Lift12 Stories: Tricia Wang (Han's Shoe) [en]

[fr] Je suis à la conférence Lift12 à Genève ces jours. Voici mes notes de sessions.

Live-blogging from Lift12 conference in Geneva. These are my notes and interpretations of Tricia Wang‘s session — best effort, but might be imprecise or even wrong!

Han grew up in rural China. Model citizen (Mao-abiding). Civil servant? Something changed. Fang Bin Xin (FBX) — “Father of China’s Great Firewall”. Gets lots of public talks on dangers of internet and need to control it.

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One of these talks. Han threw a shoe on FBX.

What happened to Han?


How does the son of a farmer end up on international news and live to tell the tale?

Spent the last few years studying trust. Can pop up and erode at a moment’s notice.

When Han went to college, everything was put in question. Hardest working people in society were sometimes made the most poor.

Han discovers Twitter. Learns stuff. Blocked in China. VPN is needed. Pay for it! 2%.

On Twitter found people with shared interests => shared identity => shared responsibility. Tweet good information!

May 19 2011, Han checks Twitter, and sees people inciting others to give FBX a hard time. Han goes to see. Bumps into students with eggs that they planned to throw. But they got nervous. Shoved the eggs in Han’s hands. Han shows them at FBX, misses, and in a final act of desperation, takes off his shoe, throws it and misses.

Bolts out of the security hall. Chased. Thinks he escaped. Shares tweets of his escape and blistered tweets. Back to his dorm, he’s major news on Twitter. Hashtags. Offers: sexy girls, apple products, one night stand, vacation to Thailand, VPNs, American pistachio nuts, shoes…

He was never working alone. Information -> ideas -> behaviors. Became international symbol for internet freedom.

How is trust constructed in China? (We need to understand that to understand Han’s story.)

How do we build up the trust to acquire share information with sources we don’t really know. Tricia does deeply immersive investigative stuff as an anthropologist. Gaming and sleeping in internet cafés, etc.

Why wasn’t Han arrested? Police visited him. Also took him to dinner and got him drunk. First, put a lot of pressure on all the institutions he was part of. We are all embedded in institutions. Institutions, in China, are also responsible for the acts of the individuals that belong to them. Personal records, lots of them. Sealed brown envelopes that follow you in life from institution to institution.

Police first went to his university. Institutions trust other institutions to get things done. Assumption: his university would correct (?) him.

Police couldn’t find central command (Twitter, etc — police didn’t get it, there was no central command for them to go after). Emergent structures…

When people lose trust in institutions, top-down measures don’t work so well.

steph-note: missed a few links here

Self-healing mesh network — the loose community Han was part of through Twitter. When the other students got cold feet (weak node) Han acted, though he hadn’t planned to. Self-organized collective.

Institutions can have weird consequences. Firewalls can sometimes protect people from the law.

Information can only be free when people aren’t in danger for accessing it.

  • Social circles: people you already know. Reinforce our relationships. Build on existing relations of trust.
  • Social network: entities we don’t have a personal relationship with. Expand our relationships. New relations of trust. Reveal common interests, etc.

Problematic implication: social graph = web of trust. Sharing can mean that we’re trying to figure out trust, rather that it’s established. Difficult to represent the strength of institutional affiliation algorithmically.

Information acts.

steph-note: skipped a bit there; fascinating but going a bit fast

Trustworthiness + out circle + in network = participation.

Example: pedestrians creating desire paths (outside of designed paths). Equivalents in social networks. Desire paths decrease social distance. They’re hard to predict.

With visibility comes traceability. Information doesn’t pick sides.

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