It is a common assumption that quality evidence informs policymaking; however, during the 2020s, the notion of evidence (truth) is being disrupted by what has become known as a ‘post-truth’ environment. A post-truth environment is characterised by misinformation and disinformation, a decline in trust in experts, and social fracturing. In contrast, generative AI, a rapidly growing technology of the 2020s, adds an illusion of objectivity to generated responses to prompts, obscuring the situated and often dominant nature of outputs. Policymakers and the politicians directing them, developing and creating policy in this landscape, are not immune to the effects of a post-truth society and the allure of GenAI.
This presentation reports on early findings of a research project in Aotearoa New Zealand, considering what sort of evidence ‘counts’ in social wellbeing policymaking. In the project’s first stage, key informants were interviewed about their experiences of providing advice to policymakers. During these interviews, participants were questioned about their views on what evidence is, how mis- and disinformation might be affecting policy, and their thoughts on generative AI being used in policy development.
Analysis of these interviews draws on concepts of epistemic (in)justice and intersectionality, asking key questions about whose voices and whose knowledge systems are being privileged, obscured, and marginalised in the creation of governmental policy in a post-truth world. Questions and tentative suggestions are presented on how experts might navigate through this landscape.
Computational models have come to occupy a prominent position in UK policymaking, spanning domains from transport to public health. While increasingly detailed quality assurance processes have been developed, the function of computational models within policy processes remains under theorised and insufficiently scrutinised. In the context of metricised governance and persistent pressure to address complex, cross-cutting social problems within siloed institutional structures, models have been framed as a technological corrective; a mechanism through which complexity can be rendered tractable by converting social processes into quantifiable, algorithmic forms. This paper interrogates that framing.
Drawing on interviews and focus groups with over 30 policy makers, analysts and modellers working across national, devolved and regional government and policymaking in the UK, we examine the role of models across policy design, implementation and evaluation. Our analysis identifies the conditions under which models offer meaningful epistemic value for policy users, including the contextualisation of evidence, the projection of long-term impacts, and the elucidation of policy trade-offs. However, we also identify structural and institutional factors that constrain and distort model use, including the prospect for meaningful model scrutiny.
We argue that increasing model complexity, compounded by the prospect of future integration of artificial intelligence and machine learning, intensifies rather than resolves this tension. We contend that the most responsible and generative uses of models are exploratory and dialogic rather than predictive, positioning models as sites of or tools for deliberation, rather than sources of authoritative output. Realising this potential requires a reframing of how models are commissioned, built, used and scrutinised within policy institutions, and deeper integration with other forms of evidence, including that derived from lived experience.
Lived experience has become an increasingly prominent concept across academia, policy, and practice. Broadly, it refers to knowledge derived from direct, everyday engagement with an issue. Its intellectual roots span feminism, phenomenology, and ethnography (McIntosh & Wright, 2019), and it is often associated with goals of empowerment (Cahill-Ripley & Graham, 2022) and enhancing democratic legitimacy (Bua & Bussu, 2020). Given its varied interpretations and the ethical complexities of engaging with people who hold this form of knowledge, it is important to examine how lived experience is understood and operationalised within different institutional contexts.
The Scottish Parliament has invested resources into developing new processes to bring a more diverse range of voices into the work of Committees. Engagement with people with lived experience of the issue under scrutiny has become a key feature of evidence gathering processes. This paper presents the findings from research that sought to understand the extent to which lived experience is conceptualised as a form of evidence and the role it plays in scrutiny.
I argue that there are roles and value attributed to knowledge from people with lived experience that are specific to the context of Parliamentary scrutiny. These give rise to some challenges and complexities about who qualifies as having lived experience, what is considered authentic and the political considerations of how transparent Committees are when reporting these processes. The paper concludes with some recommendations for ethical practice within Parliaments and for the development of theories of lived experience as a form of knowledge.