Dr Hugo Confraria and Agustina Colonna
The 2030 Agenda for Sustainable Development and its Sustainable Development Goals (SDGs) acknowledge that science, research, technology and innovation (STI) are vital drivers of the global transformation towards a better and more sustainable future for all.
However, the impact of STI investments and policies on the SDGs is complex, often intangible and full of synergies and trade-offs.
As part of STRINGS’ work to better understand these complex relationships, we set out to analyse the main findings from publications (both scientific papers and grey literature) that examine the relationship between STI and the SDGs. This blog summarises the themes emerging from this literature review, and the implications for efforts to better align STI with the SDGs.
After developing a search methodology and selecting the most relevant literature produced between January 2014 and September 2020, we grouped the publications in four broad, related themes:
- Misalignment between STI investments and the SDGs.
- Approaches to shaping STI towards the SDGs.
- Synergies and trade-offs between SDGs.
- Monitoring of the success of STI for the SDGs.
Misalignment between STI investments and the SDGs
Publications in the first theme consider the reasons for the potential misalignments between STI investments and the SDGs.
One issue highlighted is the uneven distribution of STI activities across countries, which biases the focus of STI endeavours to thematic areas and societal problems unrelated to the problems of the worldwide majority1–4. For example, high-income countries perform most of their medical research on diseases (e.g. cancer) that are not the ones with a higher global disease burden (e.g. infectious diseases).
Another factor mentioned is that societal priorities differ substantially with economic status within countries. For example, according to a survey sent to 34 African countries5, hunger (SDG 2), health (SDG 3), water and sanitation (SDG 6), access to energy (SDG 7), and infrastructure (SDG 9) matter more to the poor. In contrast, the wealthiest respondents were more likely to cite jobs and economic growth (SDG 8) peace, justice and strong institutions (SDG 16) as priorities.
Since, in most countries, STI priorities emerge from complex interactions between policymakers, funders, researchers and innovators, each with their incentives and institutionalised practices, it is possible that in many cases STI prioritisation is not well aligned with the needs of the poorest.
Another important factor identified is that some forms of contemporary STI also contribute to environmental degradation, disruption of livelihoods and exacerbate inequalities6. UNDP (2018), for example, argue that at least nine SDGs could clearly be negatively impacted by advances in automation and artificial intelligence, primarily through the direct and indirect consequence of increased unemployment but also through threats in emergent sectors like the “gig” and “on-demand” economies.
Approaches to shaping STI towards the SDGs
The second theme identifies various approaches that can be taken to shaping STI towards the SDGs. They include:
- Directionality of STI policies towards the SDGs. This may take the form of challenge or mission-oriented approaches, or other incentives for directing STI activities towards the SDGs.6,8–10
- Plans, roadmaps or integrated assessments of STI investments and policy which are agreed by public, private and civil society actors.11–17 For example, identifying technology gaps or creating research and development roadmaps.
- Promoting inclusive and grass-roots innovation policies that consider the specific situations and needs of poor people, women and vulnerable groups to achieve more equitable, sustainable and inclusive development.6,18
- Strengthening national systems of innovation in developing countries (e.g. improving infrastructure, lowering barriers to technology deployment and diffusion, building STI literacy and capabilities, strengthening the science-policy interface) and fostering well-functioning institutions (e.g. strengthening political stability, educating workforces, strengthening the science-policy interface) in order to reinforce the economic, environmental, social and cultural resilience within societies that will contribute to the achievement of the SDGs.1,18–21
- Using the SDGs as an opportunity for developing countries to “leapfrog” to sustainable frontier technologies22. For example, some people in developing countries that have had no electricity until now are bypassing fossil fuels by adopting solar electricity and leaping directly to the stage of renewables. By doing this, they are not only contributing to the realisation of SDG 7, but also developing capabilities and skills in a set of technologies that will be critical in the future.
- Finally, another framework looks at the transformations/transitions23–25 required in the wider economy to achieve the SDGs by 2030 (e.g. where technology ownership and control lies, its existing orientation and focus, etc.).
Synergies and trade-offs between SDGs
The third theme relates to the synergies and trade-offs between SDGs. It is argued that studying the interaction between SDGs is essential for the efficient design of public policies, since an integrated approach can save resources and reduce costs by exploiting the positive interlinkages (“synergies”) and minimising the negative ones (“trade-offs”)26–33.
The literature has applied various methodologies to study the linkages between SDGs, although most analysis assesses these interactions at the target level. On the empirical side, many authors have used time series of SDG indicators to correlate progress between them34–36.
Other approaches have relied on expert opinion, theoretical models or a review of the literature to identify essential interlinkages37–41. Additionally, text mining approaches have proven to be a successful methodology used in the literature to assess synergies and trade-offs42,43. For instance, Le Blanc (2015) finds that from 107 targets, 60 explicitly refer to at least one other goal than the one to which they belong. This aspect of the SDGs is frequently mentioned as an improvement on the Millennium Development Goals, which did not form such an integrated system44.
Overall, there is an agreement on the fact that positive interactions between SDG targets outweigh the negative ones36–38,45, however, there is also consensus that the interactions between SDGs are greatly context-dependent. Namely, that the relationships between different SDG targets can depend on the geographical locations, governance context, number and types of people affected, and its time frame27,37,46.
For example, increasing fishing activity in a certain region can lead to a reduction of hunger and improved livelihoods in the short-term. With time, however, fish stocks may be at risk of becoming overused with the same effort leading to less and less yield unless sustainable management practices are put in place. The context-dependencies listed previously often make it difficult to draw generalisable conclusions about interactions that may ultimately depend on locally specific factors38.
Monitoring the success of STI for the SDGs
The inherent complexity of all 17 SDGs and the variety of pathways by which different areas of STI can contribute to the achievement of specific targets makes it very difficult to rigorously evaluate progress and impact15,47,48. Yet, the existence of indicators aligned with the SDGs targets and rules for the collection of standardised data open an important opportunity for the monitoring and control of the relations between STI and the SDGs49–51.
An important issue relating to SDG indicators is that many national statistical systems have faced severe challenges in tracking progress, which requires an unprecedented amount of data and statistics at all levels52.
An analysis of the indicators in the Global SDG Indicators Database53 reveals that for four of the 17 goals, less than half of the 194 countries or areas have internationally comparable data. Even countries with available data have only a small number of observations over time, making it difficult for policymakers to monitor progress and identify trends.
Therefore, increased investments in national data and statistical systems and the mobilisation of additional international and domestic resources are needed to maintain adequate coverage of all population groups, as well as to guarantee the internal consistency, comparability and overall quality of data produced to advance implementation of the 2030 Agenda.
This is especially relevant in lower-income contexts, where these actions and investments should be complemented by an operational/technical assistance budget dedicated to monitoring and evaluating policy. It is argued that, in these contexts, enhancing capacities related to monitoring and accountability seems to be essential to set up policies that contribute to achieving the SDGs 13,54,55.
Finally, on a positive note, it has been argued that advances in technology and the proliferation of data are providing new opportunities for monitoring and tracking the progress of the SDGs. A promising avenue is the data produced through citizen science, which can complement and ultimately improve the SDG reporting process56,57. In this vein, Fritz et al. (2019), demonstrate the value of using data from citizen science for the SDGs, and provide concrete examples of how such data are currently being adopted and potential areas for future contributions. For example, volunteers in the Philippines are collecting household census data on poverty, nutrition, health, education, housing and disaster risk reduction, which are used by the Philippine Statistics Authority to enhance their statistics on 32 SDG indicators.
In summary, this literature review found many publications proposing approaches to helping shape STI investments and policies towards the SDGs. Yet, we found that less effort has been made in trying to understand what works and how to evaluate the efficacy of such approaches.
This gap is one of the things we are working on in STRINGS. By developing methodologies that help track misalignments between STI and the SDGs at the global level (for example, using bibliometric and SDG indicator data) and by analysing how policies are working, or not, to achieve the SDGs in our case studies in East Africa, India and Latin America, we are seeking to address this important question.
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