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Wildlife use is widespread across the world where animals and their derivates are consumed and/or traded (Ingram et al., 2021). When the use is unsustainable, it is a leading cause of biodiversity loss worldwide, with profound consequences for ecosystem services and functions (IPBES, 2022). In December 2022, Parties to the Convention on Biological Diversity adopted the Kunming–Montreal Global Biodiversity Framework, agreeing to achieve the sustainable use and management of biodiversity as one of four central goals by 2050. Furthermore, the COVID-19 pandemic has focussed global attention on the wildlife trade and potential risk of zoonotic emerging infectious disease spread. From February 2023, the World Health Organization (WHO) has been negotiating drafts of a global Pandemic Agreement, calling for collective action on pandemic prevention, preparedness, and response, including the need to "take measures to reduce risks of zoonotic spill-over" (Article 4; World Health Organisation, 2024). Given how wholly interconnected these issues are, leveraging approaches that tackle integrated issues around the health of people, animals, and ecosystems, such as One Health and Planetary Health approaches (de Castañeda et al., 2023), will be paramount to addressing the global challenges of biodiversity loss and zoonotic disease emergence. Managing the use of wildlife can be challenging for many reasons, including the number of actors involved along varied supply chains across rural and urban areas, the complexities around the legality of trade in different circumstances, and the capacities of governments to act (Ingram et al., 2021). The COVID-19 pandemic prompted a worldwide initiative to end the wildlife trade (Coalition to End the Trade, 2020), resulting in certain countries banning physical wildlife markets. Yet, it is becoming increasingly evident that digital services platforms, particularly social media platforms, are playing a pivotal role in the legal and illegal trade of wildlife (Morcatty et al., 2021). Yet, little has been done to stem the illegal online trade of wildlife, which undermines efforts to manage the trade effectively, sustainably, and safely (Morcatty et al., 2021). Here, we highlight two major ways in which technology companies running global social media, e-commerce (marketplaces), and content-sharing platforms (hereafter just "tech companies") can assist in achieving the goals of the Kunming–Montreal Global Biodiversity Framework and the WHO Pandemic Agreement. For the latter, examples could include public lists of tech companies, which are not part of groups working to reduce online illegal wildlife trade (Sebagh, 2021), and transparent monitoring of such groups to ensure that activities are taking place and reporting tools are effective. Furthermore, monitored trade should not only include high-value wildlife products such as ivory, or live animals in the trade, but should also include advertisements for traders and establishments that sell the meat of wild animals (i.e., wild meat), where illegal. This has received substantially less attention than the trade in high-value wildlife products. Crucially, member states differ in their resources and capabilities to tackle illegal wildlife trade online and deliver effective pandemic prevention, preparedness, and response. The latter is acknowledged in the most recent WHO Pandemic Agreement draft (World Health Organisation, 2024). Although the use of certain platforms differs by country (Ghermandi et al., 2023), global tech companies must play a role in addressing some of these inequities by targeting online interventions to countries with high illegal wildlife trade prevalence. Second, online social media and video sharing platforms have been vehicles for (mis)information dissemination across the world, with social media being described as creating the "climate change of culture" (Harris, 2019). The spread of misinformation regarding emerging infectious disease spread and effective treatment, as was evident during the COVID-19 pandemic (Cinelli et al., 2020), is a significant threat to global public health because it can hinder evidence-based actions designed to prevent or respond to outbreaks. Additionally, on some social media and video sharing platforms, the content recommender algorithms amplify minority extreme content (Whittaker et al., 2021), thus contributing to the polarization of views (Van Bavel et al., 2021), which can drive viewing figures on platforms. This could include extreme views about wildlife and wildlife uses, disease origin, risk, prevention, and treatment that have no evidence base. For example, misinformation about species purported to transmit zoonotic diseases may lead to intentional killing of those species. As already highlighted in Article 18 of the WHO Pandemic Agreement, the Parties will commit to "countering and addressing misinformation or disinformation" (World Health Organisation, 2024), which could be more easily achieved through action and cooperation from social media and content-sharing tech companies, such as through minor changes in algorithms to nudge users to consider the accuracy of the information before sharing (Pennycook et al., 2020). Some platforms, for example, use link recommendation algorithms to recommend new connections to users. These algorithms may increase the likelihood of polarization when users preferentially make connections in groups where they share mutual connections; however, evidence suggests this could be curbed by platforms if they adapt link recommendation algorithms to sporadically recommend dissimilar individuals with few common connections (Santos et al., 2021). Similarly, users may engage in opinion amplification, which refers to "the range of behaviours by users that may distort the original opinion with a more positive or negative sentiment", which can proliferate through networks when the topic is trending (Lim writing—review and editing. Thais Q. Morcatty: Writing—review and editing. Hani R. El Bizri: Writing—review and editing. Mahesh Poudyal: Writing—review and editing. Edward Mundy: Writing—review and editing. Daniel J. Ingram acknowledges support from UK Research and Innovation (Future Leaders Fellowship, Grant ref: MR/W006316/1). Thais Q. Morcatty is funded by an Oxford Brookes University Research Excellence Award. We would like to thank Dr. David Roberts and Dr. Tally Yoh for helpful comments on this article. The authors declare no conflicts of interests. Data sharing is not applicable to this article as no new data were created or analyzed in this study.
Ingram et al. (Mon,) studied this question.