A US research collaboration resulting in potentially dangerous drone technology being developed with an Iranian university could’ve been easily prevented with an unclassified research security check, says an expert from technology company Digital Science.

Sergeant Major (ret.) D.J. Gile, a twenty-four year Army veteran of special operations and intelligence and now Vice President of National Security at Digital Science, said government agencies and research institutions could take some important lessons from the case, which was exposed by The Guardian newspaper.

Reporters found that academic institutions from the United States, the United Kingdom, and Australia had collaborated with researchers affiliated with a financially-sanctioned Iranian university known for its close ties to the military. The research was described as having direct military applications.

“With significant national security consequences – and lives at stake – research institutions and agencies should ensure they have the right information to enable decision-making and compliance with national security policies,” Gile said.

“The unintentional collaboration with Iran is a key example of where having the right information available could save everyone from making a mistake they might later regret.”

“This research was funded and performed by Five Eyes countries despite claims that the researchers in question had no ties to Iran. These research collaborations could have been flagged and avoided with the use of Dimensions Research Security to check important details such as affiliations, collaborations, and funding sources,” he said.

More government and industry-backed research institutions in Five Eyes nations are turning to technological solutions to help safeguard their research against foreign influence and theft. A Digital Science solution, Dimensions Research Security enables compliance with policies and security requirements aimed at safeguarding against key threats, such as:

• Foreign influence and interference
• Conflicts of interest
• Undeclared research collaborations
• Intellectual property theft

With the world’s largest collection of linked research data, Dimensions Research Security can quickly and easily collate, link, and cross-reference patents, publications, funding sources, and even institutions’ research activities and the activities of individual researchers, and their colleagues and collaborators.

“Gaining valuable insights into such data means having a greater awareness of risks associated with individuals, their collaborators and funding sources. This can help with due diligence checks, verifying disclosures, and strategic decision-making,” Gile said.

“Researchers may be unaware they’re involved in collaborations that put themselves, their research, and their institutions at risk. The information provided by Dimensions Research Security could be instrumental in speaking with researchers about risk and compliance, helping to avoid foreign influence, and intellectual property theft – and helping to safeguard the nation’s interests,” he said.

Government agencies and academic institutions in Five Eyes nations – including those conducting defense and cyber security research – are already depending on Dimensions Research Security to protect their organizations. For more information, click the link below:

Find out more about Dimensions Research Security and request a demo today.

(This is an updated version of an original article published by Executive Biz: https://executivebiz.com/2024/06/digital-science-proposes-more-secure-pathway-for-government-research/)

The post US funds supported Iranian military drone tech – here’s how It could’ve been prevented appeared first on Digital Science.

Esther is the Founder of Wellville, a 10-year project to improve health care. A longtime tech analyst and investor, Esther is also an expert in health and technology. Wellville’s mission is to improve community health outcomes and foster long-term wellness by innovating at the intersection of health, technology, and community development.

Subscribe now to be notified of each weekly release of the latest TL;DR Short, and catch up with the entire series here. 

If you’d like to suggest future contributors for our series or suggest some topics you’d like us to cover, drop Suze a message on one of our social media channels and use the hashtag #TLDRShorts.

The post TL;DR Shorts: Esther Dyson on whether all tech is good tech appeared first on Digital Science.

Artificial intelligence (AI) has tremendous potential to transform economies and societies around the world. However, AI research and development remain highly uneven across different countries, regions and organisation types. In this analysis, we explore a few indicators that highlight the growing global divide in AI capabilities.

To define the field of AI for our analysis, we relied on the Fields of Research classification system which comes out of the box in Dimensions. Specifically, using current consultancy work we considered AI research to span the following Fields of Research:

Basic AI Fields:

• 4602 Artificial Intelligence
• 4611 Machine Learning

Applied AI Fields:

• 3102 Bioinformatics and Computational Biology
• 4903 Numerical and Computational Mathematics
• 3407 Theoretical and Computational Chemistry
• 5204 Cognitive and Computational Psychology

Distribution of AI research publications

Geographic distribution

This striking cartogram Figure 1 visualises the global landscape of artificial intelligence (AI) research from 2014-2023 based on academic publication outputs from countries around the world. The contours of each landmass depict the number of peer-reviewed papers contributed over the decade across core AI subfields spanning machine learning to computational mathematics.

Mirroring the data, the US dominates the cartogram with a swollen territorial outline reflecting its pole position – American institutes produced over 772,000 papers, accounting for a huge 30% share globally. China remains a major leader at approximately 465,000 papers or 18% share.

Beyond the two giants, moderately sized outlines mark the UK, Germany, Japan and others like India, Brazil and Iran – highlighting established AI research strongholds churning out 10,000 to 140,000 papers each over the period. Meanwhile Africa, South America and most Asian nations appear paltry, indicating largely untapped AI potential with less than a 5% collective contribution.

While North America, East Asia and select countries in Europe and Oceania show depth, the visual makes the divide across the Global South stark – over 80% of the world’s population reside here but with little access to resources critical to unlocking AI capabilities seen elsewhere. Addressing these deep disparities should be a top priority for transitioning towards more equitable and inclusive AI development globally.

To understand the extent of the global divide in the last 12 years, we analysed the trends in the top 10 countries that published AI research, based on Dimensions’ data for 2012-2023. 

The EU27 published over 30,000 AI papers annually in the early time period, leading global output. However, China has since surpassed the EU27, rapidly rising from around 13,000 papers in 2012 to become the leading publisher with nearly 60,000 in 2023. The US which started in second position follows in third now, though its publication volume has levelled off in recent years after its initial first ranking. India has experienced major growth, with over 17,000 AI papers in 2023 compared to under 4,000 a decade prior; it even overtook the UK, which started in fourth position. Canada, Australia, Japan, Russia and South Korea maintain top 10 presence, though their year-to-year output has declined mildly in the most recent years.

The data shows emerging economies like China, India and others gaining ground in AI research, reflected by their rapidly growing publication output over the past decade. Though traditional leaders in North America and Europe continue to produce high volumes, developing countries are claiming more seats at the table and diffusing expertise globally. There is still an advantage skewed towards wealthy regions. But the statistics indicate dividing lines blurring as the playing field levels to some extent, allowing more nations to drive progress based on their own interests without barriers previously faced. Whilst gaps remain in scale and infrastructure, the global AI research landscape exhibits increased participation beyond just an exclusive Western bloc.

Balance university vs company research

We have used the Global Research Identifier Database (GRID – a database of educational and research organisations worldwide) typology to understand the distribution of AI publications between public and private research institutions from 2012-2023. GRID distinguishes organisations into categories like Archive, Company, Education, Facility, Government, Healthcare, Nonprofit, and Other.

Across all Fields of Research, the distribution of research organisation types has remained very stable from 2012-2023 across all fields, as Figure 3 shows. Education institutions (universities) produce the most research, followed by Healthcare (hospitals), Facilities (specialised research institutions), Government, Companies, Nonprofits and Archives (libraries, museums).

However, the distribution differs slightly for AI research specifically, as seen in Figure 4. While Education still leads in AI, Facilities overtake Healthcare for the second spot. Companies also publish more AI research than Governments since 2021, having surpassed Nonprofits back in 2018.

The increase in AI research authored by companies presents some concerns. Primarily, there lies an inherent conflict of interest, as companies have financial incentives to promote their own AI products and services. Their research may present biassed, overtly positive conclusions that omit negative findings, skewing the literature compared to more objective academic work.

In addition, corporate research often lacks transparency about underlying data, methods, and disclosure of limitations. Companies also frequently patent algorithms, data, and innovations based on their published research, restricting access in ways that limit follow-on research progress and collaboration.

Furthermore, the priorities guiding corporate AI research cater more closely to commercial opportunities rather than pure scientific or social value. This means that important basic research with less immediate real-world application is at risk of becoming underfunded. Lastly, the underlying profit motives may override ethical considerations around things like algorithmic bias, privacy, and security – issues that companies have less incentive to study or address.

Global North vs Global South

The following figures – 5a and 5b – show the same data in the Global North (5a) and Global South (5b). Both distributions stayed relatively stable throughout the period; the 2 largest organisation types for both were Education and Facility. However, at the start of the period, Governmental organisations were in third position in the Global South, until 2018 when it was overtaken by Healthcare organisations. Non-profit organisations publish in the Global North but very marginally in the Global South, while Companies publish more in the Global North and have an increasingly important presence in the Global South.

Funding trends

Geographic trends

Dimensions contains data about research fundings publicly available – either from the public or the private sector. We find that the dominance of China and the US in AI research output correlates strongly to funding trends. 

The following figure shows global AI research funding trends from 2012 to 2020 as found in Dimensions. Analysis of the number of AI research grants funded between 2012-2020 revealed rapidly rising investment – 58.3%, while global funding across all fields of research has grown only 55.8% – across advanced and emerging economies. 

The data shows the United States maintains clear dominance, increasing grants from 10,210 to 11,467 over the period examined. But Japan and China posted larger overall gains as percentages to secure second and third place in total grants by 2020. Japan more than doubled funding, granting 3,755 in 2012 swelling to 6,465 in 2020. China’s trajectory stands out, going from 4,267 to 7,345 to surpass the European Union bloc’s relatively flat numbers. Notably, the UK doubled their numbers from 2012 to 2020. 

While the order shuffled, the top 10 country funders collectively ramped up research commitments substantially. Growing global recognition of AI’s revolutionary potential across practically all major industries drove heavier funding year after year from both traditional leaders and chasing contenders. If the world maintained this pace, analysts forecast total AI research funding could double again before 2030.

The data shows Brazil was consistently one of the top 10 countries providing AI research grants over the past decade, ranking 7th among those listed. As the only non-Western/European country besides China to make the top 10, Brazil’s presence highlights broader global interest and investments in AI research beyond just dominant Western regions. Though its number of AI grants is not as high as leaders like the US and EU27, the fact that Brazil has sustained over 1,200 grants annually signifies meaningful national support and participation in this research area among emerging economies. Brazil maintaining its 7th place ranking throughout the 9-year period reflects persistent research activity and funding commitments rather than being overtaken by other developing nations.

Conclusion

There are stark global divides in artificial intelligence (AI) research and development, with both publications and grants heavily concentrated in a few advanced countries over the past decade. The landscape of AI papers is dominated by the US and China, which have produced around 50% of all publications. A similar pattern emerges in AI grants, with the US and China also providing the most funding annually. A handful of other developed nations like the UK, Germany, and Japan have established strongholds in both metrics, collectively accounting for another substantial portion of global research outputs and total grants. However, the vast majority of the developing world – encompassing most countries across Africa, South America, and Asia – contributes under 5% in both metrics, significantly lagging in critical resources for progressing AI research.

While China has rapidly grown to lead AI publications, surpassing the EU, it still trails second behind the US in terms of number of AI grants funded. Emerging economies like India and Brazil are making consistent gains increasing research participation and grants provided. But their output and funding levels are still below AI research leaders. The data highlights how a handful of advanced Western countries and China continue to vastly outpace most other nations in both key AI research metrics. Though divides show some signs of blurring, deep funding and infrastructure disparities persist globally.

The post Research on artificial intelligence – the global divides appeared first on Digital Science.

We are not yet seeing large-scale fragmentation, but there are initial signs,” said World Trade Organization chief Ngozi Okonjo-Iweala. This trend is, firstly, dangerous and, secondly, could ultimately prove to be “very costly”. “Let’s rethink globalization.” WTO chief warns of “dangerous” fragmentation of world trade.

Source: Der Spiegel

A brief investigative commentary

Reshoring, also known as ‘onshoring’, involves the returning of production and manufacturing of goods to the company’s original country. It can help strengthen an economy by creating manufacturing jobs and reducing unemployment.^[1]

Offshoring, on the other hand, can be framed as the relocation of value chain activities from a firm’s country of origin to foreign locations as outsourcing and investing, and has often been associated with strategies pursuing cost savings, and increased revenues.^[2] It is the opposite of reshoring where companies bring production and manufacturing back to the country in which it was first established.^[3]

In today’s uncertain world, reshoring is often depicted as the successor to offshoring.  However, recently, a new term has emerged – ‘friendshoring’ which refers to the rerouting of supply chains to countries perceived as politically and economically safe or low-risk, to avoid disruption to the flow of business.^[4]

As countries around the world, especially in Asia, continue to develop, labor costs are increasing and shipping costs are becoming prohibitive. For some businesses, the cost difference between operating onshore or offshore is negligible, and thus the gap is growing smaller. However, one of the main disadvantages of offshoring reverting to reshoring is the huge costs involved in moving manufacturing operations from one country to another.

Moreover, considering the instability of international trade – the geopolitical situation has changed dramatically over the past decade, with China showing signs of taking a leading role in trading internationally. Meanwhile, with the US taking a more cautious position and other changes that have happened in global trade relations (such as Brexit), having overseas operations represents a much higher risk today.^[5]

In the UK, following Brexit and Covid-19, the focus of reshoring is moving back to its own shores in attempts to strengthen its manufacturing resilience and to ensure its supply chains in a fragmented world.^[6]

…the number of research publications associated with offshoring vastly outweighs that of reshoring. However, what is of more interest is looking at trends over time.”

The empirical evidence on reshoring in the last decade highlights that reshoring processes are on the rise, with larger firms and medium to high-tech industries exhibiting the greatest reshoring propensity.^[7]

Using data in Dimensions, we take a brief look to see what trends are evident. Is reshoring (fragmentation) on the rise at the expense of offshoring (globalization)? Globalization is used here as a proxy for offshoring and fragmentation is used as a proxy for reshoring.

We created two simple keyword searches in Dimensions, the first, ‘reshoring’ and the second, ‘offshoring’. The data produced by Dimensions reveals that overall the number of research publications associated with offshoring vastly outweighs that of reshoring. However, what is of more interest is looking at trends over time.

Figure 1 demonstrates that in the last 10 years the trend in research associated with reshoring has been mostly upward, whereas for research associated with offshoring there is evidence that research associated with offshoring is marked by a sizable downturn from 2012 and has not recovered.

Figure 1 below outlines trends over time and where we see that offshoring, depicted by the darker blue line, peaks in 2012 and then declines rapidly, and does not recover in terms of numbers of published papers. For ‘reshoring’ we see the opposite trend – virtually no research published until 2012 followed by a continuous upward trend. These observations are in line with what we might see as a paradigm shift in manufacturing from global to fragmented.

Similarly, depicted below, we find equivalent trends for policy documents (albeit with smaller numbers – see Figure 2) – policy documents associated with ‘reshoring’ not starting to be documented until 2019 and continuing to rise, whereas for policy documents related to ‘offshoring’ the trend started much earlier, in 2014, showing a much more checkered increase until 2013 where we see it decreasing, and dwindling to zero in 2022.

…decisions to reshore are becoming increasingly popular in both Europe and the US, with businesses reversing prior decisions to offshore.”

Conclusion

We can make a number of conjectures from this simple analysis. First, that there is indeed a shift from globalization towards fragmentation from the perspective of what are known as ‘value chain activities’, particularly production in manufacturing.^[8]

Second, although, as the WTO chief states, we are not yet seeing large-scale fragmentation, the signs are there and decisions to reshore are becoming increasingly popular in both Europe and the US, with businesses reversing prior decisions to offshore.^[9]

A further point – following the simple analysis carried out in this piece – is that research publications outlined related to offshoring start to increase rapidly from 2003, whereas for the research relating to ‘reshoring’ the research does not start to increase until ten years later in 2013. This bolsters the empirical evidence that globalization (offshoring, or moving production to foreign locations) is perhaps giving way to fragmentation (reshoring, or localization of production closer to home).

References

^[1] https://www.tandfonline.com/doi/full/10.1080/21681376.2023.2199054

^[2] https://www.sciencedirect.com/science/article/pii/S0148296323003636?ref=pdf_download&fr=RR-2&rr=81703bfd584f4887#b0810

^[3] https://www.xometry.com/resources/procurement/what-is-reshoring/

^[4] https://www.weforum.org/

^[5] https://www.xometry.com/resources/procurement/what-is-reshoring/

^[6] https://www.dudleyindustries.com/news/benefits-of-reshoring-manufacturing-to-the-uk

^[7] https://www.europarl.europa.eu/RegData/etudes/STUD/2021/653626/EXPO_STU(2021)653626_EN.pdf

^[8] https://www.sciencedirect.com/science/article/pii/S0148296323003636?ref=pdf_download&fr=RR-2&rr=81703bfd584f4887#b0810

^[9] https://reshoring.eurofound.europa.eu/

The post In the spotlight: Reshoring vs offshoring in a geopolitically uncertain and fragmented world appeared first on Digital Science.

In this blog series, we will explore the Fragmentation of Artificial Intelligence research. This first post lays out some of the key areas where AI research and development have become disconnected, making it more difficult to advance the field in a coordinated, ethical, and globally beneficial manner.

Artificial Intelligence (AI) is a recent discipline, having started in the 1960s, which aims at mimicking the cognitive abilities of humans. After going through a few “winters of AI” in the 70s and 90s, the field has been experiencing a boom since the 2010s thanks to increased computing capacities and large data availability.

The interdisciplinary foundations of AI draw from diverse fields across the sciences, technology, engineering, mathematics, and humanities. Core STEM disciplines like mathematics, computer science, linguistics, psychology, neuroscience, and philosophy provide vital technical capabilities, cognitive models, and ethical perspectives. Meanwhile, non-STEM fields including ethics, law, sociology, and anthropology inform AI’s societal impacts and governance. Together, this multidisciplinary collaborative approach aspires to enable AI systems that not only perform complex tasks, but do so in a way that accounts for broader human needs and societal impacts. However, significant challenges remain in developing AI that is compatible with or directed towards human values and the public interest. Continued effort is needed to ensure AI’s development and deployment serve to benefit humanity as a whole rather than exacerbate existing biases, inequities, and risks.

Global divides

Research is globally divided – the high income countries in particular are the biggest publisher of peer-reviewed publications and the biggest attendee group at research conferences. This is especially true in AI research, with AI researchers from poorer countries moving to hubs like Silicon Valley. This is, in part due to the lack of cyber infrastructure in many countries (GPU, electricity reliability, storage capacity, and so on), but also for countries in the non-English speaking world there may be a lack of, to data availability in their native language. 

The concentration of AI research in high-income countries has multiple concerning consequences.: First, it prioritizses issues most relevant to high income countries while overlooking applications that could benefit lower income countries (e.g. iImproving access to basic needs, such as clean water and food production; diagnosis and treatment of diseases more prevalent in low-income regions). Second, the lack of diversity among AI researchers excludes valuable perspectives from underrepresented groups including non-Westerners, women, and minorities. Policies and ethics guidelines emerging from the active regions may not transfer well or align across borders.

In a third blog post of this series, we will investigate the global division of AI research, and look into the possible solutions. 

Siloed knowledge

However, in recent years research in AI has become so specialised that it is difficult to see where AI starts and ends. A great example of this is the fact that many AI-related considered research publications are actually not classified as “Artificial Intelligence” in Dimensions. Take the AlphaFold publications, these are considered Bioinformatics and Computational Biology, rather than Artificial Intelligence. Many consider Machine Learning to be a subfield of Artificial Intelligence, however the Fields of Research separates both and puts them at the same level.

As AI research spreads to different fields, progress is more difficult to spread – researchers in different disciplines rarely organise conferences together, most journals are specialised into one field of research, researchers’ physical departments in universities are spread across buildings, and therefore there is less collaboration between them. Any progress such as thatprogress required to make AI more ethical, is less likely to spread evenly to every applied AI field. For instance, transparency in AI, which is still in infancy and developedhappened thanks to collaboration between ethics and AI, will take more time to reach AI applied in Physics, Chemistry, and so on. 

Do the benefits of AI application in other research fields outweigh the difficulties in applying AI advancements? And how much interdisciplinary actually happens? This will be the inquiry of our second blog post of this series.

Policy framework

Globally, government policies and regulations regarding the development and use of increasingly powerful large language models (LLMs) remain fragmented. Some countries have outright banned certain LLMs, while others have taken no regulatory action, allowing unrestricted LLM progress. There is currently no international framework or agreement on AI governance; efforts like the  Global Partnership on Artificial Intelligence (GPAI) aims to provide policy recommendations and best practices related to AI, which can inform the development of AI regulations and standards at the national and international levels. It tackles issues related to privacy, bias, discrimination, and transparency in AI systems; promotes ethical growth development, and encourages collaboration and information sharing.

AI policies vary widely across national governments. OIn 2022, out of 285 countries in 2022, just 62 (22.2%) countries had a national artificial intelligence strategy, seven7 (2.5%) were in progress and 209 (73.3%) had not released anything (Maslej et al. 2023). Of those countries that took a position, the US at that time focused on promoting innovation and economic competitiveness, while the EU focused on ethics and fundamental rights. On October 30th the US signed their first executive order on AI (The White House 2023), which demands the creation of standards, more testing and encourages a brain gain of skilled immigrants. At a smaller scale, city-level policies on AI are also emerging; sometimes conflicting with national policies. San Francisco, for instance, banned police from using facial recognition technology in 2019. 

Ultimately, AI regulations tend to restrict AI research, which if it happened unevenly around the world would create centres of research where less regulations take place. 

How does this varied policy attitude affect the prospects of AI research? Will this lead to researchers migrating to less restricted regions? Such will be questions addressed in another blog post. 

Bibliography

Maslej, Nestor, Loredana Fattorini, Erik Brynjolfsson, John Etchemendy, Katrina Ligett, Terah Lyons, James Manyika, et al. 2023. ‘Artificial Intelligence Index Report 2023’. arXiv. https://doi.org/10.48550/arXiv.2310.03715.

The White House. 2023. ‘FACT SHEET: President Biden Issues Executive Order on Safe, Secure, and Trustworthy Artificial Intelligence’. The White House. 30 October 2023. https://www.whitehouse.gov/briefing-room/statements-releases/2023/10/30/fact-sheet-president-biden-issues-executive-order-on-safe-secure-and-trustworthy-artificial-intelligence/.

The post Fragmentation of AI research: a blog series appeared first on Digital Science.

It may take a militarily powerful nation to establish a language, but it takes an economically powerful one to maintain and expand it.^[1]”

David Crystal.

A short commentary

In this short opinion piece we look at English as the universal form of communication in science, in fact, the language of both science and technology.

Although many countries still publish journals in their native tongue, English is currently still the ‘best’ way to share research findings with scientists in other parts of the world.^[2] However, from a historical perspective, this has not always been the case. Egyptian philosophers and stargazers told stories in hieroglyphs. Aristotle and Plato wrote books in Greek, which were then translated into Arabic by their followers. Then came the Romans, who wrote in Latin. It was not until the 20th century that English started to dominate.^[3]

English as today’s global ‘lingua franca,’ is the language most widely spoken throughout the world even though the vast majority of English speakers are not ‘native’ speakers of the language. Of approximately 1.5 billion people who speak English, less than 400 million use it as a first language which means that over 1 billion speak it as a second language.

With today’s technological advances, English as the global language of science and innovation could change by reducing the need to learn English as a language for international communication. AI language tools are becoming increasingly sophisticated and AI-powered translation could potentially create more fair access to science.^[4] Moreover, the rise of China’s research productivity and published research output could have a big impact on how we communicate science.^[5] The bias, if it can be called a bias, towards the use of English in the current global scientific landscape, however, can lead to barriers for those who are non-native English speakers and also to important research study outcomes being overlooked because they are not written in English.

With today’s technological advances, English as the global language of science and innovation could change”

The consequences of overlooking non-English science may be more serious than just revealing a lack of access to information written in languages other than English. For example, in a study published in PLOS^[6], it was identified that important papers reporting the infection of pigs with avian influenza viruses in China were initially going unnoticed by international communities, including the World Health Organization and the United Nations Food and Agriculture Organization. This was because they were published in Chinese-language journals^[7]. Likewise, in one of the non-English scientific papers it was reported that “urgent attention should be paid to the pandemic preparedness of these two subtypes of influenza”^[8]. It took 14 years for this finding to be picked up and reported on in the English language.

In a 2021 study, Plos Biology screened 419,679 peer-reviewed papers in 16 languages in the field of biodiversity and found that non-English-language studies can expand the geographical coverage of English-language evidence by 12% to 25%, especially in biodiverse regions. As with the study in the previous paragraph, the authors of this study urge wider disciplines to reassess the untapped potential of non-English-language science in informing decisions to address other global challenges.^[9]

Today the populations of native speakers of other languages are all growing faster than the population of native English speakers. About three times more people are native Chinese speakers as are native English speakers. Languages such as Hindi-Urdu, Arabic, Spanish, to name a few, are about the same as those whose native language is English, all of which are growing faster than native English speakers.

Many scientific papers go unnoticed because of the linguistic gap between the global north and the south. English has become the lingua franca of science to ease collaboration but has it really managed to do so? In fact the dominance of the English language risks excluding some of the global south countries.

Digital Science, as the creator of the world’s largest linked database for research information, Dimensions, is able to search the data it holds to find the language in which research publications are written. This is done using an algorithm to detect the language of publications.^[10] The total number of research publications currently stored in Dimensions is 139,644,299 and the table below highlights the probable numbers and percentages of publications in the top six languages of publication along with the number and percentage of publications where no language is detected. The total number of research publication languages in Dimensions is 148, ranging from a language with one publication to the highest numbers of publications set out in Table 1 below.

We also looked at trends over time (2001-2022) for the the top ten non-English language publications sourced from Dimensions (see Figure 1 below).

The top 10 non-English language publications and the percentage overall, show that a number of the top languages in the 2000s (in particular, French, German, Chinese, and Japanese) have waned in the 2010s; whereas others (Russian, Spanish, Portuguese, and especially Arabic, Turkish, and Indonesian) have increased significantly.  

In terms of non-English language research coverage in Dimensions (at least for the sum of the top ten 10 other languages), there has been a growth within the publications corpus from  circa 6% in 2001 to greater than 9% in 2022. We might conclude here that there is either an effect of more non-English research being indexed by Dimensions or that there are beginning to be signs of researchers publishing in their own language when it is other than English.

Perhaps it is time for the scientific world to acknowledge and embrace work published in all languages to help diversify science thereby enriching research globally.”

Conclusion

As we outlined, the language gap between the Global North and Global South is likely to have excluded much of the research in the lower income countries. As long as English remains the language for scientific communication, many people of other cultural backgrounds will continue to find it increasingly difficult to participate in the scientific process and benefit from its outcomes.^[11] With regard to patterns of non-English publishing over time, we cannot rule out that the increases that we see are not a product of Dimensions amassing more non-English research output, but, at the same time it could be that publication patterns have made shifts to digital and/or open access publications that have affected what is included in the Dimensions database. 

Perhaps it is time for the scientific world to acknowledge and embrace work published in all languages to help diversify science thereby enriching research globally.

Acknowledgement

Thanks to Alex Wade, VP Data Products, Digital Science, for providing time trends data and graph.

References

^[1] https://culturaldiplomacy.org/academy/pdf/research/books/nation_branding/English_As_A_Global_Language_-_David_Crystal.pdf

^[2] https://www.nature.com/articles/d41586-021-00899-y

^[3] https://scientific-publishing.webshop.elsevier.com/manuscript-preparation/why-is-english-the-main-language-of-science/

^[4] https://www.nature.com/articles/s41562-023-01679-6

^[5] https://scientific-publishing.webshop.elsevier.com/manuscript-preparation/why-is-english-the-main-language-of-science/

^[6] https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7094971/pdf/41586_2004_Article_BF430955a.pdf

^[7] https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7094971/

^[8] https://europepmc.org/article/cba/580966

^[9] https://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.3001296

^[10] Algorithm available on request.

^[11] https://www.frontiersin.org/articles/10.3389/fcomm.2020.00031/full

The post In the spotlight: English as the lingua franca in science appeared first on Digital Science.

At this critical juncture, midway to 2030, the evidence makes clear that incremental and fragmented change is insufficient to achieve all 17 SDGs in the remaining seven years, or even by 2050.”

Antonio Guterres

UN Secretary General, 2023

A short commentary

2023 marks the halfway point between 2015 (the entry point of the Sustainable Development Goals – SDGs), and 2030 (the end point of the SDGs).^[1] As it stands currently, the world is off track to achieving the SDGs^[2] and action is necessary to accelerate their implementation.

The 17 Sustainable Development Goals^[3] remain an increasingly important platform, and are the best roadmap that we have currently for achieving global sustainable development. To effectively realise what is known as the 2030 Agenda for sustainable development, there needs to be evidence of “a shared sense of common purpose”. However, progress on achieving the 2030 Agenda has been severely disrupted due to multiple world crises. Thus a joint effort utilising multi-stakeholder partnerships to help to achieve the SDGs is paramount at this halfway point.

Research looking at the fragmentation of SDGs reveals some interesting insights from a number of perspectives. For example, a recent study has found that at this halfway point, silos are strengthening around the 17 SDGs and their three dimensions (social, economic and environmental) producing a fragmented state.^[4] The study, carried out by researchers at the University of Utrecht, looked at the network of international organisations assessing how they had either come together or diverged since the SDGs came into effect in 2016. The research found that overall fragmentation had not decreased in the network since SDG implementation, but did find that international organisations with a focus on the three dimensions of SDG policies displayed different tendencies. For example, social international organisations are least likely to cooperate with others outside the social dimension and are hence most siloed. Environmental international organisations, conversely, are most inclined to cooperate with others outside their dimension, however, the study found that this has diminished over time.^[5]

In a report by the United Nations Development Programme, according to the IMF, global financial fragmentation caused by geopolitical tensions has increased economic fragility.  This has resulted in rising socio-economic inequality contributing to reduced global trade and social tensions in both developed and developing countries, threatening progress on the SDGs.^[6]

The governance in global sustainability is important for bringing together the 191 SDG member states and international organisations that are tasked with working towards realising the Goals. Currently though, this governance is notable in its distinct clusters of international organisations working in a siloed fashion thereby leading to a fragmented system. SDG17 – Partnership for the Goals – emphasises the global partnership that is necessary for achieving all of the SDGs and strengthening inter-organisational coordination and cooperation and is recognised as an important challenge in global sustainability governance. However, geopolitical tensions have made it more difficult to achieve this and cooperation and coordination are necessary now more than ever to speed up the implementation of the SDGs.

Advancing and achieving the SDGs in a world with increased complexity and fragmentation is not an easy task. A complex network of interconnections exist across the SDGs and show how actions directed towards one SDG can influence others. For example, food production (SDGs 1 and 2) is increasingly threatened by air pollution (SDG13), which affects soil quality (SDG15) and crop yields (SDG2). The 2023 Global Sustainability report highlights that an interconnected and systemic approach will be key and shows new evidence that understanding the interconnections between individual goals (as we see above) will be essential. The intertwinings and interdependencies that exist should mean that they cannot fragment. However, this is not the case according to research highlighted above, nor is it for research looking at fragmentation as an enduring feature of the SDGs and the global landscape.

The viewpoint we have taken for this short piece emphasises geopolitical tensions and international organisations/governance as two themes by which to briefly take a look at the narrative in this area. One of the central premises is that the SDGs by their very nature are interwoven and connected and so there should be no room for fragmentation, but what we see is that individually and collectively (by their three dimensions) SDG fragmentation has emerged in a number of different ways.

References

^[1] https://www.un.org/en/conferences/SDGSummit2023

^[2] https://www.un.org/sustainabledevelopment/blog/2023/09

^[3] https://sdgs.un.org/goals

^[4] https://www.sciencedirect.com/science/article/pii/S0959378022001054#b0610

^[5] https://www.sciencedirect.com/science/article/pii/S0959378022001054

^[6] https://www.undp.org/publications/fragmentation-integration-embedding-social-issues-sustainable-finance-0#:~:text=The%20paper%20From%20Fragmentation%20to,of%20a%20market%2Dbased%20economy

The post In the spotlight: Have the SDGs failed to reduce fragmentation in global sustainability? appeared first on Digital Science.

Update: Video recording of the session now available.

Well, Falling Walls certainly lived up to expectations! It’s six years since I was originally slated to attend but had to hand presentation duties over to my cofounder due to the birth of my youngest daughter, Annabelle.

I was fortunate to be able to attend in person this year, and today started with a wonderful panel session on the “Implications of AI for Science: Friend or Foe?”, chaired by Cat Allman who has recently joined Digital Science (yay!) and featuring a brilliant array of panellists:

• Alena Buyx, Professor of Ethics in Medicine and Health Technologies and Director of the Institute of History and Ethics in Medicine at Technical University of Munich. Alena is also active in the political and regulatory aspects of biomedical ethics; she has been a member of the German Ethics Council since 2016 and has been its chair since 2020.
• Sudeshna Das, a Postdoctoral Fellow at Emory University and with a PhD from the Centre of Excellence in Artificial Intelligence at the Indian Institute of Technology Kharagpur. Her doctoral research concentrated on AI-driven Gender Bias Identification in Textbooks.
• Benoit Schillings, X – The Moonshot Factory’s Chief Technology Officer, with over 30 years working in Silicon Valley holding senior technical roles at Yahoo, Nokia, Be.Inc and more. At X, Benoit oversees a portfolio of early-stage project teams that dream up, prototype and de-risk X’s next generation of moonshots.
• Henning Schoenenberger, Vice President Content Innovation at Springer Nature, who is leading their explorations of AI in scholarly publishing. He pioneered the first machine-generated research book published at Springer Nature.
• Bernhard Schölkopf, Director of the Max Planck Institute for Intelligent Systems since 2001. Winner of multiple awards for knowledge advancement, he has helped kickstart many educational initiatives, and in 2023 he founded the ELLIS Institute Tuebingen, where he acts as scientific director.

Cat Allman herself, now VP Open Source Research at Digital Science, was the perfect facilitator of the discussion – she has spent 10+ years with the Google Open Source Programs Office, and has been co-organizer of Science Foo Camp for 12+ years.

The panel session is part of Falling Walls Science Summit 2023, an annual event that gathers together inspirational people from across the globe who are helping to solve some of the world’s biggest problems through their research, new ventures, or work in their local community. I saw around 50 presentations yesterday during the Pitches day, and I’ll be sharing some of the highlights in a follow up post!

But before we go further, an important moment happened during the discussion, and Alena deserves a special mention for ensuring that Sudeshna was given the time to speak, just before the panel answered questions in the Q&A section.

Sudeshna had been unfortunately cut off due to timekeeping, and although it had been well-intentioned — to ensure the Q&A section didn’t get lost — Alena did the right thing in stepping in. Alena’s polite but firm interjection was appreciated by everyone in the room, and it’s this kind of thoughtfulness during the discussion, which was on show throughout, that made it a very enjoyable panel debate to attend.

Onto the session itself, and in their opening remarks, each panellist was encouraged to state whether they felt AI was a friend or foe to science. Of course, that is a binary way to view a complex and ever evolving topic, and the responses reflected this — they radiated a generally positive view of the potential for AI to help science, but with caution on how it’s important to focus on specific examples and situations, to try to be precise both in terms of what the AI is and what it’s intended to do.

Benoit expanded on this need to be precise by giving a couple of specific examples of how he’s been experimenting with AI, both of which fall into the broader category of AI acting a personal assistant. 

In one experiment, Benoit fed a model his reading list and asked for a personalised list of research recommendations and summaries. He was essentially taking to a more personalised level the types of recommendation engine that many websites use to (try to) encourage us to consume more content. What came across was his optimism that such a way of filtering / tailoring the literature — as an aid to a practising researcher — could help deal with the mountain of scientific content. He expects these types of systems to be common within the next few years, and it will be interesting to see who manages to create (or integrate) such a system successfully.

Whilst his first example could be seen as using an AI assistant to narrow down a broad selection of options, his second example is the reverse — when starting out on a new research topic, he often asks Bard for fifteen ideas for avenues to explore on that topic (I forget the exact phrase he used, sorry!). Although not all fifteen suggestions make sense, what comes back is usually useful at stimulating his further thought and ideas on the topic — it’s a great way to get started, and to avoid getting too deep or narrow too soon on a new project.

This issue with AI assistants giving incorrect or nonsensical answers also prompted the conversation to move onto that topic; Bernhard and his team are working on how future models could have some sense of causation, rather than just correlation, to try to help address this gap in current AI systems. 

He gave a particular example where machine learning models had been trained to identify patients with a particular type of illness (I didn’t catch the name); when trained, the model appeared to give excellent detection rates, and appeared to be able to determine with high accuracy whether or not a given patient suffered from this illness. 

However, when it was used in a clinical setting on new patients (presumably as a first test of the system), it failed — what had gone wrong? It turned out the model had spotted that patients with a thoracic (chest) tube had the illness, but those without the tube didn’t — as once a patient is being treated for the illness, they have such a tube fitted. As all the training data was based on known patients, it had used the presence of the tube to determine whether they had the illness. But of course new, unknown patients do not have a tube fitted, and hence the model failed. If models could have some sense of causation, this type of issue might be avoided.

This brings me onto one of the most interesting points raised during the discussion — Alena, who is a trained medical doctor, made the case that, rather than looking to AI assistants to help with potentially complex medical diagnoses, a real, tangible benefit to doctors all around the world would be for AI to help with all note-taking, paperwork, and admin tasks that eat up so much of a doctor’s time and energy.

She made the point that there are other problems with having AI / automated diagnosis machines, namely that you end up with a layering of biases. 

• First there is the algorithmic bias, from the machine learning model and its training data. For example, in medicine there are issues with training data not being gender balanced, or being dominated by lighter skin tones, making the results less reliable when applied to a general population. 
• And secondly, there is the automation bias — that causes humans to trust the answer from a machine, even when it contradicts other observations — which adds a further bias on top. This combination of biases is not good for doctors, and not good for patients! 

As an aside: there was a discussion on how the term “bias” is now often used almost exclusively to refer to algorithmic bias, but there is also inductive bias, which perhaps needs a new name! 

Sudeshna, whose PhD was in identifying gender bias in textbooks, was asked to comment on the issue of biases in AIs. She emphasised that results from AI models reflect biases present in the training data which generally reflect biases in human society. These biases can be cultural and/or driven by data-quality (garbage in -> garbage out), but also stem from the data tending to be from the Global North, where they lack local data from the rest of the world. 

Henning gave an example where his team had seen a similar issue when testing a model on answering questions about SDGs; the answers were extracted from the literature which is predominantly focused on SDGs from a Global North perspective. Henning and I were speaking to Carl Smith in the hallway after the talk, and Carl mentioned how in psychology research this type of issue is often termed the WEIRD bias; another term I learned today!

Having local data — at different scales — is important for AI models to generate answers in context, and without that data, it’s hard to see how local nuance and variety won’t be lost. However, there’s no simple solution to this, and whilst a comment was made that improving data quality (labelling, accuracy, etc) — and training models based on high quality data — was one of the best routes to improving performance, it was acknowledged that it can’t by itself fix the issues of datasets only representing a small fraction of the world’s population.

Overall the tone of the discussion was one of cautious optimism though, and the examples given by the panellists were generally positive instances of people using this new technology to help humans do things better, or quicker, or both.

Earlier in the session, Henning had referred to a book recently published by Springer which was generated using GPT, but which crucially had three human authors/editors who took responsibility (and accountability) for the published work. 

“This book was written by three experts who, with the support of GPT, provide a comprehensive insight into the possible uses of generative AI, such as GPT, in corporate finance.”

Translated opening sentence from the book’s description

Henning made a point of highlighting how current responsible uses of AI all have “humans-in-the-loop”, emphasising that AI is helping people produce things that they might not have the time or resource to. In this specific example, the book was written in approximately two to three months, and published within five — much shorter than the usual twelve months or more that a book usually takes.   

There was time towards the end for a small number of audience questions, and the first was whether we had (or could) learn something from the previous time new technology was unleashed on the public via the internet and had a transformative effect on the world; namely the rise of social media and user generated content and interaction, often dubbed Web 2.0.

It was at this point that Alena stepped in and gave Sudeshna the time to add her thoughts on the previous topic, that of how to address bias in the large language models.

Sudeshna made the very important comment that there is no fixed way in how we should look to address biases, because they aren’t static; the biases and issues we are addressing today are different from the ones of five or ten or twenty years ago. She mentioned her PhD study, on gender bias, and how today she would take a broader approach to gender classification. And so whatever methods we determine for addressing bias should reflect the fact that in ten years we will very likely see different biases, or see biases through a different lens.

Alena then gave a brilliant response to the question of whether anything was different this time vs when Facebook et al ushered in Web 2.0.

She said that back then, we’d had the unbridled optimism to say “go ahead, do brilliant things, society will benefit” to those tech companies. Whereas today, whilst we still want to say “go ahead, do brilliant things” to those companies, the difference is that today we – society / government / the people — are in the room, and have a voice. And that hopefully, because of that, we will do things better.

As the panel wrapped up, Bernhard made the observation that early predictions of the internet didn’t necessarily focus on the social side, and didn’t predict how social media would dominate. He suggests we view our predictions on AI in a similar way; they are likely to be wrong, and we need to keep an open mind.

Finally, Henning closed out the session with a reminder that it is possible to take practical steps, at first an individual then organisational level, which set the approach across a whole industry. His example was that of the SpringerNature policy of not recognizing ChatGPT as an author, which came about because they saw ChatGPT start to be listed as an author on some papers, and very quickly concluded that, because ChatGPT has no accountability, it cannot be an author. Other publishers followed suit, and the policy was effectively adopted across the industry. 

It makes you wonder what other steps could we take as individuals and organisations to bring about the responsible use of AI we all hope to encourage.   

Disclaimer: The write up above is based on my recollection of the panel discussion and some very basic notes I jotted down immediately afterwards! I have focused on those points that stood out to be, and it’s not meant to be an exhaustive summary of what was discussed. I have also  probably grouped things together that were separate points, and may have things slightly out of order. But I’ve strived to capture the essence, spirit and context of what was said, as best I can — please do ping me if you were there and think I’ve missed something!

Double disclaimer: For completeness I should point out that — as you can probably tell — I work at Digital Science, alongside Cat. Digital Science is part of Holtzbrinck, as is Springer Nature, who supported the session. But the above is entirely my own work, faults and all.

The post Implications of AI for science: Friend or foe? An impressive opening to the Falling Walls Circle 2023 appeared first on Digital Science.

Last month saw the latest Times Higher Education (THE) World University Rankings 2024 published to the usual fanfare of marketing (from highly ranked universities) and criticism (from disdainful academics and commentators). Few things get educators riled up and divided like university rankings, the definitive wedge issue of academia. But this year, the rankings have been published in the shadow of a different set of alternative voices from the BRICS countries; one that could change the face of university rankings globally.

What are university rankings for? Originally, they were conceived as a way to provide a systematic list of institutions dependent on certain criteria that would be of value to potential students and their parents making one of the biggest decisions of their lives. As the father of a 19 year old, I have just gone through this painful process, with conversations something like this:

CHILD: I want to go to X University

ME: But what about Y University – the grades are lower for admission, it’s a great place to live, and the course offers a wide variety of options in your third year?

CHILD: I want to go to X University. It’s better than Y. It has prestige.

ME: How do you know?

CHILD: It says in those rankings.

ME: But they are based on irrelevant criteria, cover research more than undergraduate studies, and are completely disowned by the academic community!

CHILD: (shrugs) I still want to go to X University

Needless to say, there was no discussion about alternative ways to weigh up universities’ relative merits, but if they had it might have been useful to reflect on events in July 2023 where a meeting of education ministers from BRICS countries – Brazil, Russia, India, China and South Africa – declared war on existing university rankings, and committed themselves to developing a new one. 

Their reasoning was based on their objection to the cost of participating in such rankings and the effect they had on research culture in universities. While a timeframe and further details have yet to be announced, it has long been felt by many universities in Global South countries that playing the rankings game was not worthwhile, as it sacrificed research norms such as collaboration and sharing. Furthermore, many academics can get drawn into trying to publish research in certain journals in order to ‘score’ more highly for their institution – journals that may not typically publish methodologies they or their research cultures would normally utilize. We have, then, systems in place where rankings for both universities and the journals their academics publish in dominate the higher education agenda. 

Criticism

University rankings have not been around as long as some may think. The US News & World Report first published its US college rankings in the early 1980s, followed in the early 2000s by Times Higher Education (THE). Several other rankings have also sprung up in the meantime at international and national levels, meaning that prospective students have never had more choice in terms of data and rankings to support their decision.

Providing more data to improve decision-making is usually a good thing, but the flip side is that such is the power of the rankings that universities are tempted to chase ranking points rather than focus on their core mission. In his book Breaking Ranks , former university administrator Colin Diver charts the rise of rankings and how they can persuade applicants to zero in on pedigree and prestige, while inducing HEIs to go for short-term gains. Not only does this rig the system, Diver also argues it reduces diversity and intellectual rigor in US colleges.

Looking at this problem more globally, a panel discussion entitled ‘University Rankings: Accept, Amend or Avoid?’ was convened  at the STI Conference in Leiden in The Netherlands (https://www.sti2023.org/) in October 2023. In establishing the panel discussion, the conference detailed events that had led up to the inclusion of this topic at the highly regarded conference on science, technology and innovation indicators. Just in the prior 12 months these involved the creation of an international coalition of stakeholders including a commitment to avoid use of university rankings in the assessment of researchers; a new initiative for HEIs called ‘More Than Our Rank’; the Harnessing the Metric Tide review of indicators, infrastructures and priorities for UK responsible research assessment; Yale University withdrawing from the US News & World Report Law Rankings, followed by several medical schools doing something similar.

Speaking on the STI Conference panel, UK-based research assessment expert Lizzie Gadd commented on the move by BRICS education ministers. Speaking on, Dr Gadd saying: “The BRICS states are expressing their dissatisfaction with the well known university rankings (THE,QS etc) due to these favouring the Global North. However, their chosen response of developing an alternative ranking based on qualitative inputs will only be effective if it displaces the existing dominant rankings in those regions. This is unlikely given previous efforts in this direction have not had this effect”.

Case study

So, thinking of the BRICS countries and many other commentators in this: when combined together, the domination of English language in research journals, Western-dominated university rankings, Western research paradigms and Western-located publishers works against authors from Global South countries, creating a form of hegemony that has been difficult to break down for decades. But how do these phenomena manifest themselves?

Back in 2010, I published an article with one of the Editors I worked with in academic publishing on the impact of the research assessment programs in the UK (REF), Australia (ERA) and New Zealand (PBRF). We interviewed academics from all three countries and asked them if they felt they were influenced in their research choices by the systems they worked under. Sure enough we found that they did, with impacts felt on lower-ranked journals who did not receive submissions in favour of higher-ranked titles.

In other words, attempts to rank or score universities in terms of their research leads to some of those universities or individual researchers impacted by those attempts to fundamentally change their approach. More insidious is how research itself is determined by a relatively narrow band of publications both for academics to publish in, and identified as ‘top’ research. For business schools, inclusion in the Financial Times Top 100 is marketing nirvana, with the potential to increase the number of MBA students (and therefore revenue) as well as the prestige of their institution. This ranking is derived in small part by the FT50, a well-established list of business and management journals that has hardly changed for decades. 

The result? Not only is it limiting for academics who are tasked with publishing in those journals as part of their commitments to their universities, it also limits what is regarded as the best examples of research in a certain area. In a study I co-authored on impact assessment, we used an AI tool to identify those business and management journals which included the most research relating to the UN Sustainable Development Goals (SDGs). Of the top 50 with the most related content, just one was also in the FT50. 

Identifying progress

So can these fractures caused and maintained by Global North-dominated university rankings be healed? There are green shoots that, if able to flourish, could help turn things around. The San Francisco Declaration on Research Assessment (DORA) has gained significant traction among stakeholders in the last decade, and the work of Dr Gadd and others at the STI Conference have inspired many universities to turn their back on rankings in favor of more balanced assessment methods. For example, at the end of September the University of Utrecht declared it had withdrawn its involvement in the THE rankings, citing that such rankings placed too much stress on university competition, not collaboration; the difficulty in scoring the quality of an institution as complex as a university, and the use of some questionable methodology. 

Progress is also being made through representation of more impactful data points in research platforms. For example, with data on nearly 140m publications, Digital Science’s Dimensions enables access to publications from a wide range of research outputs outside the Global North context, as well as content not in the English language. With translation becoming easier thanks to advances in AI, access to non-English content opens up a huge depth of opportunities for researchers the world over.

In addition, using Dimensions database researchers can identify how studies relate to the SDGs using a specific filter, or order articles based on their influence outside academia with Altmetric. Other platforms are also adding wider functionality that means citations – and specifically the Impact Factor from Web of Science – are no longer the only means of filtering research outputs.

Practical uses for this functionality include a recent report from THE, Prince Sultan University and Digital Science where for the first time Global South-oriented data was used in analyzing impact, as well as research integrity data now included in the DImensions database. The analysis in the report showed there was a significant gap between higher- and lower-income nations in regards to SDG-focused research. However, it was evident that there was growing SDG research in lower-income countries over the past 15 years or so, with some increases in collaboration within those regions.

University rankings providers are then listening to the need for wider representation in their data, with THE now also providing its Impact Ranking which has three Global South universities in its latest Top 20 and only one from the US. Other rankings providers are also widening the context of what they are evaluating, so while the methodological problems may persist of what can or cannot be ranked effectively, at least the focus of this activity is not squarely on prestige and performance.

Paradigm shift?

These developments help move the dial away from the dominance rankings have had on many university agendas, but may not be enough to engender the paradigm shift away from defining a ‘good’ university as one that simply satisfies a narrow set of criteria. What may be required is a concerted effort from funders, researchers, policymakers and universities themselves to follow a different path that instead celebrates the diversity of global research and different higher education approaches. 

We saw in an earlier piece in the Fragmentation campaign by Dr Briony Fane how an increase in focus in collaborative pharmaceutical research on the Global South was growing and that was where the biggest need was for medicines and other interventions. For all sorts of reasons, a fragmented research world has bad outcomes for huge swathes of the global population. Similarly, the fragmentation created by university rankings has impacted much of the developing world, which is why the BRICS countries have been moved to try and do something about it. Another ranking may not be the way to go about it, as it will do little to reduce fragmentation and its effects. Universities across the world need to collaborate more in research and meeting global challenges to bridge the divides between them, not compete for more meaningless points on a ranking.

The post Rank outsiders appeared first on Digital Science.

10th October is World Mental Health Day. This year’s theme is “Our Minds, Our Rights”, with a focus on how good mental health should be a basic human right for everyone, no matter their situation or circumstance.

At Digital Science, we offer a range of initiatives to support healthy bodies and minds for our workforce, so that we can best serve our amazing research community and enable them to do the most groundbreaking, societally-impactful work.

John and I sat down with Danielle Feger, Digital Science’s Global Health and Wellbeing Manager, to talk about the link between mental health and physical health, the challenges we must overcome to destigmatise mental health, the need for awareness days, and the initiatives that Digital Science has implemented to help both our internal and external communities.

Here’s our chat in full – if the embedded video doesn’t show below, you can watch it directly on YouTube:

For the resources I mention at the end of the chat, you can find Dr Zoë Ayres’s book, Managing your Mental Health during your PhD: A Survival Guide, here, and Dr Petra Boynton’s book, Being Well in Academia: Ways to Feel Stronger, Safer and More Connected (Insider Guides to Success in Academia), here.

You can also learn more about World Mental Health Day, particularly this year’s theme, on the World Health Organization website.

The post World Mental Health Day 2023 appeared first on Digital Science.

London, UK – Tuesday 3 October 2023

According to new research conducted by Digital Science there is a worrying divide between Global North and Global South countries on both the funding and collaboration in pharmaceutical research. However, the most recent data shows that this divide may be closing, benefiting Global South countries hit hardest by lack of access to essential medicines and vaccines.

The report – detailed in a new blog launching the ‘Fragmentation: A Divided Research World campaign as part of Digital Science’s TL;DR initiative – is an evaluation of scientific publications including contributions from the top ten pharmaceutical companies in the Global North and Global South, which have been indexed in Digital Science’s Dimensions database in the past five years (2018 to 2022). The study maps aspects of the landscape in this area exploring differences in: 

• pharmaceutical research practices from different perspectives including funding and collaboration
• pharmaceutical research and its association with the Sustainable Development Goals (SDGs)
• the impact of the cost of medicines developed by pharma 
• their accessibility in distinct geographic regions. 

The results show significant gaps between the two global areas, but also some ways where these gaps are now closing.

North and South

The background to the research is the stark truth that an estimated two billion people worldwide still lack access to essential medicines and vaccines. Enabling access, especially for those in most need in the Global South, is a key component in the UN’s SDGs Agenda.

Dr Briony Fane, Director of Research Analytics at Digital Science and lead author of the study, says: “While countries in the Global South have obtained benefits from pharmaceuticals originally developed for high income country markets, little research has been conducted on diseases that primarily affect these countries, such as malaria or tuberculosis.

She adds: “And it is not just in healthcare but also in education, government, not for profits, etc that science is funded for the development of new pharmaceutical products aimed at transforming lives.

But there is good news as the data and recent initiatives show the gap between North and South is closing: “The geography of the pharmaceutical industry’s participation in this area of research indicates perhaps the start of a growing commitment to its involvement in addressing the access to medicine in all areas in the world and evidence of collaboration across the Global North and Global South, however small, shows a level of responsibility being taken by the industry,” says Dr Fane.

Progress for all

In 2023, Digital Science is looking to extend its mission to support better, open, collaborative and inclusive research through a number of different initiatives. The #Fragmentation campaign will ask: is research fragmented, and if so, how? Fragmentation in research can undermine societal progress – progress which Digital Science is committed to driving forward in its support of the research ecosystem. 

The exploration of fragmented research begins with the focus on global divides such as the ‘tale of two pharmas’ detailed above, then moving onto the domain of ‘siloed knowledge’, where we will concentrate on areas of research where a lack of integration can result in research findings remaining isolated, limiting their broader applicability across the research ecosystem. Following these two themes will be investigations on policy-making, research funding and complexity. 

Dr Juergen Wastl, Director of Academic Relations & Consultancy and Digital Science, says: “Our campaign aims to highlight the structural features of fragmentation, by consolidating concepts and by demonstrating a number of analytical approaches through the use of Digital Science tools such as Dimensions.”

In June 2023 Digital Science launched its #MindtheTrustGap campaign which highlighted the different ways trust in research was being threatened and how this erosion could be mitigated across issues such as a lack of competencies in generative AI tools, the impact of AI on predatory publishing problem and the importance of data availability statements. The campaign has helped increase the profiles of research and publication integrity, aided by new product releases in this area such as Dimensions Research Integrity. 

Find out more about the Digital Science Fragmentation campaign

About Digital Science

Digital Science is an AI-focused technology company providing innovative solutions to complex challenges faced by researchers, universities, funders, industry and publishers. We work in partnership to advance global research for the benefit of society. Through our brands – Altmetric, Dimensions, Figshare, ReadCube, Symplectic, IFI CLAIMS Patent Services, Overleaf, Writefull, OntoChem, Scismic and metaphacts – we believe when we solve problems together, we drive progress for all. Visit www.digital-science.com and follow @digitalsci on Twitter/X or on LinkedIn.

Media contact

David Ellis, Press, PR & Social Manager, Digital Science: Mobile +61 447 783 023, d.ellis@digital-science.com

The post New research shows global divide in pharmaceutical research is significant – but closing appeared first on Digital Science.

Summary

In this blog we present findings from a bibliometric evaluation of scientific publications that include a contribution from the top ten pharmaceutical companies in the Global North and Global South, which have been indexed in Digital Science’s Dimensions database in the past five years (2018 to 2022). The study maps aspects of the landscape in this area exploring differences in pharmaceutical research practices from different perspectives including funding and collaboration, pharmaceutical research and its association with the SDGs, the impact of the cost of medicines developed by pharma and their accessibility in distinct geographic regions. The results show significant gaps between the two global areas, but also some ways where these gaps are now closing.

Contents

• Introduction
  • The new geography of the pharmaceutical industry
  • The pharmaceutical industry’s commitment to the Sustainable Development Goals (SDGs)
• Methodology
• Analysis
  • Global North and Global South
  • Pharmaceutical funding and collaboration with ‘access to medicine’ research publications
  • Pharma funding and collaboration associated with the UN Sustainable Development Goals
  • Funding Sources-Pharmaceutical Partnerships
• Conclusion
• References

Introduction

Access to essential medicines is a serious global concern, regardless of the income level of a country. Medicines are not affordable for those who need them in many low- and middle-income countries (the Global South), and many new medicines are too expensive even for the health systems of middle- and high-income countries (the Global North)^[2].

Staggeringly, an estimated two billion people worldwide still lack access to essential medicines and vaccines that could prevent and treat diseases, relieve suffering, improve quality of life and reduce deaths,^[3] and the majority of these people are living in global south countries. This is a clear example of fragmentation in our society – a disconnect between the ‘haves’ and ‘have nots’, where science and medicine could save lives but are unable to overcome the barriers in their way.

Pharmaceutical companies are recognised as being uniquely positioned to remedy this and improve people’s lives by producing innovative and affordable medicines^[4]. However, their products have generally been developed to target more lucrative markets and, as a result, are often poorly matched with the needs of global south countries.

Achieving equitable access to medicines is a key component in the UN’s Sustainable Development Agenda. In particular, one of the targets of the UN’s Sustainable Development Goal 3 (SDG3) – ‘Good Health and wellbeing’ – is to achieve Universal Health Coverage (UHC) and is a critical driver to realising health equity. Equitable access and resilient health systems are the basis for UHC, by enabling availability, affordability, and acceptability to ensure that people can get the right medicines of the right quality at the right price and at the right place^[5].

Since 2006 the UN’s Industrial Development Organization (UNIDO) has provided support and assistance to advance local pharmaceutical production in developing countries where its support contributes effectively to strengthening the health security of the global south countries and as a follow on to attaining SDG3, addressing the need for “access to safe, effective, quality, and affordable essential medicines and vaccines for all”^[6]. However, there remain barriers for many people in the world who have difficulty accessing the healthcare they need for multiple reasons, including:

Even for diseases that affect both the Global North and the Global South alike, research often focuses on products that are best suited for use in the Global North. For example, a lot of pharmaceutical research has been conducted on complex AIDS drugs that are more useful in global north countries, but too expensive and difficult to deliver to much of the population in global south countries.^[9] The lower income countries take the bulk of the global disease burden, yet essential healthcare products are often unaffordable or unavailable to them.

Achieving greater access for the global south countries who have less access to the most essential of medicines requires pharmaceutical companies to give them a place in their business operations. The 2022 ‘Access to Medicine Index’^[10] evaluates and compares 20 of the world’s leading research-based pharmaceutical companies according to their efforts to improve access to medicine. Data analysed for the 2022 Index found that more companies had stepped up their access efforts – including some companies that were previously less likely to take action.^[11] The data relates to 83 diseases, conditions and pathogens that disproportionately impact people living in the 108 global south countries in scope of the Index, where better access to medicine is most urgently needed. Most recently, Johnston & Johnston has agreed to allow generic versions of the drug bedaquiline in dozens (96) of lower income countries to be made available. It is implementing this by providing the Global Drug Facility (GDF)^[12] with licences enabling the organisation to procure and supply generic forms of the drug countries the organisation supplies.^[13]

The ability to contribute to health equity and, more specifically, facilitate access-to-medicine, has increasingly become a priority for the pharmaceutical industry. However, while steps are being taken to improve access to their products in the global south, many plans and strategies still overlook the poorest countries.

The new geography of the pharmaceutical industry

The geographic concentration of the pharmaceutical industry currently sits in those countries with the fastest growing economies. This concentration is gradually starting to shift and more and more we are seeing that pharmaceutical production in developing countries is increasing. For instance, India is now a more prominent and developing player in the global pharmaceutical industry and their domestic pharmaceutical market’s growth outpaced that of the overall economy by 2-3% a year^[14]. According to China Briefing, the Chinese pharmaceutical market has grown in the past few years, with a 200% increase in market capitalisation between 2016 and 2020.^[15] Thus, although the US pharmaceutical industry still dominates the global market, accounting for roughly 50% of global pharmaceutical sales revenue, we are seeing shifting patterns in the geography of the pharmaceutical industry.

The research-based pharmaceutical industry is also entering a new era in medicines development^[16] and there is fast growth in the market and research environment in emerging economies such as Brazil, China and India, leading to a gradual migration of economic and research activities from Europe to these markets^[17]. That said, of the 40 vaccine manufacturers in 14 nations that are part of The Developing Countries Vaccine Manufacturers Network, currently just one is African: the Biovac Institute based in Cape Town, South Africa, which delivers over 25 million doses of vaccines each year for illnesses such as measles, polio and tuberculosis.^[18]

Consequently there is still a heavy reliance on external sources and the export of medicines to African nations. However, within the next two decades, the African Union member states are aiming for 60% of Africa’s routinely used vaccines to be manufactured on the continent.^[19]  With roughly half the population of Africa lacking regular access to the most essential medicines, according to the WHO,^[20] attempts to reduce this has seen a growing number of healthcare practitioners beginning to build the pharmaceutical manufacturing capacity on the African continent.

Crossing the continents, Bangladesh’s pharmaceutical industry is unique in the Global South. Driven by active government policies, output has grown a thousand times since 1982, to US$2 billion (around 1% of gross domestic product), making it the biggest white collar employer in the country. The industry supplies pharmaceuticals to almost the entire domestic market and more than 100 other countries including the United States.^[21]

The pharmaceutical industry’s commitment to the Sustainable Development Goals (SDGs)

The value of translating scientific evidence into action in support of the SDGs and their attainment is of paramount importance. The pharmaceutical industry’s participation in accelerating achievement of the SDGs requires that its roadmap for research and development includes demonstrating its ability to tackle diseases in both global south and global north countries. 

The need to have access to safe and effective essential medicines is so important that it has been designated a basic human right by the World Health Organization.^[22] This importance has been given further weight by its inclusion in the UN’s Sustainable Development Agenda.

Access to medicine is essential for ending epidemics and reducing the mortality in non-communicable diseases and is one of the targets of Sustainable Development Goal 3 – Good Health and well-being (SDG3.4). Of course, living healthy lives is what most people would expect, or at the very least hope for, in the 21st century. However, for millions, this remains an aspiration. The mission of SDG3 is to change this and ensure healthy lives and promote well-being for people of all ages, and the pharmaceutical industry is making inroads in its contribution to SDG3 and beyond.

For example, GlaxoSmithKline (GSK) expresses a long-term commitment to improving access to health care across the world. Since 2010, it has capped the prices of patented medicines and vaccines in the “least developed countries” at 25% of those in the EU5 (France, Germany, Italy, Spain, and the UK) as long as manufacturing costs are covered^[23]. 

We also examine how the UN SDGs influence the pharmaceutical industry to do more good than changing and saving lives. So although the pharmaceutical industry’s primary impact is in SDG3, other Goals such as SDG12 Responsible Consumption and Production and SDG6 Clean Water and Sanitation are also influential.

For example, a number of leading pharmaceutical companies now demonstrate ‘responsible production’ by, for example, reducing animal testing and hazardous chemical use (Bayer), recycling water in the manufacturing process (GSK), or education on vaccination for the community (Pfizer), along with wastewater management, water recycling, and the use of green chemistry aimed to address environmental issues. The above examples focus on targets set out in SDG12 and SDG6.

Methodology

We extracted the top ten pharmaceutical companies by income using GRID IDs (parent GRID), whilst extracting the (child GRID) ID for each company (the top pharmaceutical companies operate worldwide and have subsidiaries across the globe) and this allowed us to split them into those operating in global north countries and those operating in global south countries depending on operation bases, ie, where top ten pharmaceutical companies based in the Global North have operations carrying out pharmaceutical research and development in the Global South. Dimensions allows us to do this using Google Big Query (GBQ) bringing together World Bank data for the Global North and Global South distinction, and the research output from Dimensions, to perform the analyses.  

Next, a simple boolean search string was created: “access medicine”~3 and, along with our search string of top ten pharmaceutical companies, Dimensions retrieved the relevant research outputs for pharmaceutical companies in global north and in global south countries.

Using the set of search results we filtered the research output by Global South (low and lower-middle income countries) and Global North (high and upper-middle income countries).

Analysis

Global North and Global South

In this section we analysed the relevant research that involves the top ten pharmaceutical companies and their contribution to research on ‘access to medicine’ in the Global North and in the Global South.

To get an initial sense of the data, we first analysed ‘access to medicine’ research publications featuring top ten pharmaceutical companies, using Dimensions. This enabled us to ascertain the geographical distribution of the pharmaceutical companies’ participation in this domain (see Figure 1) in global north and global south countries.

Figure 1 details the total volume of research publications associated with ‘access to medicine’ research by country income level..  Of the total volume (3,165 publications), 109 (3.4%) include a contribution from the pharmaceutical industry. 1,473 publications from the dataset did not have the required data to determine country-income group (46%).

Pharmaceutical funding and collaboration with ‘access to medicine’ research publications

Figure 2 outlines the volume of papers across global north and global south countries over time.  We note that a mixed pattern emerges. We also note that numbers are small and might expect this for two reasons.  Firstly, access to medicine research is a particularly niche area of research, and secondly, historically, it has not been common for the pharmaceutical industry to collaborate on academic research. But this is changing with links between academia and the pharmaceutical industry increasing both as funding partners or as collaborators, or both.^[24] The data here would confirm this.  What is apparent is that pharmaceutical companies predominantly collaborate with researchers and fund more research in the high income countries of the Global North. Although there is evidence of pharmaceutical companies funding  and collaborating with research in the global south, it is to a much lesser extent. Figure 3 reveals that collaboration in conjunction with funding by pharma for research associated with ‘access to medicine’ is evident in 2022 for the first time. It would be interesting to see whether this is the starting point for the pharmaceutical industry’s engagement and collaboration with academic researchers in the Global South going forward.

The top ten pharmaceutical industry’s contribution to ‘access to medicine’ relevant research in Global North and Global South countries is displayed in Figure 3 above detailing the extent to which collaboration and funding in this area is focused in the two regions over an eight year period.  Immediately apparent is the stronger commitment to the higher income countries, where, in particular, the pharmaceutical industry’s collaborations with academic research is most pronounced. Funding and/or collaborating with research in the Global South shows data only across three years.

Pharma funding and collaboration associated with the UN Sustainable Development Goals

Figures 4a and 4b above assess the volume of research outputs that are associated with the UN’s SDGs, either funded or in collaboration with, or both, the pharmaceutical industry. Unsurprisingly, the research focus is predominantly with SDG3 – Good health and well-being, however the data would suggest that there are potentially starting to be signs of their focus extending to SDG12 Responsible Production and Consumption (eg, supply chains) and SDG6 Clean Water and Sanitation (eg, management of wastewater). With reference to SDG6, advances in wastewater treatment processes are being made in the industry to prevent the discharge of harmful substances into water resources and the environment. In fact  AstraZeneca has made an 18.7% reduction in water use since 2015 and 100% reduction of active pharmaceutical ingredients discharges from AstraZeneca sites. 92% of discharges from direct suppliers were in compliance with SDG6 target 6.3.^[25] With respect to SDG12 again, AstraZeneca averted 2,129 tonnes of waste in 2022 alone by selling it as a by-product.

The geographical distribution of the top ten pharmaceutical industry’s participation in research associated with ‘access to medicine’ research was examined using a collaborative network visualisation tool (see Figure 5 above), VOSviewer. The tool allows us to see, in this instance, countries participating in research focused on ‘access to medicine’, the collaborative networks between those countries, and where pharmaceutical companies concentrate their collaborations. Understanding geographic patterns can also help to identify potential gaps and highlight areas where more collaborative effort might be valuable. It can also indicate regions where the pharmaceutical industry is more proactive in supporting research on access to medicines.

Funding Sources-Pharmaceutical Partnerships

We present data in Figure 6 to provide an understanding of the financial and/or collaborative support from the pharmaceutical industry behind research focused on ‘access to medicine’ in different sectors. Analysis of the dataset using Dimensions, allowed us to determine the proportion of research funded by pharmaceutical companies, alongside other sources, including government agencies, foundations, and nonprofit organisations. The analysis provides an indication (despite small numbers^[26]) of the extent of the pharmaceutical industry’s financial commitment to ‘access to medicine’ research in the Global North and Global South, and helps to evaluate the diversity of pharmaceutical funding of research in this area.

Conclusion

Exploring a niche area of research as we have done here with our focus on ‘access to medicine’, means that the data retrieved will be small in number, and made smaller by the introduction of a filter which is possible using Dimensions which in this case is the top ten pharmaceutical companies. Lower numbers in an analysis naturally brings with it a number of caveats, and one in particular, the robustness of the data and subsequent outcomes.

Despite this, it is still worthwhile and beneficial to explore the research from this perspective and has provided some useful insights. Insights such as the industries that the pharmaceutical industry supports in this niche area and where we see that it is not just in healthcare but also in education, government, not for profits, etc that science is funded for the development of new pharmaceutical products aimed at transforming lives.

Further, the geography of the pharmaceutical industry’s participation in this area of research indicates perhaps the start of a growing commitment to its involvement in addressing the access to medicine in all areas in the world and evidence of collaboration across the Global North and Global South, however small, shows a level of responsibility being taken by the industry.

Finally, on a general note, a survey by the Association of the British Pharmaceutical Industry in 2022 found that ‘industry-academic links were at an all time high and identified several trends pointing to the continued support of the pharmaceutical industry for students training and research all across the UK and worldwide’.^[27]

References

^[1] https://www.gsk.com/en-gb/responsibility/global-health-and-health-security/improving-access-to-healthcare/

^[2] Wirtz VJ, Hogerzeil HV, Gray AL, Bigdeli M, de Joncheere CP, Ewen MA et al. Essential medicines for universal health coverage. Lancet. 2017;389(10067):403–76

^[3] https://cdn.who.int/media/docs/default-source/essential-medicines/fair-price/chapter-medicines.pdf?sfvrsn=adcffc8f_4&download=true

^[4] https://unglobalcompact.org/library/1011

^[5] https://www.gsk.com/en-gb/responsibility/global-health-and-health-security/improving-access-to-healthcare/

^[6] https://www.unido.org/our-focus-advancing-economic-competitiveness-investing-technology-and-innovation-competitiveness-business-environment-and-upgrading/pharmaceutical-production-developing-countries

^[7] https://www.astellas.com/en/sustainability/access-to-medicines

^[8] Pecoul, Bernard et al. 1999. “Access to Essential Drugs in Poor Countries: A Lost Battle?” Journal of the American Medical Association. January 27, 281:4, pp. 361–67

^[9] https://www2.hawaii.edu/~noy/362texts/pharma.pdf

^[10] https://accesstomedicinefoundation.org/medialibrary/2022_access-to-medicine-index-1669982470.pdf

^[11] https://accesstomedicinefoundation.org/medialibrary/2022_access-to-medicine-index-1669982470.pdf

^[12] https://www.stoptb.org/facilitate-access-to-tb-drugs-diagnostics/global-drug-facility-gdf

^[13] https://www.science.org/content/article/major-drug-company-bends-battle-over-access-key-tb-treatment?utm_source=Nature+Briefing%3A+Translational+Research&utm_campaign=89b7cf8e10-briefing-tr-20230726&utm_medium=email&utm_term=0_872afe2a9a-89b7cf8e10-47896968

^[14] https://www.wilsoncenter.org/blog-post/indias-economic-ambitions-pharmaceutical-industry

^[15] https://www.china-briefing.com/news/china-booming-biopharmaceuticals-market-innovation-investment-opportunities/

^[16] https://www.efpia.eu/media/637143/the-pharmaceutical-industry-in-figures-2022.pdf

^[17] https://aijourn.com/press_release/pharmaceutical-glass-packaging-global-market-report-2023-growth-of-pharmaceutical-industry-in-emerging-economies-drives-sector-researchandmarkets-com/

^[18] https://unctad.org/news/covid-19-heightens-need-pharmaceutical-production-poor-countries

^[19] Saied, AbdulRahman A.a,b,*. Africa is going to develop their own health capabilities for future challenges – Correspondence. International Journal of Surgery 99():p 106585, March 2022. | DOI: 10.1016/j.ijsu.2022.106585

^[20] https://www.who.int/news/item/13-12-2017-world-bank-and-who-half-the-world-lacks-access-to-essential-health-services-100-million-still-pushed-into-extreme-poverty-because-of-health-expenses

^[21] https://www.un.org/ldcportal/content/what-ldc-graduation-will-mean-bangladesh%E2%80%99s-drugs-industry

^[22] https://apps.who.int/iris/bitstream/handle/10665/255355/9789241512442-eng.pdf

^[23] https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6316355/

^[24] https://www.abpi.org.uk/media/news/2022/september/new-survey-shows-collaboration-between-pharmaceutical-industry-and-uk-academia-is-growing/#:~:text=This%20year’s%20survey%20shows%20that,3%2Dfold%20increase%20since%202015.

^[25] https://www.astrazeneca.com/content/dam/az/Sustainability/2023/pdf/Sustainability_Report_2022.pdf

^[26] The small numbers in part might be the result of the pharmaceutical industry being less eager to publish their funded research in this area, though the topic of the search for “access to medicine’ is less ‘confidential’ in comparison to research published on a potentially new pharmaceutical ingredients etc.

^[27] https://www.abpi.org.uk/facts-figures-and-industry-data/industry-and-academia-links-survey-2022/

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