Six elements of effective co-design

By Will Allen.

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Will Allen (biography)

What does co-design for tackling complex challenges look like in practice?

Co-design is a collective way of navigating complexity, taking different forms depending on context. The following six elements are a reflection on patterns I’ve seen emerge through practice, especially in settings where multiple perspectives matter.

1. Starting with shared grounding: Creating early alignment through shared values, context, and purpose

In many collaborative projects, there’s a tendency to begin by defining tasks – what needs doing, by whom, and when. But in complex settings, where multiple perspectives and values come into play, it’s often more important to begin with relationships. It helps to understand where people are coming from, what matters to them, and how they see the purpose.

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Transdisciplinary research with and for artificial intelligence

By Florian Keil, Melina Stein and Flurina Schneider.

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1. Florian Keil’s biography
2. Melina Stein (biography)
3. Flurina Schneider (biography)

Is artificial intelligence, a technology aggressively advertised as the ultimate cure-all, fundamentally incompatible with transdisciplinarity and its decades-old insight that the “wicked” problems of the real world do not lend themselves to one-dimensional solutions? Should transdisciplinary research outright reject a technology that is already undermining efforts to achieve social and environmental justice? Or can artificial intelligence actually support transdisciplinary research when used responsibly?

Using artificial intelligence in transdisciplinary research requires a critical mindset

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Building co-production capabilities in researchers: Strengthening reflexivity via learning opportunities

By Emma Ligtermoet, Claudia Munera-Roldan, Cathy Robinson, Zaynel Sushil and Peat Leith.

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1. Emma Ligtermoet; 2. Claudia Munera-Roldan; 3. Cathy Robinson; 4. Zaynel Sushil; 5. Peat Leith (biographies)

What forms of learning can support interdisciplinary teams to rapidly build reflexivity capabilities, especially in preparation for doing transdisciplinary (engaged) science with non-researcher societal actors?

Transdisciplinary co-production requires deep and reflexive learning. Reflexivity is a key capability for researchers doing inter- and transdisciplinary science, involving the critical enquiry of existing assumptions, values and norms underlying our decisions and actions, with the aim to adapt or change current practices or discourses.

Such learning is foundational for understanding and proactively engaging with knowledge-power dynamics, including potentially catalysing shifts in incumbent dynamics when preparing to engage with non-societal actors.

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Seven quality choice points for contemporary action research

By Hilary Bradbury.

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Hilary Bradbury (biography)

How can action researchers empower system actors in impactfully responding to our deepening eco-social crisis? How can action research be a catalyst to successfully transmute the inexhaustible resource of human creativity in all spaces—self to society—toward addressing our global problems? How can we encourage deepening clarity of choices made to navigate a middle path between responding to problems within living communities and contributing to research-based theory?

Mitigating the worst of our global problems requires action research that draws on many kinds and sources of knowledge. In fact, it requires drawing much more from diverse people on the ground, who understand the problems at hand and can offer solutions anchored in their experience of what is meaningful for them.

The aim of the seven choice points described below is to support action researchers in:

  • deepening and speeding up the proliferation of good work,
  • connecting local niche experiments to global reach.

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Key leadership practices in transdisciplinary projects

By Susanne C. Moser.

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Susanne C. Moser (biography)

When training transdisciplinarians, which leadership skills and practices is it helpful to encourage? 

The kind of leadership that someone brings to a transdisciplinary project has decisive implications for how a project unfolds and for its likelihood of success. Conventional thinking about leadership often hinges on unspoken assumptions about hierarchies, power, and the significance and impact of a single individual; it also often implies unspoken ideas about inclusion, assignment, or sharing of rights and responsibilities, and those to praise or blame for any outcomes. At the same time, transdisciplinary research encourages practices that flatten hierarchies; challenge power; promote diversification and inclusion of different disciplines, expertise, and ways of knowing; and question traditional research processes.

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Principles for place-based community participation

By James A. Turner.

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James A. Turner (biography)

How can a community’s sense of connection and responsibility to care for their place be strengthened? How can this lead to ground-up change, driven by communities, to tackle complex social, economic, and environmental issues? How can such change draw on the deep sense of care and belonging people feel for their communities and environments to tailor solutions to the unique needs and context of a place?

We identified eleven key principles associated with successful place-based community-led projects. These are the first principles to be developed in-country, rather than being imported from overseas and, because these are place-based, they are specific to Aotearoa New Zealand. We share them here to illustrate what specific place-based principles look like.

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Preparing interdisciplinary research teams for transdisciplinary co-production: A framework and diagnostic questions

By Emma Ligtermoet, Claudia Munera-Roldan, Cathy Robinson, Zaynel Sushil and Peat Leith.

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1. Emma Ligtermoet; 2. Claudia Munera-Roldan; 3. Cathy Robinson; 4. Zaynel Sushil; 5. Peat Leith (biographies)

How can interdisciplinary teams rapidly and collectively diagnose and design effective engagement approaches as they prepare for engaged (transdisciplinary) research? How can they build bridges with non-researcher societal actors to understand differences in language, methodology and even fundamental philosophies about ways and means of understanding the world?

We have developed a framework with context as the central feature, as this shapes all aspects of collaborative work. Context is then used to centre exploration of interconnected elements of positionality, purpose, power and process (4Ps).

Shared deliberation of the research context and the interconnected 4Ps requires an effective collective learning environment, which is upheld by the pillars of equity, trust, openness and inclusivity, and reflexivity.

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Planning transdisciplinary stakeholder workshops: Four practical lessons

By Maxine Fromm.

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Maxine Fromm (biography)

How can transdisciplinary researchers best organise workshops that create a collaborative space for different stakeholders? What practical planning is required? How can organisers meet the challenges of translating a project idea into concrete workshops?

This i2Insights contribution offers four practical lessons gathered throughout a dialogue series on a just industry transition between Dutch representatives from industry, non-governmental organisations, academia and ministries, which was organised by the Sustainable Industry Lab.

Lesson 1: Planning should start from your stakeholders’ needs

As Lisa Andrews and colleagues noted in their i2Insights contribution, Three lessons for mainstreaming transdisciplinarity, you need to ‘reach stakeholders where they are’ and take into account their knowledge levels, interests and agendas.

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Three key strategies enabling artificial intelligence to bridge inequities

By Kerstin Nothnagel.

kerstin-nothnagel
Kerstin Nothnagel (biography)

With artificial intelligence transforming many aspects of society, from healthcare to education to economic development, how can it be used to reduce rather than perpetuate inequalities? In particular, given that artificial intelligence can widen gaps by exacerbating existing inequalities through biased datasets, lack of infrastructure, and limited access to resources, how can the benefits of artificial intelligence be brought into the reach of low-income nations and marginalised communities? What practical steps can be taken to ensure artificial intelligence is developed and applied in a way that is inclusive and benefits everyone?

My work has been in the health field, but the findings are likely to be more broadly applicable. I suggest three strategies that would enable artificial intelligence to reduce inequities. The first two are key contributions that researchers can make. The third is a call to policy makers and funders. An example is provided for each strategy.

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Mobilizing the Arnstein Gap for better planning

By Keiron Bailey.

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Keiron Bailey (biography)

What is the Arnstein Gap? How can the Arnstein Gap usefully inform future citizen or stakeholder engagement?

Arnstein’s Ladder and the Arnstein Gap

Let’s begin with a brief reminder of Arnstein’s Ladder, which is a description of eight levels of public participation in government decision making developed by Sherry Arnstein in 1969 and illustrated in the figure below. More detail is available in the i2Insights blog post Stakeholder engagement: Learning from Arnstein’s ladder and the IAP2 spectrum by Gabriele Bammer. 

In 2006 my colleague Dr. Ted Grossardt and I introduced the Arnstein Gap (Bailey and Grossardt, 2006), which is the difference between the perceived and desired levels of public involvement according to Arnstein’s Ladder.

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Better understanding trust

By Gabriele Bammer.

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Gabriele Bammer (biography)

Trust is regarded as essential for effective teamwork and stakeholder engagement, so how can we better understand trust? How can that understanding underpin more effective action in establishing trust and in remedying loss of trust?

I use ideas about trust developed by Piotr Sztompka (1999) to reflect on trust in teamwork and in stakeholder engagement in research projects. Stakeholder engagement is divided into two broad types:

  • engagement with those affected by the problem being researched, and
  • engagement with those in a position to act on the problem; they are often decision makers.

Sztompka provides a useful definition of trust (p. 25) as:
“a bet about the future contingent actions of others.”

Trust consists of beliefs or specific expectations about others which influence how we act, what Sztompka calls “commitment through action” (p. 26).

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The enablers of effective knowledge exchange between science and policy

By Vivian Nguyen and Chris Cvitanovic.

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1. Vivian Nguyen (biography)
2. Chris Cvitanovic (biography)

What are the practical enabling conditions necessary for effectively implementing strategies to enhance knowledge exchange at the science-policy interface?

To address this question, we undertook a comprehensive and global review of the published literature in the field of environmental management. Specifically, following established scoping review protocols, we examined 56 empirical case studies that document enablers of effective knowledge exchange between science and policy. By doing so, we also identified and provided actionable insights that can help anyone working at the interface of science and policy to enhance their knowledge exchange efforts, ultimately leading to more impactful and desirable outcomes, and ensuring that the benefits of knowledge exchange efforts outweigh the cost of implementation.

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