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AI and Civic Trust in Hong Kong — Level B2 — Scrabble letters spelling love scam on a wooden table

AI and Civic Trust in Hong KongCEFR B2

27 Apr 2026

Adapted from Nishant Shah, Global Voices CC BY 3.0

Photo by Markus Winkler, Unsplash

Level B2 – Upper-intermediate
6 min
309 words

The arrival of generative AI has changed how civic life faces deception. On a public university campus in Hong Kong, routine scam warnings appear each academic year: posters, emails, notices, station ads and headlines. A high‑profile case in which an employee was fooled by a deepfake video call and transferred millions has led officials to warn that society is not fully prepared and that new responses are needed.

Earlier debates about misinformation focused on circulation, such as rumours or manipulated images going viral. Generative AI shifts the problem: plausibility, not obvious falsehood, becomes cheap and widespread. Digital life fills with content that is not clearly fake but also not reliably true, which creates cognitive fatigue and a feeling of surrender. As verification tools multiply, trust moves from everyday social practices to technical systems that claim to tell us what is authentic; financial authorities describe this as a field where AI must be used to fight AI.

AI is also entering ordinary public interfaces, for example:

  • enquiry systems and service kiosks
  • governance application processes and translation tools
  • payment gateways, automated assistance and city management workflows

Efficiency alone does not make institutions more civic. Public hearings into the Tai Po residential fire show that civic trust requires people to understand how decisions are made, to have ways to challenge errors, and to know how responsibility is shared. The Digital Narratives Studio shifts the question from how AI improves services to what civic relations those services should support. It practices relational infrastructuring: small, informal gatherings where people name encounters, compare experiences, share interpretations and test judgement together, paired with language and practices that make AI accountable and open to change. This bottom‑up work is slow and not easily scalable, but it aims to rebuild the relational conditions so publics can make meaning together rather than only verify what is real.

Difficult words

  • deceptionact of making someone believe false things
  • deepfakesynthetic media that imitates a real person
  • plausibilityquality of seeming reasonable or likely true
  • cognitive fatiguemental tiredness from too much thinking or attention
  • verificationprocess of checking if information is authentic
  • civicrelating to community life and public affairs
  • relational infrastructuringbuilding shared relations and local accountability practices

Tip: hover, focus or tap highlighted words in the article to see quick definitions while you read or listen.

Discussion questions

  • How might shifting trust from everyday social practices to technical verification systems change public life and civic participation?
  • What are the advantages and disadvantages of the slow, bottom-up gatherings described in the article for rebuilding trust?
  • How could public institutions balance efficiency from AI with the need for transparency and ways to challenge decisions?

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