Sajjad Reyhani Haghighi, Mikaeel Pasandideh Saqalaksari, Scott N. Johnson The implementation of chatbot services could significantly improve the efficiency of the inquiry-handling processes related to ecology and environmental sciences (Ranoliya et al. 2017, Rosruen and Samanchuen 2018, Quah and Chua 2019, Ukpabi et al. 2019). For example, according to Hitachi Ltd.'s method for calculating CO2 emissions, the use of chatbot service has led to a decrease in CO2 emissions by 40%. This decrease is a result of the reduction in the number of hours needed to handle inquiries from employees by 60% and the 8% reduction in power consumption of IT devices (Hitachi Ltd. n.d.). Berners-Lee (2020) reported that the production of emails generates varying amounts of CO2, ranging from 0.03 to 26 g, depending on the length and number of recipients. Emails globally are estimated to account for as much as 150 million tons of CO2e in 2019, about 0.3% of the world's carbon footprint. In this context, chatbot services offer a more sustainable alternative. For instance, chatbots can provide accurate and efficient responses to inquiries based on a dataset of frequently asked questions by leveraging Artificial Intelligence Markup Language (AIML) and Latent Semantic Analysis (LSA; Ranoliya et al. 2017). This Chatbot service could help lower the carbon footprint of organizations, such as universities, businesses, and others, through a potential reduction in the need for traditional email inquiries, while still providing users with a satisfying interactive experience. The carbon emissions produced by the usage of devices, the internet, and supporting systems are estimated to contribute about 3.7% to the world's total greenhouse gas emissions (Ferreboeuf 2019). Despite the lack of concrete evidence, chatbots are thought to be more energy efficient than traditional internet searching. This is because chatbots can provide personalized and accurate results with less energy consumption by using natural language processing algorithms and machine learning techniques to understand the user's query and retrieve relevant information in real-time, without the need for multiple searches or clicks. In contrast, traditional internet searching requires multiple searches and clicks, leading to higher energy consumption due to data processing and transfer between servers and devices. Both chatbots and traditional internet searching rely on energy consumption, which can vary depending on several factors, including the number of searches, length of conversation, query complexity, device type, and algorithmic efficiency. Direct comparison of carbon dioxide emissions and energy consumption between search engines and chatbots is currently impossible due to a lack of confirmed information. However, it is important to take a broader view when comparing the energy usage of these two technologies. While the energy efficiency of a single search performed by a chatbot or search engine may not necessarily differ significantly from one another, the cumulative effect of millions of users utilizing these platforms, in addition to the energy required for infrastructure maintenance and expansion, has the potential to result in a significant impact on energy usage and carbon emissions. As such, it is crucial to consider the broader implications of chatbots and to promote the development of more energy-efficient algorithms and hardware to reduce their environmental impact.