PDF(Pubmed)
Abstract：
BACKGROUND: The online pharmacy market is growing, with legitimate online pharmacies offering advantages such as convenience and accessibility. However, this increased demand has attracted malicious actors into this space, leading to the proliferation of illegal vendors that use deceptive techniques to rank higher in search results and pose serious public health risks by dispensing substandard or falsified medicines. Search engine providers have started integrating generative artificial intelligence (AI) into search engine interfaces, which could revolutionize search by delivering more personalized results through a user-friendly experience. However, improper integration of these new technologies carries potential risks and could further exacerbate the risks posed by illicit online pharmacies by inadvertently directing users to illegal vendors.
OBJECTIVE: The role of generative AI integration in reshaping search engine results, particularly related to online pharmacies, has not yet been studied. Our objective was to identify, determine the prevalence of, and characterize illegal online pharmacy recommendations within the AI-generated search results and recommendations.
METHODS: We conducted a comparative assessment of AI-generated recommendations from Google\'s Search Generative Experience (SGE) and Microsoft Bing\'s Chat, focusing on popular and well-known medicines representing multiple therapeutic categories including controlled substances. Websites were individually examined to determine legitimacy, and known illegal vendors were identified by cross-referencing with the National Association of Boards of Pharmacy and LegitScript databases.
RESULTS: Of the 262 websites recommended in the AI-generated search results, 47.33% (124/262) belonged to active online pharmacies, with 31.29% (82/262) leading to legitimate ones. However, 19.04% (24/126) of Bing Chat\'s and 13.23% (18/136) of Google SGE\'s recommendations directed users to illegal vendors, including for controlled substances. The proportion of illegal pharmacies varied by drug and search engine. A significant difference was observed in the distribution of illegal websites between search engines. The prevalence of links leading to illegal online pharmacies selling prescription medications was significantly higher (P=.001) in Bing Chat (21/86, 24%) compared to Google SGE (6/92, 6%). Regarding the suggestions for controlled substances, suggestions generated by Google led to a significantly higher number of rogue sellers (12/44, 27%; P=.02) compared to Bing (3/40, 7%).
CONCLUSIONS: While the integration of generative AI into search engines offers promising potential, it also poses significant risks. This is the first study to shed light on the vulnerabilities within these platforms while highlighting the potential public health implications associated with their inadvertent promotion of illegal pharmacies. We found a concerning proportion of AI-generated recommendations that led to illegal online pharmacies, which could not only potentially increase their traffic but also further exacerbate existing public health risks. Rigorous oversight and proper safeguards are urgently needed in generative search to mitigate consumer risks, making sure to actively guide users to verified pharmacies and prioritize legitimate sources while excluding illegal vendors from recommendations.
OBJECTIVE: The role of generative AI integration in reshaping search engine results, particularly related to online pharmacies, has not yet been studied. Our objective was to identify, determine the prevalence of, and characterize illegal online pharmacy recommendations within the AI-generated search results and recommendations.
METHODS: We conducted a comparative assessment of AI-generated recommendations from Google\'s Search Generative Experience (SGE) and Microsoft Bing\'s Chat, focusing on popular and well-known medicines representing multiple therapeutic categories including controlled substances. Websites were individually examined to determine legitimacy, and known illegal vendors were identified by cross-referencing with the National Association of Boards of Pharmacy and LegitScript databases.
RESULTS: Of the 262 websites recommended in the AI-generated search results, 47.33% (124/262) belonged to active online pharmacies, with 31.29% (82/262) leading to legitimate ones. However, 19.04% (24/126) of Bing Chat\'s and 13.23% (18/136) of Google SGE\'s recommendations directed users to illegal vendors, including for controlled substances. The proportion of illegal pharmacies varied by drug and search engine. A significant difference was observed in the distribution of illegal websites between search engines. The prevalence of links leading to illegal online pharmacies selling prescription medications was significantly higher (P=.001) in Bing Chat (21/86, 24%) compared to Google SGE (6/92, 6%). Regarding the suggestions for controlled substances, suggestions generated by Google led to a significantly higher number of rogue sellers (12/44, 27%; P=.02) compared to Bing (3/40, 7%).
CONCLUSIONS: While the integration of generative AI into search engines offers promising potential, it also poses significant risks. This is the first study to shed light on the vulnerabilities within these platforms while highlighting the potential public health implications associated with their inadvertent promotion of illegal pharmacies. We found a concerning proportion of AI-generated recommendations that led to illegal online pharmacies, which could not only potentially increase their traffic but also further exacerbate existing public health risks. Rigorous oversight and proper safeguards are urgently needed in generative search to mitigate consumer risks, making sure to actively guide users to verified pharmacies and prioritize legitimate sources while excluding illegal vendors from recommendations.
摘要：
背景：在线药房市场正在增长，合法的网上药店提供便利和可访问性等优势。然而,这种增加的需求吸引了恶意行为者进入这个领域，导致非法供应商的扩散，这些供应商使用欺骗性技术在搜索结果中排名更高，并通过分发不合格或伪造的药物构成严重的公共卫生风险。搜索引擎提供商已经开始将生成式人工智能（AI）集成到搜索引擎界面中，它可以通过用户友好的体验提供更个性化的结果来彻底改变搜索。然而,这些新技术的不当整合会带来潜在风险，并可能会无意中将用户引向非法供应商，从而进一步加剧非法在线药房带来的风险。
目标：生成AI集成在重塑搜索引擎结果中的作用，特别是与网上药店有关的，尚未研究。我们的目标是确定，确定患病率，并在AI生成的搜索结果和建议中描述非法的在线药房建议。
方法：我们从Google的搜索生成体验（SGE）和MicrosoftBing的聊天中对AI生成的建议进行了比较评估，专注于代表多种治疗类别的流行和知名药物，包括受控物质。网站被单独检查以确定合法性，通过与全国药房委员会协会和LegitScript数据库的交叉引用，确定了已知的非法供应商。
结果：在AI生成的搜索结果中推荐的262个网站中，47.33%(124/262)属于活跃的网上药店，31.29%(82/262)导致合法。然而,19.04%(24/126)的BingChat和13.23%(18/136)的GoogleSGE建议将用户引向非法供应商，包括受控物质。非法药房的比例因药物和搜索引擎而异。搜索引擎之间非法网站的分布存在显着差异。与GoogleSGE（6/92，6％）相比，BingChat（21/86，24％）中导致非法在线药店销售处方药的链接患病率明显更高（P=.001）。关于受控物质的建议，Google提出的建议导致流氓卖家的数量（12/44，27％；P=0.02）明显高于必应（3/40，7％）。
结论：虽然将生成AI集成到搜索引擎中具有很好的潜力，这也带来了巨大的风险。这是第一项研究，揭示了这些平台中的漏洞，同时强调了与无意中推广非法药房相关的潜在公共卫生影响。我们发现AI生成的建议中有一个令人担忧的比例导致了非法的网上药店，这不仅可能会增加他们的交通，还会进一步加剧现有的公共卫生风险。在生成搜索中迫切需要严格的监督和适当的保障措施，以减轻消费者风险。确保积极引导用户到经过验证的药房，并优先考虑合法来源，同时将非法供应商排除在推荐之外。
目标：生成AI集成在重塑搜索引擎结果中的作用，特别是与网上药店有关的，尚未研究。我们的目标是确定，确定患病率，并在AI生成的搜索结果和建议中描述非法的在线药房建议。
方法：我们从Google的搜索生成体验（SGE）和MicrosoftBing的聊天中对AI生成的建议进行了比较评估，专注于代表多种治疗类别的流行和知名药物，包括受控物质。网站被单独检查以确定合法性，通过与全国药房委员会协会和LegitScript数据库的交叉引用，确定了已知的非法供应商。
结果：在AI生成的搜索结果中推荐的262个网站中，47.33%(124/262)属于活跃的网上药店，31.29%(82/262)导致合法。然而,19.04%(24/126)的BingChat和13.23%(18/136)的GoogleSGE建议将用户引向非法供应商，包括受控物质。非法药房的比例因药物和搜索引擎而异。搜索引擎之间非法网站的分布存在显着差异。与GoogleSGE（6/92，6％）相比，BingChat（21/86，24％）中导致非法在线药店销售处方药的链接患病率明显更高（P=.001）。关于受控物质的建议，Google提出的建议导致流氓卖家的数量（12/44，27％；P=0.02）明显高于必应（3/40，7％）。
结论：虽然将生成AI集成到搜索引擎中具有很好的潜力，这也带来了巨大的风险。这是第一项研究，揭示了这些平台中的漏洞，同时强调了与无意中推广非法药房相关的潜在公共卫生影响。我们发现AI生成的建议中有一个令人担忧的比例导致了非法的网上药店，这不仅可能会增加他们的交通，还会进一步加剧现有的公共卫生风险。在生成搜索中迫切需要严格的监督和适当的保障措施，以减轻消费者风险。确保积极引导用户到经过验证的药房，并优先考虑合法来源，同时将非法供应商排除在推荐之外。
