Citizen-centric Hyper-E government in 2030+

AI-driven analytics combined with human judgment.

Citizen-Centric Hyper-E government In 2030+

This video above describes current EU decision-making process.

Emerging Global Trends That Bring Hope for 2030+

Google I/O 2018: Machine Learning and AI ruled the roost

Google Duplex: A.I. Assistant Calls Local Businesses To Make Appointments
Data in a patient’s record is represented as a timeline for Google’s Deep learning model to analyse it and predict chances of readmission.
Incoming sound is processed through an ASR system. This produces text that is analyzed with context data and other inputs to produce a response text that is read aloud through the TTS system (Google AI Blog, 2018)

Not only big technology companies but also the politician start to using Artificial Intelligence and Machine learning system, and these affect the democracy.

Artificial Intelligence for Democratic Innovation

Technology first: Trump’s presidential campaign team were able to present a different version of him to different voters (EPA)

The future of Government 2030+

Inspiration unlocks the future; technology will catch up. (Shurina, 2015)

Design Research as a foresight method: Forecasting the future of government

Map about the future of government

Thinking in code. Iterating in public. (Foreshew-Cain, 2016)

Experiment 1: Project Good — Decision Making Platform For Urban Planning

What if the citizens would be made accountable for community decisions? Can the citizens have a sustainable place in Camden?

Prototype 01: What if..? question cube that illustrated situations in 2030+
‘Project Good’ Storyboard — Decision making process

Prototype: AI analysis system which is accessible to any citizens

Workshop in Central Saint Martens on Friday 27th April
  • It would be beneficial to create and show other examples to present how our system works from starting point to the final stage, including varied stakeholders and the impact each project would have on them.
  • Try to develop the way we displayed and requested data from the users of our service. We should consider the specific types of data we may need which would likely vary per project.
  • To make our system friendlier for its stakeholders, it would also be good to make it more transparent by sharing information such as maintenance and other costs that would be created by each project.
  • In my opinion, we could not solve the way of setting citizens’ data accessibilities and how can citizens be motivated to open their data accessibility with the government. Also, there were too many voting chances which made the process more complicated. Additionally, prevent losing human touch from automated data analysis process.

Experiment 02: Sherlock — Decision Making Platform For Open Democracy

Provocation

What if citizens were able to have access to and control of future decision making, supported by machine learning and Artificial Intelligence?

Introduction

About Sherlock

Service blueprint

Hyper-E Government: AI + Hyper-connectedness allows better information about upcoming issues.

Prototype: AI Prediction and data transparency

“Open data is not just about transparency. It can create public and economic value.” (Hesa.ac.uk, 2018)

Prototype 02: Introducing Decision making process to citizens
Prototype 02: System map and interactive equipment for introducing entire service journey
Introducing Sherlock’s data analyse process.
Prototype 03: Paper prototype of voting app
Final app design for citizens — From notification to voting
Citizen journey map

Learnings and Iteration

Experiment 3: Data collection — Your body accessibility

You are your identity: Biometrics.

Questionnaire: Biometrics-Your body accessibility
Survey with people and interview
The result of the survey

Main Insights

  • People allowed their data that already used for using smart devices or data which might be collected through surveillance cameras such as facial recognition, voice recognition, gesture recognition, retinal scan, ear scanning, fingerprint sensor and gait analysis.
  • If there were benefits when they decided to share their biometrics, they could only allow visible pieces of information.
  • However, the information about their inner body does not be allowed. Because they thought the situation that government wants to access their mind or to thinking feels scary.

Designing service for Future of government

  • Trend 01: Government as a platform
    Citizens’ needs are getting complicated and diversify. The solution to the new problem will not answer for the future. Government should invent new approaches to serve the public.
  • Trend 02: Everyone is talking: Hyper-connectivity (Forbes.com, 2013)
    Hyper-connectivity will change the relationship between government and citizens. Public services should be predictable and customized.
  • Trend 03: Big data and Artificial Intelligence
    Understanding how the technology work in the service is the critical sector of designing services. AI can improve the service delivery in government’s services. For this, the government should invest in research and promotion.
  • Trend 04: Data transparency in Machine Learning
    Due to GDPR, these topics already placed at a crucial point. The article on the website ‘We live security’ said that without transparency, machine learning process is just ‘Black box.’ (Writer and Writer, 2017) Therefore, ensure data transparency in machine learning process will contribute to prediction in the decision-making process.
  • Trend 05: Citizen centrism
    Ultimately, the citizen is the core value of the government’s service. Citizen-centric government will be collaborative, Technology-driven, Agile and responsive, Driven by insight and Third-party friendly. (Business Value Exchange (BVEx), 2016)

Bibliography

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Yuneui (Yunnie) Choi

I’m a service experience designer who loves innovative technology, human-centred goodness and collaborative work. Currently based in Seoul, South Korea.