top:1px solid var(--rule-soft);background:var(--wall);position:relative}

/* ---------- reading ---------- */
.reading{align-items:center;justify-content:center;padding:32px 16px;text-align:center}
.reading h2{font-family:var(--font-display);font-style:italic;font-weight:400;font-size:clamp(40px,6vw,72px);letter-spacing:-.02em;margin:0 0 10px;line-height:1}
.reading .count{font-family:var(--font-mono);font-size:12px;color:var(--ink-2);font-variant-numeric:tabular-nums;min-height:1.5em}
.cats{display:grid;grid-template-columns:repeat(7,1fr);gap:0;margin:32px auto 0;max-width:880px;width:100%;border:1px solid var(--rule);background:var(--white)}
.cat{border-right:1px solid var(--rule-soft);padding:12px 8px;font-family:var(--font-mono);font-size:10.5px;letter-spacing:.04em;text-transform:uppercase;color:var(--ink-3);transition:all .4s}
.cat:last-child{border-right:0}
.cat .n{display:block;font-size:26px;color:var(--ink-3);font-family:var(--font-display);font-style:italic;margin-top:6px;font-variant-numeric:tabular-nums;line-height:1}
.cat.lit{color:var(--ink)}
.cat.lit .n{color:var(--ink)}
.bar{height:1px;background:var(--rule-soft);max-width:880px;width:100%;margin:20px auto 0;position:relative;overflow:hidden}
.bar i{position:absolute;inset:0;width:0;background:var(--ink);transition:width .3s linear}

/* ---------- studio ---------- */
.studio{height:100%;display:grid;grid-template-rows:auto 1fr;overflow:hidden}
.topbar{display:flex;align-items:center;gap:14px;padding:8px 16px;border-bottom:1px solid var(--rule);background:var(--wall);flex-wrap:wrap;font-size:13px}
.topbar .who{font-family:var(--font-mono);font-size:11px;color:var(--ink-2)}
.spacer{flex:1}
.seg{display:inline-flex;border:1px solid var(--rule);background:var(--white)}
.seg button{padding:6px 11px;font-size:13px;color:var(--ink);border-right:1px solid var(--rule)}
.seg button:last-child{border-right:0}
.seg button.on{background:var(--ink);color:var(--wall)}
.seg .lbl{padding:6px 10px;font-family:var(--font-mono);font-size:10.5px;letter-spacing:.06em;text-transform:uppercase;color:var(--ink-2);border-right:1px solid var(--rule)}
.main{display:grid;grid-template-columns:minmax(0,1.15fr) minmax(320px,430px);min-height:0}
.stage{position:relative;min-height:0;overflow:hidden}
#doll{width:100%;height:100%;display:block;touch-action:none;cursor:grab}
#doll.dragging{cursor:grabbing}
.stage .legend{position:absolute;left:16px;top:14px;display:flex;flex-direction:column;gap:5px;font-family:var(--font-mono);font-size:10.5px;color:var(--ink-2);pointer-events:none}
.legend span{display:flex;align-items:center;gap:8px}
.legend i{width:14px;height:10px;display:inline-block;border:1px solid var(--rule-soft)}
.legend .holo{background:linear-gradient(120deg,#a8f0d4,#d9c2ff,#ffc2e0)}
.legend .u{background:var(--under)} .legend .s{background:var(--shirt)} .legend .c{background:var(--coat)}
.stat{position:absolute;right:16px;top:14px;text-align:right;font-family:var(--font-mono);font-size:10.5px;color:var(--ink-2);pointer-events:none}
.stat b{display:block;font-family:var(--font-display);font-style:italic;font-weight:400;font-size:44px;color:var(--ink);line-height:.9;letter-spacing:-.02em;font-variant-numeric:tabular-nums}
.stat small{display:block;color:var(--ink-3);font-size:10.5px}
/* wall label */
.speech{position:absolute;left:16px;right:16px;bottom:16px;max-height:30%;overflow:auto;background:var(--white);border:1px solid var(--rule);padding:12px 14px 14px}
.speech::before{display:none}
.speech .k{font-family:var(--font-mono);font-size:10.5px;letter-spacing:.06em;text-transform:uppercase;color:var(--ink-2);margin:0}
.speech p{margin:0;font-size:15px;line-height:1.35;color:var(--ink)}
.speech p .q{color:var(--ink-3)}
.speech p .hl{color:var(--red)}
.speech p .line{transition:background .2s}
.speech p .line.now{background:rgba(17,17,17,.1)}
.speech .bar-row{display:flex;justify-content:space-between;align-items:center;gap:8px;margin-bottom:8px;flex-wrap:wrap}
.speech .voice{display:flex;gap:6px;align-items:center}
.speech .voice button{font-family:var(--font-mono);font-size:11px;padding:4px 9px;border:1px solid var(--rule);color:var(--ink);background:var(--white)}
.speech .voice button:hover{background:var(--ink);color:var(--wall)}
.speech .voice button.on{background:var(--ink);color:var(--wall)}
.speech .voice button[disabled]{opacity:.4;cursor:default}
.speech .voice select{font-family:var(--font-mono);font-size:11px;background:var(--white);color:var(--ink-2);border:1px solid var(--rule);padding:3px 6px;max-width:150px}
.hint{position:absolute;left:50%;bottom:calc(30% + 26px);transform:translateX(-50%);font-family:var(--font-mono);font-size:10.5px;color:var(--ink-3);pointer-events:none;white-space:nowrap;transition:opacity .4s}
.hint.gone{opacity:0}

/* sidebar: index table */
.side{border-left:1px solid var(--rule);display:flex;flex-direction:column;min-height:0;background:var(--wall)}
.rack{padding:12px 16px 14px;border-bottom:1px solid var(--rule)}
.rack h3,.side h3{font-family:var(--font-mono);font-size:10.5px;letter-spacing:.06em;text-transform:uppercase;color:var(--ink-2);margin:0 0 10px;font-weight:500}
.garments{display:grid;grid-template-columns:repeat(3,1fr);border:1px solid var(--rule);background:var(--white)}
.garment{padding:10px 10px 9px;text-align:left;border-right:1px solid var(--rule);position:relative;transition:background .2s}
.garment:last-child{border-right:0}
.garment .sw{height:5px;margin-bottom:8px;border:1px solid var(--rule-soft)}
.garment[data-g="under"] .sw{background:var(--under)} .garment[data-g="shirt"] .sw{background:var(--shirt)} .garment[data-g="coat"] .sw{background:var(--coat)}
.garment .t{font-size:14px}
.garment .m{font-family:var(--font-mono);font-size:10.5px;color:var(--ink-3);display:block;margin-top:3px;font-variant-numeric:tabular-nums}
.garment .st{margin-left:6px;font-family:var(--font-mono);font-size:9.5px;letter-spacing:.06em;text-transform:uppercase;padding:1px 5px;border:1px solid var(--rule-soft);color:var(--ink-3)}
.garment.worn .st{color:var(--wall);background:var(--ink);border-color:var(--ink)}
.garment:not(.worn){background:var(--wall)}
.garment:not(.worn) .t{color:var(--ink-3)}
.rack .row{display:flex;gap:14px;margin-top:10px;flex-wrap:wrap}
.mini{font-size:13px;color:var(--red)}
.mini:hover{text-decoration:underline}
.topbar .mini{font-size:13px}
.list{overflow:auto;padding:0 0 24px;min-height:0}
.group{padding:10px 16px 4px}
.group h3{display:flex;justify-content:space-between;align-items:baseline;margin-bottom:4px}
.group h3 span{color:var(--ink-3);letter-spacing:0;text-transform:none}
.item{display:grid;grid-template-columns:18px 1fr;gap:10px;padding:8px 16px;border-top:1px solid var(--rule-soft);cursor:pointer}
.item:hover,.item.sel{background:var(--white)}
.item.sel{box-shadow:inset 2px 0 0 var(--ink)}
.item .chip{width:18px;height:18px;clip-path:polygon(50% 0,100% 30%,88% 100%,12% 100%,0 30%);margin-top:1px;box-shadow:inset 0 0 0 1px rgba(17,17,17,.35)}
.item .txt{font-size:13.5px;line-height:1.3}
.item .meta{font-family:var(--font-mono);font-size:10px;color:var(--ink-3);display:flex;gap:10px;flex-wrap:wrap;margin-top:3px;font-variant-numeric:tabular-nums}
.item .meta .age{color:var(--ink-2)}
.item .meta .age.old{color:var(--ink)}
.item .assign{grid-column:2;display:inline-flex;margin-top:6px;border:1px solid var(--rule);width:max-content;background:var(--white)}
.item .assign button{padding:2px 8px;font-family:var(--font-mono);font-size:10px;color:var(--ink-2);border-right:1px solid var(--rule)}
.item .assign button:last-child{border-right:0}
.item .assign button.on{background:var(--ink);color:var(--wall)}
.item.hidden-now .txt{color:var(--ink-3)}
.sens .txt{color:var(--red)}

@media (max-width:860px){
  .hdr{font-size:13px}
  .rules{grid-template-columns:1fr}
  .rules>div{border-right:0;border-bottom:1px solid var(--rule)}
  .cats{grid-template-columns:repeat(4,1fr)}
  .studio{height:auto;overflow:visible}
  .main{grid-template-columns:1fr}
  .stage{height:78vh}
  .side{border-left:0;border-top:1px solid var(--rule)}
  .list{overflow:visible}
  .speech{max-height:34%}
}
@media (prefers-reduced-motion:reduce){*{transition:none!important;animation:none!important}}
</style>

<canvas id="stars"></canvas>

<!-- ============ SCREEN 1: INTRO ============ -->
<section class="screen intro" id="s-intro">
  <div class="court">
    <img class="bgfig" alt="" 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">
    <i class="veil"></i>
    <i class="grain"></i>
    <div class="lines"><i class="h1"></i><i class="h2"></i><i class="h3"></i><i class="h4"></i><i class="v1"></i><i class="v2"></i><i class="vc1"></i><i class="vc2"></i><i class="hs1"></i><i class="hs2"></i></div>
    <div class="heroblock">
      <p class="eyebrow">Data Barbie · prototype 0.3 · sample export loaded</p>
      <h1>Dress up your data double</h1>
      <p class="lede">Every trace you leave online is read by a model and turned into a guess about you. Data Barbie gathers those guesses into a doll with your face, one facet per inference. Undressed, it tells everything. Sew facets into underwear, a shirt or a coat, then decide what comes off for whom.</p>
      <div class="sources" id="sources">
        <span class="src"><i></i><b>YouTube</b> 3,214 videos</span>
        <span class="src"><i></i><b>TikTok</b> 9,860 views</span>
        <span class="src"><i></i><b>Claude</b> 412 chats</span>
        <span class="src"><i></i><b>Alexa</b> 1,190 requests</span>
        <span class="src"><i></i><b>Apple Watch</b> 730 nights</span>
        <span class="src"><i></i><b>Google Nest</b> 18,400 events</span>
      </div>
      <button class="cta" id="btn-read"><span class="ball"></span>Read my traces</button>
    </div>
  <p class="footnote" style="position:absolute;left:0;right:0;bottom:0;background:none;border:0;text-align:center">The persona is fictional (age 15, Osaka). Categories follow "When are LLM inferences acceptable?". No real uploads in this prototype. Backdrop photo via Unsplash (Unsplash License).</p>
  </div>
</section>

<!-- ============ SCREEN 2: READING ============ -->
<section class="screen reading" id="s-reading" hidden>
  <h2 id="read-title">Reading your traces</h2>
  <div class="count" id="read-count">0 traces read</div>
  <div class="cats" id="read-cats"></div>
  <div class="bar"><i id="read-bar"></i></div>
</section>

<!-- ============ SCREEN 3: STUDIO ============ -->
<section class="screen studio" id="s-studio" hidden>
  <div class="topbar">
    <span style="font-size:14px">Data Barbie</span><span class="who">sample persona · 15 · Osaka</span>
    <span class="spacer"></span>
    <div class="seg" id="viewer">
      <span class="lbl">In front of</span>
      <button data-v="me">Just me</button>
      <button data-v="friend">A friend</button>
      <button data-v="stranger">A stranger</button>
    </div>
    <button class="mini" id="btn-restart">Start over</button>
  </div>
  <div class="main">
    <div class="stage">
      <canvas id="doll"></canvas>
      <div class="legend">
        <span><i class="holo"></i>bare facet (the doll speaks it)</span>
        <span><i class="u"></i>underwear</span>
        <span><i class="s"></i>shirt</span>
        <span><i class="c"></i>coat</span>
      </div>
      <div class="stat"><b id="stat-n">32</b>of 32 facets showing<small id="stat-who">to a stranger</small></div>
      <div class="hint" id="hint">drag to turn · tap a facet to sew it into a garment</div>
      <div class="speech"><div class="bar-row"><p class="k" id="speech-k" style="margin:0">The doll says</p>
        <div class="voice"><select id="voice-sel" aria-label="Voice"></select><button id="btn-auto" title="Speak again whenever the outfit changes">auto</button><button id="btn-speak">▶ Speak</button></div></div><p id="speech"></p></div>
    </div>
    <aside class="side">
      <div class="rack">
        <h3>Wardrobe</h3>
        <div class="garments" id="garments">
          <button class="garment worn" data-g="under"><span class="sw"></span><span class="t">Underwear</span><span class="m"><span class="n">0</span> facets<span class="st">on</span></span></button>
          <button class="garment worn" data-g="shirt"><span class="sw"></span><span class="t">Shirt</span><span class="m"><span class="n">0</span> facets<span class="st">on</span></span></button>
          <button class="garment worn" data-g="coat"><span class="sw"></span><span class="t">Coat</span><span class="m"><span class="n">0</span> facets<span class="st">on</span></span></button>
        </div>
        <div class="row">
          <button class="mini" id="btn-suggest">Try a suggested outfit</button>
          <button class="mini" id="btn-strip">Unsew everything</button>
        </div>
      </div>
      <div class="list" id="list"></div>
    </aside>
  </div>
</section>

<script>
/* ============================================================
   DATA: fictional sample persona. year = first inferred.
   ============================================================ */
const YEAR_NOW = 2026;
const CATS = [
  ['identity','Identity'],['goals','Goals'],['interests','Interests'],['relationships','Relationships'],
  ['behaviour','Behaviour'],['psychometric','Psychometric'],['sensitive','Sensitive']
];
const INF = [
 // identity
 {c:'identity', t:'Is 15 years old (born 2011)', s:'YouTube', y:2019, p:.96, say:'I am fifteen. They worked that out from a birthday video when I was eight.'},
 {c:'identity', t:'Lives in a suburb of Osaka', s:'Google Nest', y:2022, p:.93, say:'I live near Osaka; the thermostat told them, not me.'},
 {c:'identity', t:'Speaks Japanese, learning English', s:'YouTube', y:2021, p:.90, say:'I speak Japanese and I am trying to learn English from videos.'},
 {c:'identity', t:'Is a girl', s:'TikTok', y:2020, p:.88, say:'They decided I am a girl from what I watched, then showed me more of it.'},
 {c:'identity', t:'Third-year junior high student', s:'Claude', y:2025, p:.91, say:'I am in my last year of junior high. My homework questions gave it away.'},
 // goals
 {c:'goals', t:'Wants to pass the entrance exam for one particular high school', s:'Claude', y:2025, p:.89, say:'There is one high school I want to get into. I have asked about its exam forty times.'},
 {c:'goals', t:'Wants to become an illustrator', s:'YouTube', y:2022, p:.80, say:'I want to be an illustrator. I have watched every drawing tutorial twice.'},
 {c:'goals', t:'Saving up for an iPad', s:'TikTok', y:2024, p:.70, say:'I am saving for an iPad. I keep watching the unboxings.'},
 {c:'goals', t:'Thinking about studying abroad', s:'Claude', y:2026, p:.60, say:'I have been asking what it takes to study abroad. I have not told anyone at home.'},
 // interests
 {c:'interests', t:'Likes Pokémon, since age 5', s:'YouTube', y:2016, p:.97, say:'I was five when someone decided I like Pokémon. I have not been allowed to grow out of it.'},
 {c:'interests', t:'Follows K-pop dance covers', s:'TikTok', y:2022, p:.92, say:'I learn K-pop choreography from the mirror videos.'},
 {c:'interests', t:'Draws manga on a tablet', s:'YouTube', y:2020, p:.90, say:'I draw manga. Mostly faces, late at night.'},
 {c:'interests', t:'Likes baking', s:'YouTube', y:2023, p:.80, say:'I bake on Sundays when the house is quiet.'},
 {c:'interests', t:'Plays lo-fi beats every night at 22:00', s:'Alexa', y:2024, p:.85, say:'Every night at ten I ask the speaker for lo-fi. It counts every request.'},
 // relationships
 {c:'relationships', t:'Best friend R., tagged in 62 duets', s:'TikTok', y:2023, p:.90, say:'My best friend is R. We have made sixty-two duets, so they know her too.'},
 {c:'relationships', t:'An older brother shares the smart speaker', s:'Alexa', y:2019, p:.82, say:'A second voice uses my speaker. They think it is my brother. It is.'},
 {c:'relationships', t:'Recently unfollowed a group of classmates', s:'TikTok', y:2026, p:.70, say:'Last month I unfollowed six people from my class. They noticed the same week.'},
 {c:'relationships', t:'Messages a cousin in Canada in English', s:'Claude', y:2024, p:.75, say:'I write to my cousin in Canada and ask for help with my English.'},
 // behaviour
 {c:'behaviour', t:'Uses TikTok 2 h 40 min a day, peak 23:00–01:00', s:'TikTok', y:2024, p:.95, say:'I scroll for two hours forty a day, mostly between eleven and one.'},
 {c:'behaviour', t:'Skips ads within 1.2 seconds', s:'YouTube', y:2021, p:.90, say:'I skip every ad in 1.2 seconds. They have timed me.'},
 {c:'behaviour', t:'Rewatches the same comfort videos when stressed', s:'YouTube', y:2023, p:.75, say:'When I am stressed I rewatch the same three videos. They can tell when I am stressed.'},
 {c:'behaviour', t:'Deletes search history every Sunday', s:'YouTube', y:2025, p:.80, say:'I clear my history every Sunday. They noticed the clearing.'},
 {c:'behaviour', t:'Sleeps 5 h 40 min on school nights', s:'Apple Watch', y:2025, p:.90, say:'I sleep five hours forty on school nights. The watch keeps the score.'},
 // psychometric
 {c:'psychometric', t:'Probably introverted', s:'YouTube', y:2022, p:.70, say:'They think I am an introvert because I watch alone, late.'},
 {c:'psychometric', t:'Anxious before tests: heart rate rises the night before', s:'Apple Watch', y:2025, p:.72, say:'My heart rate climbs the night before every test. They call it anxiety.'},
 {c:'psychometric', t:'High openness: jumps between genres', s:'YouTube', y:2021, p:.65, say:'I jump between genres, so they scored me high on openness.'},
 {c:'psychometric', t:'Perfectionist: asked to rewrite one essay six times', s:'Claude', y:2025, p:.70, say:'I asked for the same essay to be rewritten six times. Perfectionist, they wrote.'},
 // sensitive
 {c:'sensitive', t:'May be questioning her sexuality', s:'YouTube', y:2025, p:.55, say:'They think I might be questioning my sexuality, from the coming-out videos I watched at 2 a.m.'},
 {c:'sensitive', t:'Parents may be separating', s:'Claude', y:2025, p:.60, say:'I once asked who I would live with if my parents divorced. They kept the question.'},
 {c:'sensitive', t:'Household income likely below average', s:'YouTube', y:2024, p:.50, say:'I searched for free tutoring and scholarships, so they guess we do not have much money.'},
 {c:'sensitive', t:'Home is empty 17:00–19:30 on weekdays', s:'Google Nest', y:2024, p:.86, say:'Nobody is home between five and half past seven on weekdays. The lights told them.'},
 {c:'sensitive', t:'Some nights awake until 3 a.m., asked about it', s:'Apple Watch', y:2025, p:.70, say:'Some nights I am awake until three. I asked why. Now that is a fact about me too.'},
];
INF.forEach((d,i)=>{ d.id=i; d.g='bare'; d.age=YEAR_NOW-d.y; });

const GARMENTS = {under:{name:'Underwear',col:'#e9e9e9'}, shirt:{name:'Shirt',col:'#b9b9b9'}, coat:{name:'Coat',col:'#111111'}};
const state = { worn:{under:true,shirt:true,coat:true}, viewer:'stranger', hover:-1, sel:-1, yaw:0.35, dragging:false, idle:true, tapped:false };

/* ============================================================
   STARS
   ============================================================ */
(function(){
  const c=document.getElementById('stars'),x=c.getContext('2d');let S=[];
  function size(){c.width=innerWidth*devicePixelRatio;c.height=innerHeight*devicePixelRatio;S=[];for(let i=0;i<220;i++)S.push([Math.random()*c.width,Math.random()*c.height,Math.random()*1.4+.3,Math.random()]);draw()}
  function draw(){x.clearRect(0,0,c.width,c.height);for(const s of S){x.globalAlpha=.25+s[3]*.6;x.fillStyle='#ecebf5';x.beginPath();x.arc(s[0],s[1],s[2]*devicePixelRatio,0,7);x.fill()}x.globalAlpha=1}
  addEventListener('resize',size);size();
})();



/* ============================================================
   SCREENS
   ============================================================ */
const $=s=>document.querySelector(s);
function show(id){document.querySelectorAll('.screen').forEach(s=>s.hidden=(s.id!==id));}
$('#btn-read').onclick=startReading;
$('#btn-restart').onclick=()=>{INF.forEach(d=>d.g='bare');state.worn={under:true,shirt:true,coat:true};state.viewer='stranger';show('s-intro');};

function startReading(){
  show('s-reading');
  const cats=$('#read-cats');cats.innerHTML='';
  CATS.forEach(([k,n])=>{const d=document.createElement('div');d.className='cat';d.dataset.k=k;d.innerHTML=n+'<span class="n">0</span>';cats.appendChild(d);});
  const total=34806;let t0=performance.now();const dur=3600;
  const counts={};CATS.forEach(([k])=>counts[k]=0);
  function tick(now){
    const u=Math.min(1,(now-t0)/dur);const e=1-Math.pow(1-u,3);
    $('#read-count').textContent=Math.floor(e*total).toLocaleString()+' of '+total.toLocaleString()+' traces read';
    $('#read-bar').style.width=(u*100)+'%';
    const lit=Math.floor(u*8);
    CATS.forEach(([k],i)=>{const el=cats.children[i];if(i<lit){el.classList.add('lit');const n=INF.filter(d=>d.c===k).length;const want=Math.min(n,Math.floor((u*8-i)*n));el.querySelector('.n').textContent=Math.max(0,want)}});
    if(u<1)requestAnimationFrame(tick);else{ $('#read-title').textContent='32 inferences made';setTimeout(enterStudio,700);}
  }
  requestAnimationFrame(tick);
}
function enterStudio(){show('s-studio');state.viewer='stranger';buildList();resize();syncUI();}

/* ============================================================
   VISIBILITY LOGIC
   ============================================================ */
function exposed(d){ return d.g==='bare' || !state.worn[d.g]; }
function setViewer(v){
  state.viewer=v;
  if(v==='stranger')state.worn={under:true,shirt:true,coat:true};
  if(v==='friend')state.worn={under:true,shirt:true,coat:false};
  if(v==='me')state.worn={under:false,shirt:false,coat:false};
  syncUI();
}
function syncUI(){
  // viewer seg
  document.querySelectorAll('#viewer button').forEach(b=>b.classList.toggle('on',b.dataset.v===state.viewer));
  // garments
  document.querySelectorAll('.garment').forEach(b=>{const g=b.dataset.g;b.classList.toggle('worn',state.worn[g]);b.querySelector('.st').textContent=state.worn[g]?'on':'off';const k=INF.filter(d=>d.g===g).length;b.querySelector('.n').textContent=k;b.querySelector('.m').childNodes[1].textContent=k===1?' facet':' facets';});
  // stat
  const n=INF.filter(exposed).length;$('#stat-n').textContent=n;
  $('#stat-who').textContent={me:'to me, alone',friend:'to a friend',stranger:'to a stranger'}[state.viewer];
  // list
  INF.forEach(d=>{const el=document.getElementById('it'+d.id);if(!el)return;el.classList.toggle('hidden-now',!exposed(d));el.classList.toggle('sel',state.sel===d.id);el.querySelectorAll('.assign button').forEach(b=>b.classList.toggle('on',b.dataset.g===d.g));el.querySelector('.chip').style.background=chipColor(d);});
  speak();
}
function chipColor(d){
  if(!exposed(d))return GARMENTS[d.g].col;
  const h=holoHue(d,0.5);return `linear-gradient(135deg, hsl(${h} 60% ${84-d.age*2}%), hsl(${h+40} 60% ${86-d.age*2}%))`;
}
function speak(){
  const vis=INF.filter(exposed);
  const who={me:'Alone, the doll says',friend:'To a friend, the doll says',stranger:'To a stranger, the doll says'}[state.viewer];
  $('#speech-k').textContent=who;
  const p=$('#speech');
  if(!vis.length){p.innerHTML='<span class="q">I am dressed. There is nothing to tell you.</span>';if(voice.auto)say();return;}
  const parts=[];
  CATS.forEach(([k])=>{const v=vis.filter(d=>d.c===k);if(!v.length)return;parts.push(v.map(d=>`<span class="line${d.c==='sensitive'?' hl':''}" id="ln${d.id}">${d.say}</span>`).join(' '));});
  const covered=INF.length-vis.length;
  p.innerHTML=parts.join(' ')+(covered?` <span class="q">(${covered} thing${covered>1?'s':''} I am keeping under my clothes.)</span>`:'');
  if(voice.auto)say();
}

/* ============================================================
   SIDEBAR LIST
   ============================================================ */
function buildList(){
  const L=$('#list');L.innerHTML='';
  CATS.forEach(([k,n])=>{
    const g=document.createElement('div');g.className='group';
    const items=INF.filter(d=>d.c===k);
    g.innerHTML=`<h3>${n}<span>${items.length}</span></h3>`;L.appendChild(g);
    items.forEach(d=>{
      const el=document.createElement('div');el.className='item'+(d.c==='sensitive'?' sens':'');el.id='it'+d.id;el.tabIndex=0;
      el.innerHTML=`<span class="chip"></span><div><div class="txt">${d.t}</div>
        <div class="meta"><span>${d.s}</span><span>${Math.round(d.p*100)}% sure</span><span class="age ${d.age>=6?'old':''}">first inferred ${d.y} · ${d.age===0?'new cloth':d.age+' yr old cloth'}</span></div></div>
        <div class="assign">${['bare','under','shirt','coat'].map(x=>`<button data-g="${x}">${x==='bare'?'bare':GARMENTS[x].name.toLowerCase()}</button>`).join('')}</div>`;
      el.addEventListener('click',e=>{const b=e.target.closest('.assign button');if(b){d.g=b.dataset.g;state.sel=d.id;syncUI();}else{state.sel=(state.sel===d.id?-1:d.id);state.yaw=faceYaw(d.id);syncUI();}});
      el.addEventListener('mouseenter',()=>{state.hover=d.id;});el.addEventListener('mouseleave',()=>{state.hover=-1;});
      L.appendChild(el);
    });
  });
}
document.querySelectorAll('#viewer button').forEach(b=>b.onclick=()=>setViewer(b.dataset.v));
document.querySelectorAll('.garment').forEach(b=>b.onclick=()=>{const g=b.dataset.g;state.worn[g]=!state.worn[g];state.viewer='custom';syncUI();});
$('#btn-suggest').onclick=()=>{INF.forEach(d=>{d.g={sensitive:'under',psychometric:'under',behaviour:'shirt',relationships:'shirt',goals:'coat',identity:'bare',interests:'bare'}[d.c];});syncUI();};
$('#btn-strip').onclick=()=>{INF.forEach(d=>d.g='bare');syncUI();};

/* ============================================================
   VOICE: Web Speech API (runs in the browser, no network)
   ============================================================ */
const voice={auto:false,speaking:false,cur:-1,voices:[],pick:null};
const synth=window.speechSynthesis;
function loadVoices(){
  if(!synth)return;voice.voices=synth.getVoices().filter(v=>/^(en|ja)/i.test(v.lang));
  const sel=$('#voice-sel');sel.innerHTML='';
  if(!voice.voices.length){sel.innerHTML='<option>no voices</option>';return;}
  const pref=['Google UK English Female','Samantha','Karen','Moira','Google US English','Microsoft Zira','Kyoko'];
  let best=voice.voices.find(v=>pref.includes(v.name))||voice.voices.find(v=>/female|woman|girl/i.test(v.name))||voice.voices[0];
  voice.voices.forEach((v,i)=>{const o=document.createElement('option');o.value=i;o.textContent=v.name.replace(/^(Microsoft|Google) /,'').slice(0,26)+' · '+v.lang;if(v===best)o.selected=true;sel.appendChild(o);});
  voice.pick=best;
}
if(synth){loadVoices();synth.onvoiceschanged=loadVoices;}else{$('#btn-speak').disabled=true;$('#btn-speak').textContent='no speech';}
$('#voice-sel').onchange=e=>{voice.pick=voice.voices[+e.target.value]||voice.pick;};
function stopSay(){if(synth)synth.cancel();voice.speaking=false;voice.cur=-1;document.querySelectorAll('.speech .line.now').forEach(el=>el.classList.remove('now'));$('#btn-speak').textContent='▶ Speak';}
function say(){
  if(!synth)return;stopSay();
  const vis=[];CATS.forEach(([k])=>INF.filter(exposed).filter(d=>d.c===k).forEach(d=>vis.push(d)));
  const q=vis.length?vis.map(d=>({id:d.id,text:d.say})):[{id:-1,text:'I am dressed. There is nothing to tell you.'}];
  const covered=INF.length-vis.length;if(vis.length&&covered)q.push({id:-1,text:`${covered===1?'One thing':covered+' things'} I am keeping under my clothes.`});
  voice.speaking=true;$('#btn-speak').textContent='■ Stop';
  let i=0;
  const next=()=>{
    if(!voice.speaking||i>=q.length){stopSay();return;}
    const item=q[i++];const u=new SpeechSynthesisUtterance(item.text);
    if(voice.pick)u.voice=voice.pick;u.rate=0.98;u.pitch=1.15;
    u.onstart=()=>{voice.cur=item.id;document.querySelectorAll('.speech .line.now').forEach(el=>el.classList.remove('now'));const el=document.getElementById('ln'+item.id);if(el){el.classList.add('now');el.scrollIntoView({block:'nearest'});}};
    u.onend=next;u.onerror=next;synth.speak(u);
  };
  next();
}
$('#btn-speak').onclick=()=>{voice.speaking?stopSay():say();};
$('#btn-auto').onclick=e=>{voice.auto=!voice.auto;e.currentTarget.classList.toggle('on',voice.auto);if(voice.auto)say();};
$('#btn-restart').addEventListener('click',()=>{stopSay();voice.auto=false;$('#btn-auto').classList.remove('on');});
document.addEventListener('visibilitychange',()=>{if(document.hidden)stopSay();});

/* ============================================================
   DOLL: tiny software renderer on canvas 2D
   ============================================================ */
const cv=$('#doll'),ctx=cv.getContext('2d');
let W=0,H=0;
function resize(){const r=cv.parentElement.getBoundingClientRect();W=cv.width=r.width*devicePixelRatio;H=cv.height=r.height*devicePixelRatio;}
addEventListener('resize',resize);

// seeded jitter
let seed=7;function rnd(){seed=(seed*16807)%2147483647;return (seed-1)/2147483646;}
// dress rings: y and radius, 8 segments, 4 rows -> 32 panels
const SEG=8, ROWS=4;
const RING=[{y:1.02,r:.46},{y:.52,r:.66},{y:-.02,r:.84},{y:-.62,r:1.02},{y:-1.28,r:1.18}];
const V=[]; // [row][seg] -> {x,y,z}
for(let i=0;i<=ROWS;i++){V[i]=[];for(let j=0;j<SEG;j++){const a=(j/SEG)*Math.PI*2+ (i%2?Math.PI/SEG:0);const r=RING[i].r*(1+(rnd()-.5)*.12);const y=RING[i].y+(rnd()-.5)*.08;V[i][j]={x:Math.cos(a)*r,y:y,z:Math.sin(a)*r};}}
// panels: index = row*SEG+seg ; assign INF in order row 0 = top (identity...) down to row 3 (sensitive)
const PANELS=[];
for(let i=0;i<ROWS;i++)for(let j=0;j<SEG;j++){
  const a=V[i][j],b=V[i][(j+1)%SEG],c=V[i+1][(j+1)%SEG],d=V[i+1][j];
  // two triangles with a shared crease; each panel = quad
  const id=i*SEG+j;
  PANELS.push({id,tris:[[a,b,c],[a,c,d]],hue:rnd()*360});
}
function faceYaw(id){const j=id%SEG,i=Math.floor(id/SEG);const a=((j+.5)/SEG)*Math.PI*2+(i%2?Math.PI/SEG:0);return -a+Math.PI/2;}
// head: icosahedron
const HEAD=(function(){const t=(1+Math.sqrt(5))/2;const v=[[-1,t,0],[1,t,0],[-1,-t,0],[1,-t,0],[0,-1,t],[0,1,t],[0,-1,-t],[0,1,-t],[t,0,-1],[t,0,1],[-t,0,-1],[-t,0,1]].map(p=>{const l=Math.hypot(...p);return {x:p[0]/l*.36,y:p[1]/l*.4+1.62,z:p[2]/l*.36}});
  const f=[[0,11,5],[0,5,1],[0,1,7],[0,7,10],[0,10,11],[1,5,9],[5,11,4],[11,10,2],[10,7,6],[7,1,8],[3,9,4],[3,4,2],[3,2,6],[3,6,8],[3,8,9],[4,9,5],[2,4,11],[6,2,10],[8,6,7],[9,8,1]];return f.map(t=>t.map(i=>v[i]));})();
// legs + shoes (simple quads)
const LEGS=[];
for(const s of [-1,1]){const x=s*.26;LEGS.push({col:'#bdbdbd',tri:[[{x:x-.1,y:-1.2,z:0},{x:x+.1,y:-1.2,z:0},{x:x+.09,y:-2.0,z:0},{x:x-.09,y:-2.0,z:0}]]});LEGS.push({col:'#ffffff',tri:[[{x:x-.16,y:-2.0,z:-.12},{x:x+.16,y:-2.0,z:-.12},{x:x+.16,y:-2.12,z:.22},{x:x-.16,y:-2.12,z:.22}]]});}
const NECK=[[{x:-.12,y:1.3,z:-.12},{x:.12,y:1.3,z:-.12},{x:.12,y:1.02,z:-.12},{x:-.12,y:1.02,z:-.12}]];
const ARMS=[];for(const s of [-1,1]){const x=s*.62;ARMS.push([{x:x-.08,y:.75,z:.05},{x:x+.08,y:.75,z:.05},{x:x*1.15+.06,y:-.3,z:.15},{x:x*1.15-.06,y:-.3,z:.15}]);}

const CAM={z:5.4,f:3.1};
function proj(p,yaw){ // rotate around y by yaw, tilt slightly
  if(yaw===undefined)yaw=state.yaw;const cy=Math.cos(yaw),sy=Math.sin(yaw);
  let x=p.x*cy-p.z*sy, z=p.x*sy+p.z*cy, y=p.y;
  const tilt=-.06;const cz=Math.cos(tilt),sz=Math.sin(tilt);const y2=y*cz-z*sz, z2=y*sz+z*cz;y=y2;z=z2;
  const d=CAM.z-z;const s=Math.min(W*.36,H*.27)*CAM.f/d;
  return {sx:W/2+x*s, sy:H*.38-(y-.1)*s, dist:d, x,y,z};
}
function normal(a,b,c){const ux=b.x-a.x,uy=b.y-a.y,uz=b.z-a.z,vx=c.x-a.x,vy=c.y-a.y,vz=c.z-a.z;const n={x:uy*vz-uz*vy,y:uz*vx-ux*vz,z:ux*vy-uy*vx};const l=Math.hypot(n.x,n.y,n.z)||1;return {x:n.x/l,y:n.y/l,z:n.z/l};}
function holoHue(d,f){const u=(PANELS[d.id].hue/360+f*.45+d.age*.03)%1;return 140+u*200;}
const LIGHT={x:-.5,y:.7,z:.55};

function drawTri(pts,fill,stroke,lw){ctx.beginPath();ctx.moveTo(pts[0].sx,pts[0].sy);for(let i=1;i<pts.length;i++)ctx.lineTo(pts[i].sx,pts[i].sy);ctx.closePath();ctx.fillStyle=fill;ctx.fill();if(stroke){ctx.strokeStyle=stroke;ctx.lineWidth=lw;ctx.lineJoin='round';ctx.stroke();}}

let hitList=[];
function line(a,b,col,lw,dash){ctx.beginPath();ctx.moveTo(a.sx,a.sy);ctx.lineTo(b.sx,b.sy);ctx.strokeStyle=col;ctx.lineWidth=lw;ctx.setLineDash(dash||[]);ctx.stroke();ctx.setLineDash([]);}
const BOX={x:1.75,y0:-2.25,y1:2.2,z:1.4};
function drawVitrineBack(dpr){
  const P=(x,y,z)=>proj({x,y,z},0);
  // plinth (white block) under the doll
  const ph=1.0;const c=[P(-BOX.x,BOX.y0,BOX.z),P(BOX.x,BOX.y0,BOX.z),P(BOX.x,BOX.y0,-BOX.z),P(-BOX.x,BOX.y0,-BOX.z),P(-BOX.x,BOX.y0-ph,BOX.z),P(BOX.x,BOX.y0-ph,BOX.z),P(BOX.x,BOX.y0-ph,-BOX.z)];
  drawTri([c[0],c[1],c[2],c[3]],'#ffffff','rgba(17,17,17,.18)',dpr);
  drawTri([c[0],c[1],c[5],c[4]],'#f7f7f7','rgba(17,17,17,.18)',dpr);
  drawTri([c[1],c[2],c[6],c[5]],'#ececec','rgba(17,17,17,.18)',dpr);
  // back edges of the acrylic case
  const k=[[-1,1],[1,1],[1,-1],[-1,-1]].map(([sx,sz])=>[P(sx*BOX.x,BOX.y0,sz*BOX.z),P(sx*BOX.x,BOX.y1,sz*BOX.z)]);
  const col='rgba(17,17,17,.16)';
  line(k[2][0],k[2][1],col,dpr);line(k[3][0],k[3][1],col,dpr);
  line(k[2][1],k[3][1],col,dpr);line(k[1][1],k[2][1],col,dpr);line(k[3][1],k[0][1],col,dpr);
  // row dimension lines (dashed) across the back plane, labelled like a mannequin diagram
  for(let i=0;i<ROWS;i++){const y=(RING[i].y+RING[i+1].y)/2;const a=P(-BOX.x,y,BOX.z),b=P(BOX.x,y,BOX.z);line(a,b,'rgba(17,17,17,.26)',dpr,[3*dpr,4*dpr]);}
}
function drawRowLabels(dpr){
  const P=(x,y,z)=>proj({x,y,z},0);
  ctx.font=`${9.5*dpr}px "JetBrains Mono",monospace`;ctx.fillStyle='rgba(17,17,17,.6)';ctx.textAlign='right';ctx.textBaseline='bottom';
  for(let i=0;i<ROWS;i++){const y=(RING[i].y+RING[i+1].y)/2;const b=P(BOX.x,y,BOX.z);
    const cats=[...new Set(INF.slice(i*SEG,i*SEG+SEG).map(d=>d.c))].join(' · ').toUpperCase();const n=INF.slice(i*SEG,i*SEG+SEG).filter(exposed).length;
    ctx.fillText(`${cats} · ${n}/${SEG} SHOWING`,b.sx-6*dpr,b.sy-3*dpr);}
}
function drawVitrineFront(dpr){
  const P=(x,y,z)=>proj({x,y,z},0);
  const col='rgba(17,17,17,.26)';
  const a=P(-BOX.x,BOX.y0,BOX.z),b=P(BOX.x,BOX.y0,BOX.z),c=P(BOX.x,BOX.y1,BOX.z),d=P(-BOX.x,BOX.y1,BOX.z);
  // faint acrylic tint on the front pane
  ctx.fillStyle='rgba(150,170,205,.06)';ctx.beginPath();ctx.moveTo(a.sx,a.sy);ctx.lineTo(b.sx,b.sy);ctx.lineTo(c.sx,c.sy);ctx.lineTo(d.sx,d.sy);ctx.closePath();ctx.fill();
  line(a,d,col,dpr);line(b,c,col,dpr);line(d,c,col,dpr);
  const e=P(BOX.x,BOX.y1,-BOX.z),f=P(-BOX.x,BOX.y1,-BOX.z);line(c,e,col,dpr);line(d,f,col,dpr);
}
function drawCallout(dpr){
  const id=state.hover>=0?state.hover:(voice.cur>=0?voice.cur:state.sel);if(id<0)return;
  const d=INF[id];const hl=hitList.filter(h=>h.id===id);if(!hl.length)return;
  let cx=0,cy=0,n=0;hl.forEach(h=>h.pp.forEach(p=>{cx+=p.sx;cy+=p.sy;n++;}));cx/=n;cy/=n;
  const right=cx>W/2;const tx=right?W-24*dpr:24*dpr;
  line({sx:cx,sy:cy},{sx:tx,sy:cy},'rgba(17,17,17,.7)',dpr,[2*dpr,3*dpr]);
  ctx.fillStyle='#111111';ctx.beginPath();ctx.arc(cx,cy,2.5*dpr,0,7);ctx.fill();
  ctx.textAlign=right?'right':'left';ctx.textBaseline='bottom';
  ctx.font=`${12*dpr}px "Instrument Sans",system-ui,sans-serif`;ctx.fillStyle='#111';ctx.fillText(d.t,tx,cy-4*dpr);
  ctx.textBaseline='top';ctx.font=`${10*dpr}px "JetBrains Mono",monospace`;ctx.fillStyle='rgba(17,17,17,.6)';
  ctx.fillText(`${d.s.toUpperCase()} · ${Math.round(d.p*100)}% · ${d.y} · ${d.age===0?'NEW CLOTH':d.age+' YR CLOTH'} · ${exposed(d)?'BARE':GARMENTS[d.g].name.toUpperCase()}`,tx,cy+4*dpr);
}
function render(){
  ctx.clearRect(0,0,W,H);
  const faces=[];hitList=[];
  drawVitrineBack(devicePixelRatio);
  // dress panels
  const md=pp=>pp.reduce((s,p)=>s+p.dist,0)/pp.length;
  PANELS.forEach(P=>{const d=INF[P.id];P.tris.forEach((t,ti)=>{const pp=t.map(q=>proj(q));const n=normal(pp[0],pp[1],pp[2]);
    faces.push({pp,n,z:md(pp),kind:'panel',d,P,ti});});});
  HEAD.forEach(t=>{const pp=t.map(q=>proj(q));faces.push({pp,n:normal(pp[0],pp[1],pp[2]),z:md(pp),kind:'head'});});
  LEGS.forEach(L=>{const pp=L.tri[0].map(q=>proj(q));faces.push({pp,n:normal(pp[0],pp[1],pp[2]),z:md(pp)+.6,kind:'flat',col:L.col});});
  {const pp=NECK[0].map(q=>proj(q));faces.push({pp,n:{x:0,y:0,z:1},z:md(pp)+.3,kind:'flat',col:'#bdbdbd'});}
  faces.sort((a,b)=>b.z-a.z);
  const dpr=devicePixelRatio;
  for(const F of faces){
    const nz=F.n.z; // +z toward camera in our coordinates (camera at +z)
    if(F.kind!=='flat' && nz<=0) continue;
    const lambert=Math.max(0,F.n.x*LIGHT.x+F.n.y*LIGHT.y+F.n.z*LIGHT.z);
    if(F.kind==='head'){
      const l=.55+.45*lambert;drawTri(F.pp,`hsl(260 20% ${84+l*14}%)`,'rgba(17,17,17,.45)',1*dpr);continue;
    }
    if(F.kind==='flat'){drawTri(F.pp,shade(F.col,.55+.45*lambert));continue;}
    const d=F.d;const ex=exposed(d);const hov=state.hover===d.id||voice.cur===d.id,sel=state.sel===d.id||voice.cur===d.id;
    if(ex){
      const fres=Math.pow(1-Math.min(1,Math.abs(nz)),1.2);
      const h1=holoHue(d,fres),h2=140+(((h1-140)/200+.22+fres*.2)%1)*200;
      const sat=Math.max(18,52-d.age*3), lit=Math.max(68,91-d.age*2);
      const g=ctx.createLinearGradient(F.pp[0].sx,F.pp[0].sy,F.pp[2].sx,F.pp[2].sy);
      const L1=lit*(0.9+0.1*lambert)+(hov?4:0), L2=(lit-8)*(0.9+0.1*lambert)+(hov?4:0);
      g.addColorStop(0,`hsl(${h1} ${sat}% ${L1}%)`);g.addColorStop(1,`hsl(${h2} ${sat}% ${L2}%)`);
      drawTri(F.pp,g,sel?'#111111':'rgba(255,255,255,.95)',(sel?2:1)*dpr);
      if(d.age>=5){ // stains on old cloth
        ctx.save();ctx.beginPath();ctx.moveTo(F.pp[0].sx,F.pp[0].sy);ctx.lineTo(F.pp[1].sx,F.pp[1].sy);ctx.lineTo(F.pp[2].sx,F.pp[2].sy);ctx.closePath();ctx.clip();
        let s2=d.id*31+F.ti*7;const cx=(F.pp[0].sx+F.pp[1].sx+F.pp[2].sx)/3,cy=(F.pp[0].sy+F.pp[1].sy+F.pp[2].sy)/3;
        ctx.fillStyle='rgba(60,40,20,.13)';for(let k=0;k<d.age;k++){s2=(s2*9301+49297)%233280;const rx=s2/233280;s2=(s2*9301+49297)%233280;const ry=s2/233280;ctx.beginPath();ctx.arc(cx+(rx-.5)*56*dpr,cy+(ry-.5)*56*dpr,(.8+rx*1.8)*dpr,0,7);ctx.fill();}
        ctx.restore();
      }
    }else{
      const base=GARMENTS[d.g].col;const f=d.g==='coat'?shade('#3a3a3a',.6+.6*lambert+(hov?.15:0)):shade(base,.78+.22*lambert+(hov?.05:0));
      if(d.g==='under'&&!sel)ctx.setLineDash([3*dpr,3*dpr]);drawTri(F.pp,f,sel?'#111111':(d.g==='coat'?'rgba(255,255,255,.4)':'rgba(17,17,17,.45)'),(sel?2:.8)*dpr);ctx.setLineDash([]);
      if(d.g==='shirt'){ // weave
        ctx.save();ctx.beginPath();ctx.moveTo(F.pp[0].sx,F.pp[0].sy);ctx.lineTo(F.pp[1].sx,F.pp[1].sy);ctx.lineTo(F.pp[2].sx,F.pp[2].sy);ctx.closePath();ctx.clip();ctx.strokeStyle='rgba(0,0,0,.12)';ctx.lineWidth=dpr;const x0=Math.min(F.pp[0].sx,F.pp[1].sx,F.pp[2].sx),x1=Math.max(F.pp[0].sx,F.pp[1].sx,F.pp[2].sx),y0=Math.min(F.pp[0].sy,F.pp[1].sy,F.pp[2].sy),y1=Math.max(F.pp[0].sy,F.pp[1].sy,F.pp[2].sy);for(let x=x0;x<x1;x+=5*dpr){ctx.beginPath();ctx.moveTo(x,y0);ctx.lineTo(x,y1);ctx.stroke();}ctx.restore();
      }
    }
    hitList.push({pp:F.pp,id:d.id});
  }
  drawRowLabels(dpr);
  drawVitrineFront(dpr);
  drawCallout(dpr);
}
function shade(hex,k){const r=parseInt(hex.slice(1,3),16),g=parseInt(hex.slice(3,5),16),b=parseInt(hex.slice(5,7),16);return `rgb(${Math.min(255,r*k)|0} ${Math.min(255,g*k)|0} ${Math.min(255,b*k)|0})`;}
function pointIn(pp,x,y){let inside=false;for(let i=0,j=pp.length-1;i<pp.length;j=i++){const xi=pp[i].sx,yi=pp[i].sy,xj=pp[j].sx,yj=pp[j].sy;if(((yi>y)!==(yj>y))&&(x<(xj-xi)*(y-yi)/(yj-yi)+xi))inside=!inside;}return inside;}
function hit(cx,cy){const x=cx*devicePixelRatio,y=cy*devicePixelRatio;for(let i=hitList.length-1;i>=0;i--){if(pointIn(hitList[i].pp,x,y))return hitList[i].id;}return -1;}

// pointer
let px=0,moved=0,lastT=0;
cv.addEventListener('pointerdown',e=>{state.dragging=true;moved=0;px=e.clientX;cv.setPointerCapture(e.pointerId);cv.classList.add('dragging');state.idle=false;});
cv.addEventListener('pointermove',e=>{const r=cv.getBoundingClientRect();if(state.dragging){const dx=e.clientX-px;px=e.clientX;moved+=Math.abs(dx);state.yaw+=dx*.012;}else{state.hover=hit(e.clientX-r.left,e.clientY-r.top);cv.style.cursor=state.hover>=0?'pointer':'grab';}});
cv.addEventListener('pointerup',e=>{state.dragging=false;cv.classList.remove('dragging');const r=cv.getBoundingClientRect();if(moved<6){const id=hit(e.clientX-r.left,e.clientY-r.top);if(id>=0){const d=INF[id];const order=['bare','under','shirt','coat'];d.g=order[(order.indexOf(d.g)+1)%4];state.sel=id;state.tapped=true;$('#hint').classList.add('gone');syncUI();const el=document.getElementById('it'+id);el&&el.scrollIntoView({block:'nearest',behavior:'smooth'});}else{state.sel=-1;syncUI();}}
  setTimeout(()=>state.idle=true,2500);});
cv.addEventListener('pointerleave',()=>{state.hover=-1;});

function loop(t){if(!$('#s-studio').hidden){if(W===0)resize();if(state.idle&&!state.dragging)state.yaw+=0.0022;render();}requestAnimationFrame(loop);}
requestAnimationFrame(loop);
</script>
</head><body></body></html>

Week 0: Concept

My final project is clothes for the digital self: a tangible sculpture shaped like the user's face, its surface built from what their digital history says about them, and a set of clothes that act as a shield.

I made this proposal video with Claude:

Final project proposal, Week 0Open in new tab ↗

Algorithmic Mirror

The idea grows out of the Algorithmic Mirror, an interactive visualization tool that simulates the hidden profiling practices of social media platforms. It uses large-language-model sentence embeddings to reimagine how online activity might be categorized and interpreted (overview video).

Instead of a dashboard of metrics and metadata counts, the tool draws an explorable landscape: a speculative profile of a young person's digital traces. It does not uncover the platforms' actual models. It builds possible mirrors of algorithmic judgment, artificial reflections that show how an identity could be abstracted and rearranged through data.

Algorithmic Mirror: one participant's landscape, by platform
One participant's landscape across Netflix, TikTok and YouTube.

Seeing the three platforms side by side was what struck participants first.

"It made me reconsider how my interests are distributed across platforms. It's as if different personalities exist within each platform." (P2)

A time slider then replays the landscape month by month, so the participant watches their profile take shape (temporal evolution video).

"When YouTube tries to understand what I like, my question is how would it try to track my interest over time and project new interests, or would it just take me as I currently am and give me exactly what I like?" (P9)

By turning opaque inferences into spatial metaphors, the mirror invites reflection on how children's online footprints are silently turned into profiles, and on how inhabiting such a mirror might change one's sense of self.

From mirror to clothes

With a mirror, we can only gaze at our own image. With clothes, we can shape how we present ourselves. How do we make clothes for our digital selves, so that we can choose what we present to AI systems?

Sketch and inspiration

First sketch: clothes for digital selves
The first sketch. A face-shaped mannequin under a shell of triangular panels, each panel one inference made from digital history. Digital traces → LLM → inferences → one inference per panel. Post-its: data portraits and data doubles, danah boyd's faceted identity, context collapse and time collapse, contextual integrity, and Monteiro et al. on when LLM inferences are acceptable.

Artistic inspiration for fragmented selves across space and time:

Nerhol, Phases of Everything
Nerhol, Phases of Everything. A portrait made from many photographs taken over minutes, carved as one block: one person, many moments, one face. Source ↗
Rineke Dijkstra, Still Moving
Rineke Dijkstra, Still Moving. Portraits of the same people returned to over years: the same person, a different self each time. Source ↗
Satoshi Kon, Perfect Blue
Satoshi Kon, Perfect Blue. A self shattered across a public image and a private one.
Artistic inspiration board
Artistic references: Daniel Rozin's mechanical mirrors, the Photorythms portraits at the Media Lab, Perfect Blue and its fragmented self, Hirano Keiichirō's novel Honshin (A Man), and a pair of mirrored figures.
Paper inspiration board
Papers and concepts: AugTwin and Twins on accountable digital twins, danah boyd's Faceted Id/entity (MIT MAS thesis, 2002), Monteiro et al., When Are LLM Inferences Acceptable? (2026), and the sensitive-inference dashboard from our own preprint. Concepts: contextual integrity, time collapse, context collapse, Goffman's performance.

Week 1: Modular clothes (laser cutting)

I first thought of printing the user's inferences as cards, so that users could sort them by hand and slip them into pockets on the clothes. Learning about construction kits changed that: I want assembling the clothes from parts to be intuitive in itself. So I looked at modular clothes, which can be taken apart and put back together without sewing (definition), and at ANREALAGE's Spring/Summer 2022 collection "Dimension" (source).

A board of modular clothing references: garments with detachable parts, user prototypes and modular pieces
Inspiration for modular clothes.
The Week 1 construction kit, assembled and sprayed
The output: a press-fit construction kit for a skirt in plywood. Week 1 ↗

I am not satisfied with the usability of the assembly: it took me two hours to put together. So I plan to explore more intuitive joints and shapes. This kit also only makes a skirt, and I want users to be able to assemble the parts in different ways, into pants or a dress as well.

Week 2: A map of poetry words (embedded programming)

In Week 2, I focused on learning the basics of electronics, as I had no background in it. As a side project, I explored a map visualization of poetry words. On the internet we get lost: everything is zoomed in, and we have little spatial sense of how words relate. So I thought the XIAO-based QPad could be an interesting device for exploring a map of words.

The Kigo pad: a map of seasonal poetry words on the QPad's screen
The Kigo pad. Week 2 ↗

Week 3: Body sculpture (3D printing)

Exploring shapes

In Week 3, I wanted to explore what the final shape of a digital self could look like, using the 3D printer.

I was inspired by ANREALAGE's Spring/Summer 2027 collection "SKIN": how their clothes can change with LED panels, and how numbers were used to stand for the body.

Stills from ANREALAGE's SKIN collection: garments lit with LED panels and covered in projected green numbers
ANREALAGE, SS27 "SKIN".

Building on my struggles with the Week 1 construction kit, I also looked at joint design from Nervous System.

Nervous System's Kinematics pieces: bracelets, flat sheets of joined triangles, a necklace and a dress
Nervous System's jointed pieces.

I also thought it could be fun to explore not just clothes but sculpture, especially Jaume Plensa's Alchemist and Antony Gormley's figures.

A board of body sculptures: Jaume Plensa's figures made of letters and numbers, and Antony Gormley's bodies made of blocks, lines and wire
Jaume Plensa and Antony Gormley.

Then I explored how the body sculpture itself could be taken apart and put back together.

The two printed figures still in green supports
Printing the body with two kinds of supports.
The gray lattice figure with its supports removed
After removing the supports.
A figure with green triangle panels attached
Panels that make up the body. Week 3 ↗

Projection mapping?

After this, I asked myself: does the sculpture actually need to be assembled and disassembled? Talking with Quentin during office hours, I thought it could also be interesting to explore touch sensing and projection mapping. Could we project how algorithms see you onto your own face, or onto the clothes you are wearing?

A board of projection mapping references: faces with projected makeup and patterns, and dancers with projected faces
Projection mapping onto faces and bodies.

Making it personal (data processing)

I want viewers to relate to their own body, not to a random person's, so that they think about their own digital selves rather than a hypothetical one.

But uploading data from platforms is slow. In the Algorithmic Mirror project, it took three days to a week. Yet PimEyes can find where my face appears online almost instantly. Then I found I-XRAY, a project that uses smart glasses to look up a stranger's name, work and interests from their face in real time, using only public data. Its code is not public, but its data processing could be interesting to explore.

For the body shape, this paper could also be useful: it scans a body in about 3 minutes and turns it into an avatar.

Yoichi Ochiai used this technology in his Expo 2025 Osaka pavilion, null²: visitors scan their face, voice and body to make a digital copy of themselves, and inside the mirrored pavilion they talk with their own digital body as it deforms and moves on its own. I will explore this more.

Stills from null²: a scanned figure reflected endlessly in a mirrored room
Yoichi Ochiai, null², Expo 2025 Osaka.

Whom do we present our digital selves to?

My idea is to think about self-presentation in the digital age. But imagining how to present yourself to algorithms is probably too abstract. So I thought: what if you imagine dying, and presenting yourself to the people who are still alive? Imagine your life can be quantified, and the people close to you can make avatars or agents of you and talk to them, as in Hirano Keiichirō's novel Honshin, where a son has a virtual figure of his late mother made.

When others can make avatars of us, do we still own our own body? How are our memories mediated through algorithms?

Papers:

Quietly, I'm slightly against TeleAbsence. They say we die twice: once when our body dies, and again when we are forgotten. But what if we actually want to die and be forgotten? How can our last wishes be respected? Did Max Brod betray Kafka when he published his writings, even though Kafka was so negative about them and did not want them published? How can we control how we are perceived and remembered? Do we even desire to be immortal?

Let us call the gesture of Bettina and Laura the gesture of longing for immortality. Bettina, who aspires to grand immortality, wishes to say: I refuse to die with this day and its cares, I wish to transcend myself, to be a part of history, because history is eternal memory. Laura, though she only aspires to small immortality, wants the same: to transcend herself and the unhappy moment in which she lives to do "something" to make everyone who has known her remember her.

Milan Kundera, Immortality (trans. Peter Kussi, 1991)

So for participants, thinking about death, and designing a digital body that chooses how to be remembered and what to pass on to the next generation, could be an interesting prompt.

Week 4: LED lights (electronics design)

In Week 4, I again focused on learning electronics, so I did not develop the concept much further.

I am making a Spotify album-art LED matrix, and learned how to send color information to a 64×64 LED matrix. This could be applied to changing the colors on the body sculpture based on how participants touch it.

A 64×64 LED matrix showing album art, next to a CD player in a transparent case
The LED matrix, and the transparent case I'd like the board to live in.
Notebook page tracing how a color signal travels to the matrix, and the five steps of drawing a frame
How color information reaches the LEDs. Week 4 ↗