Possibilities In Future Careers — In a Future Scenario of “Citizen Centric HyperEgovernment”
Read our student Kunwei Niu‘s blog post about the Future of Government 2030+, Possibilities In Future Careers — In a Future Scenario of “Citizen Centric HyperEgovernment” originally posted on https://medium.com/@kunweiniu/possibilities-in-future-careers-58c439c40d52
Niu’s post is a response to the Global Design Futures unit on the course, in which students worked on the Future of Government 2030+ project, in collaboration with the EU Joint Research Commission and the EU Policy Lab, as well as the Public Collaboration Lab at UAL and Camden Council. Read more about the project work-in-progress here http://masedi.myblog.arts.ac.uk/2018/05/03/sharing-work-in-progress-the-future-of-government-2035/
Possibilities In Future Careers
— In a Future Scenario of “Citizen Centric HyperEgovernment”
We live in a world that is experiencing unprecedented rapid development and changes. Whether it is the Industrial 4.0 that is happening, the big data in Sharing Economy, it has a major impact on people’s career planning.
The most significant factor would be the computerization and automation in many industries, which will leave many employees facing an unemployment or redeployment crisis (Scott, 2017). For potential job seekers who are still learning knowledge and skills at school, whether the skills they learned can match their future career needs is also an unknown issue. Therefore, one of the questions and voices of job seekers would be:
“What changes would happen in the future career market?”
I will discuss the topic of “Possibilities In Future Careers” based on the future scenario from the Future of Government project. With Service Design thinking, I would come up with 5 future trend forecasts through research, speculation and experiment.
During the Future of Government project, 3 team members and I focused on the “Strong Growth and Access to Jobs” challenge for the London Borough of Camden (LBC), Strategy and Change who are collaborating with the Public Collaboration Lab (PCL) (UAL) and European Commission’s Joint Research Centre (JRC), in order to look for a new governance model and new relationships among citizens, governments and businesses for the UK governments in the near future around 2030.
To make the London Borough of Camden a better place for citizens, local government has made a series of plans and appeals facing emerging opportunities and challenges with the rapid development of society. They describe their ambitions and plans about careers in one of Camden 2025 Call to Actions:
“In 2025, growth in Camden should be strong and inclusive — everyone should be able to access the work that is right for them” (Camden Council, 2018)
In terms of jobs and skills, Camden Council aims to reduce the level of unemployment and inequality and improve digital connectivity for citizens and businesses (Camden Council, 2018). In the near future about 2030, there will be:
- More flexible jobs
- More strengths-based jobs
- Multiple career networks from schools to businesses
- More community engagement form both national companies and local start-ups
The future scenario we chose is raised from JRC’s previous research and citizens workshops- “Citizen Centric HyperEgovernment”.
As shown in original documents, there will be a high coverage of AI technology in governance and participation. Within this AI-driven governance system, decision making will be more smarter and easier either for Government or for citizens. In addition, transparency will become the basic requirement for cooperation and data sharing and the public service will be predictively and accurately provided to citizens and other social actors.
We focus on two kinds of groups, one is job seekers who do not have a clear awareness about their strengths and aspirations for career, and no plan for job seeking as well. The other one is people who need job transitions. They usually lack in vigilance and preparation for future jobs and required skills, so that they need to learn new skills and get proper training to adapt to new jobs.
What they need is that:
- Timely jobs and required skills forecasting
- Clear and personalized career and training plans
After learning about the expectations from government and citizens, I need to do some research about what is happening now that will imply the future as weak signals.
Benefit from Data Revolution
5 years ago, Tatevossian said that “98 percent of all stored data is in digital form”. At that time, we focused on developing tools and programs for collecting more kinds of data with visualizing diagrams and emphasized the importance of the quantity of databases for many years.
Nowadays, data has gone through huge changes which influence various aspects- volume, variety, velocity and veracity, and it is no longer a difficult task to have a large database (IBM, 2015).
It can be seen that data collecting and updating is much faster than before due to the development of Internet and IoT technology (Tombolo, no date). Every citizen can easily input and share data actively through different ways. Many data would be collected from all kinds of devices through different channels automatically.
Tombolo is a data innovation project delivered by Future Cities Catapult and Space Syntax through providing software system with a data modelling digital product for policy makers, planners, designers and developers to work on city design and development with real data evidence (Future Cities Catapult, 2018).
Aiming to make changes in the future, Tombolo wants to use data collecting and analysing open-source software (Digital Connector) to interconnect datasets and urban models. In that case, the data produced by us within cities would be collected together to same large platform and share to all of us for innovation and development practices, which is in line with the future scenario I working on.
To develop further this project, Tombolo team launched “City Data Hack” hackathon in March this year to tackle three challenges raised from three local authorities in London.
One of the challenges is “Employment and Skills” put forward by Greater London Authority. They want young citizens to be able to make informed and better learning and career decisions within the proper information about jobs, vacancies and skills supported by a web-based tool(Tombolo, 2018). In their future visions:
Information is an important part of the skills system.
Learners need information about career options, qualifications and learning providers. Learning providers need to know what skills are in demand. Career advisers need to know about job opportunities and the qualifications that will help their clients get these jobs. Policy makers also need information to address skills ‘gaps’, and to ensure that learning opportunities are accessible to all.(Tombolo, 2018)
As we have similar data sharing issues to deal with and similar aspirations about jobs and skills, Tombolo project can be a strong reference to my provocation about the future career.
Future Public Services Delivery
In 2016, IBM team came up with a series of conjectures on how public services will be delivered in the future. Since UK governments are facing high pressure from increasing efficiency and offering better service aiming to citizens with different needs, it is urgent to create a new plan that meet the standards of the digital era (IBM Industries, 2016). IBM team claimed that:
“By 2020, all public services will be digitised and integrated, transforming the way citizens interact with public services” (IBM Industries, 2016)
In the area of social welfare, they mentioned “Smart Job Search” and secure employment, which means careers play an important role in one’s welfare.
Generally speaking, career is a crucial basement and guarantee for a citizen’s life quality and stability. For government, maintaining the overall development of the community is a tough mission from past to now. Besides, with the increasingly development of emerging science and technologies, there will be more and more uncertainties governments have to face, which could be either challenges or opportunities.
To maximise the advantages of technology in governments’ service delivery, IBM team suggested that in the future, citizens can be informed suitable jobs matched with their skills, career advice and training suggestions based on the data sharing system.
To achieve this, I think there would be:
- More diverse data collecting from not only citizens but also educational institutions and companies through IoT system and smart devices
- More accurate data analysis and better matching among skills, training and jobs through Artificial Intelligence practicing
- More suitable career and training plans for each citizen through deeper machine learning within AI-driven system
Meanwhile, as we enjoy the advantages from big data sharing system, we need to tackle with the challenges about data privacy and strategies, which means how to engage citizens, educational institutions and companies in this data sharing platform and could all benefit. This would be a question for me that I need to look for the answer afterwards.
Network Effects Promotes Value
Digital Social Innovation (DSI) formally known as DSISCALE, is supported by the European Union and funded under the Horizon 2020 Programme. Here is a incubator community where organizations and projects could be supported with digital technologies, funding and collaborators to tackle social challenges together (Digital Social Innovation, no date).
DSI advocates open technologies and is working on exploring more possibilities for use of technologies, citizens’ initiative about social issues and transparency in governance. It can be shown in many projects practiced in this “community” with use of multiple technologies. Among these, works and skills is still a hot topic that people work on.
In addition, DSI believes that network has a direct and important impact on the value of the project. As can be seen from the above figure, the frequency of usage of different technologies for solving problems in skills and works related projects has similarities. The top 4 technology categories used in these two kinds of projects are:
- Social networks and social media
- Crowdsourcing, crowdmapping and crowdfunding
- Mobile web apps
- Peer-to-peer networks
Therefore, it is obvious that networks is a considerable success elements in jobs and skills relevant projects, which means social networks, alumni networks, mentorship networks and career networks and so on.
“… as the size of the network increases, the value to each user increases, and the overall value of the innovation increases by more times than the size of the network.” (Digital Social Innovation, 2017)
“Network effects are a major enabler for DSI to deliver impact” (Digital Social Innovation, 2017)
From my point of view, this can be used for describing the Sharing Economy, which means the scale of success would be influenced a lot by the openness of data and information sharing. In the future society, you probably would gain more profits once you contributed the same, so that it is easier to succeed through large-scale collaborations of data sharing, strategy planning and practicing.
Weak Signals about the Future
Based on the above background learning and secondary research, I have found some weak signals that may indicate the possibilities in future careers.
#1 Data sharing collaboration and data-driven decision-making
Citizens need to share data to receive services and companies need to share information to gain more value and efficiency. Sharing and contributing would be first step in this service model (Digital Social Innovation, 2017). Real and big data still have right to speak.
#2 Use technology like deeper machine learning in service deliveries
We need more accurate and predictive AI system for information matching, information recommendation, decision making, as well as plan making for educational institutions(IBM Industries, 2016).
#3 Easier multiple and flexible collaborations among stakeholders
There will be an universal acknowledge that more collaboration is better and it be easier to cooperate with multiple stakeholders in a flexible model, which means every stakeholder can have different collaboration models at the same time.
Since we already know that there are very likely to be various unavoidable changes in the future, is it possible for us to be informed in advance and prepare for it as soon as possible? I asked myself a new question:
“How to predict changes in advance and prepare for them?”
To find proper answers about the future, the traditional design thinking that designing for problem solving does not work any more.
Standing in the future scenario, facing the users and stakeholders from the future, we need to use Speculative Design to find the answer, to imagine possible futures.
“… if we speculate more — about everything — reality will become more malleable.” (Dunne and Raby, 2013)
Based on the insights and weak signals from above research, my teammates and I would like to make a provocation about the future jobs and skills relevant service:
“What if Camden Council creates jobs and skills in Camden, offering opportunities to citizens for improving their skills and enables them to get a subsequent well-being?”
The reason is that the future scenario we chose and the aspirations from Camden Council show that there is a need for integrating educational and career relevant resources, we suppose government will be a service enabler to capture data, analyse data and share data in the future.
I would like to show different stages with changes in iterations about the speculation, as well as reasons about the changes. Specifically, how and why I demonstrated, tested and iterated the provocation to practice speculative design.
Experiment 1 – New Collaboration Model in Future Careers
Our initial idea about “Future Models of Service Delivery”
In this concept, we imagine a new collaboration model among citizens, government, institutions and businesses, which means in the future, government will be a service enabler and facilitator, while citizens, institutions and businesses could collaborate with each other within the AI-driven data sharing platform supported by governments.
– Government’s perspective: Co-decision Making Innovation
AI government enables stakeholders to connect with each other. Engages stakeholders with decision making process/policy making.
– Citizens’ Perspective: Proactivity
Citizen can be matched with job opportunities based on their Digital Profile and Matching Information with the businesses. Citizen can get training channels according to their Career Goals and Matching Information.
– Businesses’ Perspective: Training Collaboration
Businesses collaborates with council, create training and job opportunities for the residents.
– Institutions’ Perspective: Learning+Skills
Institutions collaborates with council, assess and improve the skills of citizen.
Therefore, in this new service model, every stakeholder can take the initiative to contribute and benefit. In other words, every stakeholder’s actions and rewards from different perspectives.
We would like to use a interactive prototype to show this new collaboration model of service delivery.
We use modular circle jigsaws to realize interaction parts with audience. In our imagine, audience would feel the value behind each initiative when they creating a new collaboration model under each topic.
We got the opportunity to get feedback from Adam representing PLC team and our tutor firstly. Then we described our project processes and the concept about the future model of service delivery.
The feedback given this round was not very good. They said that our concept is more like a solution for solving a current problem, not a provocation about the future.
“Not design a service, but design a model of service delivery” (Lara, 2018)
In terms of the draft prototype about different collaboration models, the feedback shows that it is too vague to express our concept and has less connections. Due to this reason, we decide to suspend this prototype temporarily and think about how to improve and get more feedback from the upcoming co-design workshop at CSM with different clients and experts.
For the co-design workshop, we prepared a few printing materials to show our future user journey of two target groups and future relationship map. The reason why we prepare paper materials is that generally it is a good way to collect interactions and feedback of participants. So that we provided several pens and stickers as well.
In the end of the workshop, we got different verbal feedback without notes on papers. The verbal feedback emphasized that:
- The uniqueness and innovation of the concept
- How AI works in this service system
- Data transparency in companies data sharing
Besides, I summarized some possible reasons of why the format of collecting feedback does not work:
- Lack of well-designed format of collecting feedback
- Limited time is a challenge for both presenters and audience
learning and iteration
From this design experiment, I realized that even when we do Speculative Design, we still need to stand on specific scenarios and personas. For this time, we ignored the importance of scenario and persona and made something does not in line with the local situation.
The other thing is that, when we talk about service design, it is usually easy to think about a current service system and relevant stakeholders. In this way, we made a mistake that only focusing on the service model and stakeholders at present and we have not realised that circumstance for a long time without looking for a innovative future concept.
To iterate the concept, we think there is a need for us to rebuild the provocation since we want to come up with and show key values of our speculation about the future careers.
For this time, we supposed that the most tricky problem is the engagement of companies. How do we encourage businesses share their information and contribute in this service system? How to balance the benefit for each stakeholder in order to achieve a proper participation?
“What if Camden Council encourage companies to contribute in individual skill training while empowering citizens to be a lifetime learner with healthy lifestyles?”
After discussion and ideation about the speculation, we came up with a 2nd provocation. In this provocation, we emphasized the role of businesses and the value for citizens who are key users in this service delivery model.
Experiment 2 – “Future Skills”
This time, we simplified our service model diagram with key information on it, such as roles, values and actions.
We made some sketches about the finial format of prototypes. There are two ways to show our service model.
One is to use 3D models to show how different stakeholders work in this service model, like the route of information flows. The other one is to display the interaction among stakeholders in different stages in line with user’s journey.
After a little iteration, we chose this shape and format as our prototype, because this is more three-dimensional and more convenient for audience to check the details. The content on each disk is different stages in user journey.
This is a interactive prototype with electric board at the bottom and the “E-ID” card would be the hidden switch in this apparatus. When the switch is triggered and the circuit is connected, the light bulbs at the bottom of each circle will light up. At the same time, the graphics and text on each acrylic disk will be lit to show the user journey together.
We tested this prototype with peers and tutors. The problem is that this format is not suitable enough for value expressing. Several individual disks did not show much senses of harmony.
Learning and Iteration
What I learned from this time is that prototype making is an important elements in speculative design and we need to make every part meanings without decorations only.
It is also important that looking for the proper solution, maybe not the perfect and best solution. That is because project time for prototyping is very limited, we need to learn to do multitasks at the same time, which requires proper results that suitable for current situation.
So we picked our key values out and thought about how to show them by prototype making:
- Jobs and Skills Forecasting
- Preparation of Citizens
| Future Trend Forecasts
Based on the research before and speculative design experiments, I came up with 5 future trend forecasts.
#1 More open data sharing in future career markets
In the future career markets, both employees and employers will offer more data for exchanging. Through this, employees will have more opportunities to pay attention to other companies and employers will be more easier to find the proper one.
#2 More accurate matching system for employment
Based on AI-driven data analysis, there will be more deeper machine learning technologies and strategies in order to provide more accurate information matching especially in employment. We don’t need to look for the proper opportunities one by one and update CV all the time.
#3 E-ID for data collecting, analysing and presenting
With digital technologies rapidly development, we will all use invisible account in the future, such as an E-ID for personal profile and career and training plan, as well as other services (IBM Industries, 2016).
#4 Data-driven decision making
Big data is still crucial to future career markets, as the more data provided, the decision making with AI technologies will be more objective and holistic. In the future, I suggested that data capturing and analysing will keep going.
#5 Smarter community with engagement
In future community, there will be more open to every social actor and more connective. Once you engage in a community, you will be able to access to the situation changes in this area, more locally and more internationally as well. In future career markets, there will be more international companies and local business engaging in this smarter community development.
Agrawal, V. (no date) Available at: https://datafloq.com/read/why-is-big-data-so-important-in-todays-world/2674 (Accessed: 8 May 2018).
Camden 2025 (2018) Available at: http://www3.camden.gov.uk/camden2025/ (Accessed: 20 March 2018).
Canigueral, A. (2017) Available at: https://www.ouishare.net/article/building-the-networked-city-from-the-ground-up-with-citizens-interview-with-francesca-bria (Accessed: 11 May 2018).
City Data Explorer (2018) Available at: https://tombolo.emu-analytics.net/view/950db2c7-1a3b-448d-9b21-444a0ec7b5e0(rightBar:appinfo)?basemapDetail=4&zoom=4.6&lng=-0.58456&lat=54.91938 (Accessed: 22 March 2018).
Dunne, A. and Raby, F. (2013) Speculative Everything: Design, Fiction and social Dreaming. London: The MIT Press.
Egan, M. (2018) Hedge fund billionaire: 70% chance of recession before 2020 election. Available at: http://money.cnn.com/2018/02/22/news/economy/recession-election-ray-dalio-2020/index.html (Accessed: 15 May 2018).
European Commission (2018) How to design the future of government. Available at: https://blogs.ec.europa.eu/eupolicylab/how-to-design-the-future-of-government/ (Accessed: 3 May 2018).
IBM (2018) Available at: https://www.ibm.com/blogs/insights-on-business/government/?cm_mmc=OSocial_Youtube-_-Leadership+Agenda_Leadership+Agenda+Government-_-WW_WW-_-IBM+Government+Blog&cm_mmca1=000000QK&cm_mmca2=10000772 (Accessed: 7 May 2018)
MA Service Experience Design and Innovation (2018) Available at: http://masedi.myblog.arts.ac.uk/2018/05/03/sharing-work-in-progress-the-future-of-government-2035/ (Accessed: 3 May 2018).
Mitchell, A. (2018) Artificial Intelligence in Government. Available at: https://www2.deloitte.com/uk/en/profiles/amitchell.html (Accessed: 15 May 2018).
Scott, P. (2017) These are the jobs most at risk of automation according to Oxford University: Is yours one of them?. Available at: https://www.telegraph.co.uk/news/2017/09/27/jobs-risk-automation-according-oxford-university-one/ (Accessed: 20 March 2018).
Tatevossion, A. (2013) ‘Big Data’ for development: What is it, and why you should care. Available at: https://www.devex.com/news/big-data-for-development-what-is-it-and-why-you-should-care-81453
Tombolo (2018) Available at: http://www.tombolo.org.uk/ (Accessed: 10 March 2018)
Tombolo (2018) Avaiable at: https://futurecities.catapult.org.uk/project/tombolo/ (Accessed: 8 May 2018).
Waters, R. (2018) ‘Deep learning’ — the hot topic in AI. Available at: https://www.ft.com/content/0a879bec-48bd-11e8-8c77-ff51caedcde6 (Accessed: 11 May 2018).
Wright, I. (2018) What Is Industry 4.0, Anyway?. Available at: https://www.engineering.com/AdvancedManufacturing/ArticleID/16521/What-Is-Industry-40-Anyway.aspx (Accessed: 15 May 2018).
https://docs.google.com/document/d/172tXvGcMhe0NjDjYMXd4P_04na88D8W_Ye-bTm5kaA4/edit (2018) (Accessed: 20 March 2018).
https://drive.google.com/drive/folders/1rutsCToyF4wa7CMYj97QwsQxdAiXa2Sd (2018) (Accessed: 4 May 2018)
https://digitalsocial.eu/viz/#/map?l=0&e=0&f0=7&f1=78&x=94.971&y=421.233&k=5 (2018) (Accessed: 20 March 2018)