Debate and Decide: Innovative Participatory Governance in South Australia 2010–2018

Paper by Matt D. Ryan: “This article provides an account of how innovative participatory governance unfolded in South Australia between 2010 and 2018. In doing so it explores how an ‘interactive’ political leadership style, which scholarship argues is needed in contemporary democracy, played out in practice. Under the leadership of Premier Jay Weatherill this approach to governing, known as ‘debate and decide’, became regarded as one of the most successful examples of democratic innovation globally. Using an archival and media method of analysis the article finds evidence of the successful application of an interactive political leadership style, but one that was so woven into competitive politics that it was abandoned after a change in government in March 2018. To help sustain interactive political leadership styles the article argues for research into how a broader base of politicians perceives the benefits and risks of innovative participatory governance. It also argues for a focus on developing politicians’ collaborative leadership capabilities. However, the article concludes by asking: if political competition is built into our system of government, are we be better off leveraging it, rather than resisting it, in the pursuit of democratic reform?…(More)”.

The case for adaptive and end-to-end policy management

Article by Pia Andrews: “Why should we reform how we do policy? Simple. Because the gap between policy design and delivery has become the biggest barrier to delivering good public services and policy outcomes and is a challenge most public servants experience daily, directly or indirectly.

This gap wasn’t always the case, with policy design and delivery separated as part of the New Public Management reforms in the ’90s. When you also consider the accelerating rate of change, increasing cadence of emergencies, and the massive speed and scale of new technologies, you could argue that end-to-end policy reform is our most urgent problem to solve.

Policy teams globally have been exploring new design methods like human-centred design, test-driven iteration (agile), and multi-disciplinary teams that get policy end users in the room (eg, NSW Policy Lab). There has also been an increased focus on improving policy evaluation across the world (eg, the Australian Centre for Evaluation). In both cases, I’m delighted to see innovative approaches being normalised across the policy profession, but it has become obvious that improving design and/or evaluation is still far from sufficient to drive better (or more humane) policy outcomes in an ever-changing world. It is not only the current systemic inability to detect and respond to unintended consequences that emerge but the lack of policy agility that perpetuates issues even long after they might be identified.

Below I outline four current challenges for policy management and a couple of potential solutions, as something of a discussion starter

Problem 1) The separation of (and mutual incomprehension between) policy design, delivery and the public

The lack of multi-disciplinary policy design, combined with a set-and-forget approach to policy, combined with delivery teams being left to interpret policy instructions without support, combined with a gap and interpretation inconsistency between policy modelling systems and policy delivery systems, all combined with a lack of feedback loops in improving policy over time, has led to a series of black holes throughout the process. Tweaking the process as it currently stands will not fix the black holes. We need a more holistic model for policy design, delivery and management…(More)”.

Using Democratic Innovation to Rebuild Trust between Elected Officials and Citizens

Article by Nick Vlahos: “According to Pew Research, public trust in government is among the lowest it has been in 70 years of polling. Today, 25% of Democrats and Democratic-leaning independents say they trust the federal government just about always or most of the time, compared with 8% of Republicans and Republican leaners.

The dismal statistics we continue to see year in and year out are compounded by the fact that democracy is under threat around the world. In response, many are turning to democratic innovations. According to Oliver Escobar and Stephen Elstub, democratic innovations are “processes or institutions that are new to a policy issue, policy role, or level of governance, and developed to reimagine and deepen the role of citizens in governance processes by increasing opportunities for participation, deliberation and influence.”

Many of these innovations intend to redefine the role of citizens and carve out unique opportunities for them to engage with their peers, collectively problem-solving, and making decisions on important issues. However, there are increasing calls for re-envisioning the relationship between elected officials and citizens using deliberative and participatory processes.

One such approach is the deliberative town hall, implemented by the Institute for Democratic Engagement and Accountability at Ohio State University. The model utilizes democratic innovation in the form of a deliberative mini-public within a single constituency, in relation to an elected official. Deliberative town halls bring together a cross-section of the community using stratified sampling, or civic lottery. The process further involves informed discussion on a topic with an elected official.

This approach has been commonly used with Members of Congress, but has recently been used in other Commonwealth countries, notably in Australia. What we know from this experience is that deliberative town halls can rebuild democratic relations by making interactions between elected officials and citizens more authentic, using reciprocal reason giving and sharing, and through active listening. In addition, ensuring that people with lived experience and scientific or topical expertise are present in conversations creates conditions for members of the public to better understand the nuances of an issue. Lastly, the Australian example highlights how having some type of impact over an outcome is highly prized by the public – they want to have their input factored into a decision, if not determining a decision altogether…(More)”.

AI in public services will require empathy, accountability

Article by Yogesh Hirdaramani: “The Australian Government Department of the Prime Minister and Cabinet has released the first of its Long Term Insights Briefing, which focuses on how the Government can integrate artificial intelligence (AI) into public services while maintaining the trustworthiness of public service delivery.

Public servants need to remain accountable and transparent with their use of AI, continue to demonstrate empathy for the people they serve, use AI to better meet people’s needs, and build AI literacy amongst the Australian public, the report stated.

The report also cited a forthcoming study that found that Australian residents with a deeper understanding of AI are more likely to trust the Government’s use of AI in service delivery. However,more than half of survey respondents reported having little knowledge of AI.

Key takeaways

The report aims to supplement current policy work on how AI can be best governed in the public service to realise its benefits while maintaining public trust.

In the longer term, the Australian Government aims to use AI to deliver personalised services to its citizens, deliver services more efficiently and conveniently, and achieve a higher standard of care for its ageing population.

AI can help public servants achieve these goals through automating processes, improving service processing and response time, and providing AI-enabled interfaces which users can engage with, such as chatbots and virtual assistants.

However, AI can also lead to unfair or unintended outcomes due to bias in training data or hallucinations, the report noted.

According to the report, the trustworthy use of AI will require public servants to:

  1. Demonstrate integrity by remaining accountable for AI outcomes and transparent about AI use
  2. Demonstrate empathy by offering face-to-face services for those with greater vulnerabilities 
  3. Use AI in ways that improve service delivery for end-users
  4. Build internal skills and systems to implement AI, while educating the public on the impact of AI

The Australian Taxation Office currently uses AI to identify high-risk business activity statements to determine whether refunds can be issued or if further review is required, noted the report. Taxpayers can appeal the decision if staff decide to deny refunds…(More)”

Scaling deep through transformative learning in public sector innovation labs – experiences from Vancouver and Auckland

Article by Lindsay Cole & Penny Hagen: “…explores scaling deep through transformative learning in Public Sector Innovation Labs (PSI labs) as a pathway to increase the impacts of their work. Using literature review and participatory action research with two PSI labs in Vancouver and Auckland, we provide descriptions of how they enact transformative learning and scaling deep. A shared ambition for transformative innovation towards social and ecological wellbeing sparked independent moves towards scaling deep and transformative learning which, when compared, offer fruitful insights to researchers and practitioners. The article includes a PSI lab typology and six moves to practice transformative learning and scaling deep…(More)”.

Data and the Digital Self

Report by the ACS: “A series of essays by some of the leading minds on data sharing and privacy in Australia, this book takes a look at some of the critical data-related issues facing Australia today and tomorrow. It looks at digital identity and privacy in the 21st century; at privacy laws and what they need to look like to be effective in the era of big data; at how businesses and governments can work better to build trust in this new era; and at how we need to look beyond just privacy and personal information as we develop solutions over the coming decades…(More)”.

Developing new models for social transformation

Report by Sarah Pearson: We live in unprecedented times. A period where globalisation has supported relative peace and growing prosperity. Where technological innovation has transformed social connectivity, democratised access to information and power, and driven new industry and jobs. The current pandemic, geopolitical power struggles, and a widening disparity in the distribution of the benefits of technology, however, threatens this progression. Many people have been, and many more are being left behind, with the recent COVID-19 pandemic seriously affecting progress in areas such as gender equality. Innovation, from an operational, business model, technological and societal perspective, is poised and ripe to help. This research focused on how this innovation could be applied to philanthropies seeking to address social change, overcome disadvantage, and build Equality of Opportunity.

Opportunities abound: starting with how we lead and govern in Foundations so that we unleash creativity and opportunity, throughout the organisation and externally; how we become more open and access new impactful ideas we would not have dreamt of without looking more widely; how we fund differently in order to make the most of our corpus, apply a gender lens, provide more than financial resources,
and support long term impact through new funding models; how we manage programs with sufficient flexibility to allow for unforeseen impact and experimentation by those we support; with whom and how we partner to deliver greater systemic change, and how to engage in an inclusive ecosystem of impact; how we leverage data to understand the issues, provide an asset for innovation, and measure our impact; and crucially how we set up for a diverse, experimental, learning culture. And in all of this, how we connect to and empower those with lived expertise to build economic self-determination, and combine with other expertise to grow inclusive problem-solving communities…(More)”.

An infrastructure for building policy capability – lessons from practice

Paper by Sally Washington: “The Covid-19 pandemic highlighted the importance of good systems for policy and decision-making. An effective policy system depends on robust policy capability. This article articulates key dimensions of policy capability based on the practical experience of policy practitioners from a range of jurisdictions. It briefly draws on the literature on policy making and organizational capability before situating the key components of policy capability as mutually reinforcing parts of a policy capability infrastructure. These include “supply side” components of leadership, policy quality systems, people capability, and effective internal and external engagement, as well as the “demand side” component of the political administrative interface that shapes and is shaped by policy capability in the public service. This framing of policy capability as an infrastructure broadens the definition of policy capability from a narrow focus on people and skills to a systemic approach that includes the range of systems and processes that enable and support good government decision-making. The article argues that the policy capability infrastructure could serve as a useful and generic analytical framework for describing, assessing, and improving policy capability in teams, organizations, or across an entire public service. Policy leaders are invited to test the framework and share their insights and results, including with colleagues in academia. If it works in practice, it might also work in theory…(More)”.

Data for Social Good: Non-Profit Sector Data Projects

Open Access Book by Jane Farmer, Anthony McCosker, Kath Albury & Amir Aryani: “In February 2020, just pre-COVID, a group of managers from community organisations met with us researchers about data for social good. “We want to collaborate with data,” said one CEO. “We want to find the big community challenges, work together to fix them and monitor the change we make over ten years.” The managers created a small, pooled fund and, through the 2020–2021 COVID lockdowns, used Zoom to workshop. Together we identified organisations’ datasets, probed their strengths and weaknesses, and found ways to share and visualise data. There were early frustrations about what data was available, its ‘granularity’ and whether new insights about the community could be found, but about half-way through the project, there was a tipping point, and something changed. While still focused on discovery from visualisations comparing their data by suburb, the group started to talk about other benefits. Through drawing in staff from across their organisations, they saw how the work of departments could be integrated by using data, and they developed new confidence in using analytics techniques. Together, the organisations developed an understanding of each other’s missions and services, while developing new relationships, trust and awareness of the possibilities of collaborating to address community needs. Managers completed the pilot having codesigned an interactive Community Resilience Dashboard, which enabled them to visualise their own organisations’ data and open public data to reveal new landscapes about community financial wellbeing and social determinants of health. They agreed they also had so much more: a collective data-capable partnership, internally and across organisations, with new potential to achieve community social justice driven by data.

We use this story to signify how right now is a special—indeed critical—time for non-profit organisations and communities to build their capability to work with data. Certainly, in high-income countries, there is pressure on non-profits to operate like commercial businesses—prioritising efficiency and using data about their outputs and impacts to compete for funding. However, beyond the immediate operational horizon, non-profits can use data analytics techniques to drive community social justice and potentially impact on the institutional capability of the whole social welfare sector. Non-profits generate a lot of data but innovating with technology is not a traditional competence, and it demands infrastructure investment and specialist workforce. Given their meagre access to funding, this book examines how non-profits of different types and sizes can use data for social good and find a path to data capability. The aim is to inspire and give practical examples of how non-profits can make data useful. While there is an emerging range of novel data for social good cases around the world, the case studies featured in this book exemplify our research and developing thinking in experimental data projects with diverse non-profits that harnessed various types of data. We outline a way to gain data capability through collaborating internally across departments and with other external non-profits and skilled data analytics partners. We term this way of working collaborative data action…(More)”.

Mapping community resources for disaster preparedness: humanitarian data capability and automated futures

Report by Anthony McCosker et al: “This report details the rationale, background research and design for a platform to help local communities map resources for disaster preparedness. It sets out a first step in improving community data capability through resource mapping to enhance humanitarian action before disaster events occur.The project seeks to enable local community disaster preparedness and thus build community resilience by improving the quality of data about community strengths, resources and assets.

In this report, the authors define a gap in existing humanitarian mapping approaches and the uses of open, public and social media data in humanitarian contexts. The report surveys current knowledge and present a selection of case studies delivering data and humanitarian mapping in local communities.

Drawing on this knowledge and practice review and stakeholder workshops throughout 2021, the authors also define a method and toolkit for the effective use of community assets data…(More)”