Viewpoint: Exploring the Impact of AI on Sustainable Tourism

Artificial Intelligence (AI) is quickly transforming the tourism industry. I believe it has the potential to positively transform the way we travel and experience new destinations and I have briefly introduced the theme before. From enhancing customer service to personalizing travel experiences, AI offers numerous benefits for both travelers and businesses.

At the same time, the concept of sustainable tourism is gaining momentum. Sustainable tourism, or eco-tourism, is a growing trend that is focused on preserving natural resources, providing economic benefits to local communities, and keeping tourism activities low-impact and respectful of host cultures.

The impact of AI on sustainable tourism is a theme I am particularly interested in and one I am willing to explore. In this blog post, I will explore some of the current and future applications of AI in the tourism sector, and how they can improve efficiency, satisfaction and sustainability. For that purpose, I will consider and evaluate four main areas of intervention where I think AI may play a determining role in this context, albeit with a few caveats to be considered.

Environmental Sustainability

Tourism is one of the world's largest industries, and it has a significant impact on the environment. The tourism industry is responsible for generating a significant amount of carbon emissions, water consumption, and waste production. To mitigate these impacts, the industry has started implementing sustainable practices, and AI can play a crucial role in aiding these efforts.

AI can truly have a strong impact on environmental conservation. It can help in this regard by providing data-driven insights that can aid in decision-making. AI can analyze data from various sources to predict demand and plan for resource allocation. AI models have clear advantages over traditional spreadsheet-based analytic methods. Applying AI-driven forecasting to supply chain management, for example, can reduce errors by between 20 and 50 percent —and translate into a reduction in lost sales and product unavailability of up to 65 percent. Companies in the telecommunications, electric power, natural gas, and healthcare industries have found that AI forecasting engines can automate up to 50 percent of workforce-management tasks, leading to cost reductions of 10 to 15 percent while gradually improving hiring decisions—and operational resilience. AI can also help companies tap new sources of data for analytics. Automation in analytics — often called “smart data discovery” or “augmented analytics” — is reducing the reliance on human expertise and judgment by automatically pointing out relationships and patterns in data. In short, AI and traditional analytics are being combined to make data analysis easier and more effective. This can be used to ensure that tourism activities are sustainable and do not put undue pressure on the environment.

AI-powered drones are being used to monitor wildlife populations and track illegal poaching activities in remote areas. For example, the Connected Conservation Initiative in Zambia’s Kafue national park uses AI to enhance conventional anti-poaching efforts by creating a virtual fence across Lake Itezhi-Tezhi. Forward-looking infrared (FLIR) thermal cameras record every boat crossing in and out of the park, day and night. AI-powered satellite imagery is also being used to detect changes in animal populations and habitats.

AI algorithms can analyze data from drones and other sources to identify areas of high conservation value and prioritize conservation efforts. For example, AI can learn how to identify which photos out of thousands contain rare species or pinpoint an animal call out of hours of field recordings – hugely reducing the manual labor required to collect vital conservation data. By analyzing satellite data, AI algorithms can help track and monitor deforestation, wildlife migration patterns, and climate change. This information can be used to develop more effective conservation strategies and protect the planet’s biodiversity.

Additionally, AI can be used to analyze satellite imagery to identify deforestation hotspots and plan reforestation efforts. For example, Imazon, a Brazil-based organization, uses artificial intelligence and Microsoft Azure services to prototype deforestation risk and prevent future losses to the Amazon rainforest . Imazon uses satellite images of Brazil’s Amazon rainforest and then stores them in the Azure cloud where Imazon AI algorithms detect unofficial roads and other risk factors of deforestation. The resulting output is visualized in an interactive map, highlighting the high-risk areas .

AI-powered virtual assistants can provide tourists with personalized recommendations based on their preferences and behavior, which can reduce the need for printed brochures and maps that may be harmful to the environment. AI travel technologies are driving quicker customer service, personalized recommendations, flight forecasting and other advancements. Chatbots and AI travel planners can answer questions, share info about hotels and destinations and perform other tasks to create individualized travel experiences. AI-powered chatbots and virtual assistants will allow hotel staff to interact with guests in real-time and provide personalized recommendations and assistance. Virtual travel assistants and chatbots are being designed to help improve passenger experience by personalizing recommendations based on traveler preference and entitlement; provide and coordinate travel changes during IRROPS (irregular operations), enabling rebooking /re-planning of the remaining itinerary.

AI can also be used to reduce the carbon footprint of the tourism industry. Inefficient transportation is a significant contributor to carbon emissions, but AI-powered algorithms can help optimize transportation movement for travelers, reducing energy consumption and emissions. For example, airlines such as AirFrance and Norwegian Airlines have signed up to use Sky Breathe, an AI technology that analyzes flight operations to reduce fuel consumption. AI also has the potential to reduce companies’ greenhouse gas emissions and cut costs by monitoring their carbon footprint and then reducing it through increased efficiency.

AI-powered traffic management systems can be used to optimize traffic flow, reduce congestion, and minimize fuel consumption by analyzing real-time traffic data. AI algorithms can adjust traffic signals and reroute vehicles to less congested roads, reducing travel time and fuel consumption. A study by Juniper Research found that smart traffic management systems will save cities $277 billion by reducing emissions and congestion globally by 2025. Smart intersections are identified as the key technology behind these savings, by enabling a reduction of over 33 hours of time spent in traffic per annum per motorist by 2025.

According to a study by MIT, using carpooling options from companies like Uber and Lyft could reduce the number of vehicles on the road by a factor of three without significantly impacting travel time. This could lead to reduced traffic congestion and lower carbon emissions. AI-powered ride-sharing services could further reduce the number of vehicles on the road, leading to less traffic congestion and lower carbon emissions.

Furthermore, AI can enable more efficient energy management in hotels and other tourism infrastructures, reducing energy consumption and costs. One promising application of AI in sustainable tourism is the use of smart algorithms to optimize energy consumption in tourism facilities. For instance, AI-powered energy management systems can be used to regulate heating, ventilation, and air conditioning (HVAC) systems in hotels, resorts, and other tourism facilities. These systems can optimize energy consumption, reduce energy costs further, and improve occupant comfort. For example, Arloid AI assists your net zero journey by using Deep Reinforcement Learning tools that can continuously analyze endless combinations of site-specific factors, which then determines the most efficient parameters for each autonomous zone in your building in real time. As a result, you will see a 30% energy cost reduction and a 40% carbon footprint reduction, all without compromising occupant comfort.

Another significant environmental impact of the tourism industry is the consumption of water. AI-powered systems can monitor water usage in hotels and other tourism infrastructures, identifying areas where water conservation can be improved by combining software, hardware, wireless communications and sensors. For example, the Energyly Water Monitoring System gives you the power to monitor your water usage and helps industries and hotels to increase productivity, compliance while enhancing safety, sustainability and service. It can help identify areas where water conservation can be improved by detecting leakages, managing water pressure and consumption, and providing real-time analytics on water usage. Another initiative is the Hotel Water Measurement Initiative (HWMI) which enables a hotel property to calculate the amount of water used per occupied room per day and per area of meeting space per hour. Using this tool will help hotels understand their water consumption, benchmark their performance, set measurable targets, complete corporate reports and report to corporate clients. AI can also help in the efficient management of water resources by predicting water scarcity and providing information for decision-making. AI can make the process of water management easier with data analytics, regression models, and algorithms. These cutting-edge technologies help in building efficient water systems and networks. AI can be used to build water plants and to get the status of water resources.

Moreover, AI can help address the issue of waste management in the tourism industry. AI-powered smart bins can help segregate and recycle waste by using advanced technology including robotics, AI and sensors to properly identify and sort recycling waste. This can reduce the amount of waste that ends up in landfills by increasing the accuracy of sorting recyclable materials. For example, a team of researchers from the University of Technology Sydney’s Global Big Data Technologies Centre (GBDTC) have designed a hi-tech “smart bin” that can do this sorting automatically. The device is equipped with an arsenal of advanced technology, combining artificial intelligence, robotics and machine vision.

AI can also help in reducing food waste by predicting the demand for food in hotels and restaurants, reducing overproduction and food wastage. For example, food waste management company Winnow estimates that its AI-powered tools have already saved 61,000 tons of Co2 to date. That’s the equivalent of 36,512,500 meals worth €42 million. Winnow’s technology collects and measures data to help inform chefs about how to adjust their purchase orders to prevent waste. The system comprises a Winnow Vision camera and Winnow Waste Monitor. The Winnow Vision system takes photos of food as it’s thrown in the bin and, using AI, the machine trains itself to recognize the food type. The Winnow Waste Monitor comprises a digital scale and a connected tablet. Using a standard bin placed on the scale, kitchen staff can throw food away in the usual way. The weight is recorded and then the user identifies the item on the tablet and selects the reason for the waste.

Social Sustainability

Social sustainability refers to the ability of present and future generations to meet their needs while maintaining or enhancing social well-being. Tourism is an industry that heavily relies on personal interactions, both between guests and service providers and among tourists. Therefore, the use of AI in tourism must strike a balance between enhancing sustainability and maintaining the social aspect of the industry.

One of the main impacts of AI on sustainable tourism is the ability to personalize travel experiences. AI-powered chatbots and virtual assistants can provide travelers with personalized recommendations based on their preferences and interests. Chatbots are software programs that can interact with customers via text or voice, using natural language processing (NLP) and machine learning (ML) to understand and respond to queries. Chatbots can provide information, assistance, recommendations and bookings for travelers, 24/7, without human intervention. For example, Kiwi.com is an online travel agency that uses an AI-powered chatbot called to help customers with flight changes, cancellations, refunds and other issues.

AI can also analyze large amounts of data from various sources, such as user profiles, preferences, behavior, feedback and social media, to create customized offers and suggestions for travelers. For example, Booking.com uses AI to recommend hotels, flights and activities based on the user's previous searches, bookings and reviews. They have a team of more than 100 data scientists working on things such as product development, customer services support, messaging and many others. Advanced algorithms can learn from a user’s browsing activities, purchase history, and a host of other factors to provide data-powered recommendations. For instance, they can offer the best hotels, the cheapest flights, alternative dates, and additional services like car rentals. Airbnb also uses AI to match hosts and guests based on their preferences and compatibility. Despite limited available data for both parties, Airbnb has successfully integrated machine learning into many aspects of its product development process. In the near-term, Airbnb is focused on utilizing machine learning to (1) personalize search rankings for guests, and (2) optimize pricing for hosts. During the early days of Airbnb, search rankings were determined by a handful of hard-coded, basic variables such as dates, duration of stay, and price. However, as Airbnb scaled its number and tenure of users, it collected valuable data that could be used to predict listing preferences. During an interview with VentureBeat, Mike Curtis, VP of Engineering at Airbnb, noted that there are a bunch of other signals that you’re giving us based on just which listings you click on. For example, what kind of setting is it in? What kind of decor is in the house? These are things Airbnb can use to feed into the model to come up with a better prediction of which listings to show you first.

Personalization is thus a vital aspect of AI-based services in the tourism industry. This use of AI can also help to reduce the environmental impact of travel by encouraging travelers to visit off-the-beaten-track destinations that are less crowded and therefore have a lower impact on the environment.

AI can further support the tourism industry in addressing social challenges by providing data-driven insight into the industry and the impact of tourism activities, which can be used to optimize and enhance tourism projects. Big data enables tourism professionals to learn more about their customers’ preferences and behaviors, which can help them tailor their services to meet their needs.

AI can create new job opportunities through the development and maintenance of AI-based products and services. According to an article on Forbes, AI technology will create more jobs than it automates. These newly created jobs will require new skills and necessitate significant investment in upskilling and reskilling. Applying AI for automation is beneficial by reducing expenses, accelerating processes, and increasing precision. The downside is that as AI automates processes, these robots are replacing some jobs but it’s predicted that AI will create 97 million new jobs by 2025. A recent study of 1,000 global companies by Accenture found that AI is already creating three new categories of jobs: trainers, explainers and sustainers. Through tax benefits and other incentives, policy makers can encourage companies to invest in human capital, including job creation, learning and capability building, and wage growth.

Finally, AI-powered language translation solutions have helped to break down language barriers, facilitating communication and cultural exchange. For example, Lingmo International offers a range of next-generation translation products and services, including innovative mobile apps and state-of-the-art wearable translation devices. These products use IBM® Watson® cognitive AI to deal with dialects and grasp nuances that traditional translation tools can’t handle. This has helped users gain greater contextual awareness and has made it easier for businesses to collaborate across countries, continents, and cultures. This has opened up opportunities for people all over the world to connect with each other, share ideas and learn from different perspectives. Business transactions, travel, and education have all been made easier with the help of AI-powered language translation.

Economic Sustainability

As the world becomes more interconnected and travel becomes more accessible, tourism has become one of the largest and most profitable industries in the world. The tourism industry has been one of the sectors with the highest growth rate in recent years, contributing significantly to the economic development of many countries worldwide. In fact, the World Travel and Tourism Council estimated that tourism accounted for 10.3% of global GDP in 2019, and even after the hiatus caused by the COVID-19 pandemic, which brought the industry to its knees, it has been growing steadily back again since 2021. However, this growth has also led to challenges and concerns regarding sustainability and the impact it has on the economic stability of communities. The benefits of tourism are not always shared equally, and many local communities often do not benefit from tourism as much as they could.

One solution that has been brought forward as a way to address these challenges is the integration of artificial intelligence in the tourism industry. AI can help to ensure that tourism activities contribute to the economic growth and development of local communities in several ways.

Firstly, we should again consider that AI can be used to gather data on tourist behavior and preferences. AI can help understand and predict tourist behavior by analyzing data from various sources such as User Generated Comments (UGCs) post their travel1. AI methods such as Aspect Based Sentiment Analysis (ABSA) and Emotion analysis (EA) can be used to predict tourist behavior. AI can also facilitate the integration of physical and online/virtual elements to enhance tourists’ experiences pre-, during, and post-travel. This knowledge can help local businesses to tailor their services and products better, adapt to emerging trends, and offer unique experiences to attract tourists. For example, personalized AI modeling development for smart tourism platforms can precisely predict tourism choice behavior patterns. This can potentially improve decision-making and decision-support in the tourism/hospitality industries. It can also help tourism professionals allocate resources effectively and efficiently, improving customer satisfaction while reducing environmental impacts. By doing so, local communities can better attract and retain tourists, which can lead to increased economic growth and development.

Secondly, AI can be used to improve the efficiency of tourism operations. For example, AI-powered chatbots can be effectively applied in the Travel, Tourism & Hospitality industry. They can offer answers to frequently asked questions through automated responses. This can help free up staff to focus on other tasks while providing tourists with automated customer service. AI can be used to optimize scheduling and resource allocation in tourism businesses. AI-driven schedule optimizers offer solutions that smooth out and speed up workforce management processes. By adopting customized AI-driven schedulers, businesses can optimize across all their spheres of operation, save time and money, and ultimately boost their productivity. Additionally, variability in tourism fluctuations can be reduced and inbound tourism numbers/spending significantly increased by implementing smarter (data-driven) marketing budget allocations. Furthermore, AI-powered revenue management systems can significantly enhance hotel revenue management by using predictive modeling to analyze historical data and predict future demand and revenue, optimizing pricing and availability to maximize revenue. According to McKinsey, AI-based pricing and promotion have the potential to deliver between $259.1B to $500B in global market value. The global Revenue Management market is expected to grow from $14.5B in 2019 to $22.4B by 2024, attaining a Compound Annual Growth Rate (CAGR) of 9.6%. Boston Consulting Group (BCG) found that automating pricing rules with AI in revenue management systems can increase revenues up to 5% in less than nine months. Additionally, AI-powered marketing solutions have helped to target the right audience, increase brand awareness, and drive customer engagement. AI-powered marketing solutions have helped businesses to intelligently choose important information from each interaction with their customer and leads. By gathering contact information, site behavior and buying preferences, businesses can fine-tune products or processes to enhance customer engagement. AI can dynamically populate products on apps, webpages or via email based on data assimilated about customer attributes, browsing patterns, or situational context to create a personalized shopping experience. Also, In the tourism industry, a new scale has been developed that offers destination marketing organizations (DMOs) and service providers a tool to measure experiences and to segment tourists by the level of engagement. By streamlining their operations, businesses can reduce costs and increase their profits, which can help to support local communities in the long term.

Thirdly, I am reminded that AI can also help promote sustainable tourism practices by creating smart tourism destinations that reduce negative impacts. As mentioned before, AI can help optimize energy and resource use, reduce waste, and protect fragile ecosystems. With AI, tourism destinations can also develop smart transport systems that reduce carbon emissions, smart waste management systems that sustainably dispose of waste, and smart resource management systems that utilize natural resources sustainably. One way is through the use of smart technologies such as artificial intelligence, cloud computing, and the Internet of Things (IoT). These technologies can be integrated into a platform that offers explicit information and efficient services to tourists. Another way is through the implementation of effective policies and strategic decision-making by policymakers. For example, the United Nations World Tourism Organization (UNWTO) has published a report on Climate Action in the Tourism Sector which provides an overview of methodologies and tools to measure greenhouse gas emissions. The UNWTO also launched the Glasgow Declaration at COP26 UN Climate Change Conference which proposes a coordinated plan for tourism to support the global commitment to halve emissions by 2030 and achieve net zero by 2050.

Lastly, AI can create positive economic impacts in local communities by encouraging cultural preservation, and enhancing local industry development. The cultural and creative sectors are a significant source of jobs and income, and also generate important spillovers to the wider economy. They are a driver of innovation, a source of creative skills with strong backward and forward linkages in the economy, and act as a magnet that helps drive growth in other sectors such as tourism. AI is one of the top five technologies likely to be adopted by companies by 2025. AI-powered systems can help develop tourism products and services that promote local culture, heritage, and traditions by providing a framework for communities to assess cultural, social, and environmental factors. For example, a study conducted in rural Austria investigated success and sustainability factors for tourism offers based on intangible cultural heritage, such as traditional nature-related knowledge and practices. The study proposed an assessment framework for communities to package knowledge and practices into tourism offers that contribute to sustainable tourism development with shared benefits in rural areas away from well-known tourism centers and attractions. Such activities also contribute to safeguarding and revitalizing intangible cultural heritage and cultural landscapes in a sustainable manner, balancing entertainment and educational/cultural values. They can also help local businesses expand their reach, increase their revenue, and make informed decisions to better serve tourists.

Cultural Heritage Sustainability

Cultural heritage is an essential aspect of tourism. Tourists usually visit various parts of the world to experience the cultural traditions, customs, architecture, and art. However, cultural heritage is also vulnerable to degradation due to natural disasters, human activities, and climate change. It is, therefore, crucial to preserve cultural heritage to promote sustainable tourism. AI has emerged as a useful tool for cultural heritage preservation.

AI can be used to detect, monitor, and analyze changes in cultural heritage sites. This is done through the use of remote sensing technologies such as drones, satellite imagery, and LiDAR (Light Detection and Ranging). For example, satellite imagery can help monitor cultural heritage sites under threat. Drones can be used for 3D documentation of critical heritage infrastructures in cultural heritage for which drones are necessary. Machine learning methods based on deep learning can help detect built cultural heritage from satellite imagery. These technologies enable the creation of accurate 3D models of cultural heritage sites, which can be used to monitor changes in the condition of the sites over time. This information can then be used to plan and implement preservation measures.

AI may as well be used to develop predictive models that can forecast the impact of climate change and other environmental factors on cultural heritage sites. These models can help to inform decision-making processes, such as the design of preservation measures and policies. AI is being used to help combat climate change by providing insights into where uncertainties come from related to climate change and that can help us understand what the models are telling us, which can feed back into better observation programs, improving the models, and even using AI as part of the model system. AI offers us the unprecedented ability to harvest knowledge from the experiments we are currently conducting on Earth’s systems to design new ones that are optimized for both humans and the environment. As predictive analytics models improve, innovators in this space are advocating for better access and ways to interpret climate data.

Moreover, AI can be used to create experiences that enable tourists to experience cultural heritage sites without necessarily having to visit them physically, which can be particularly useful in situations where cultural heritage sites are inaccessible or too fragile to be opened to the public. AI-powered tools such as augmented reality (AR) and virtual reality (VR) can provide visitors with immersive and interactive experiences, using computer-generated images, sounds and sensations that bring historical and cultural sites to life. VR and AR can be used for various purposes in tourism, such as destination marketing, education, entertainment and accessibility. This can help to promote responsible tourism by encouraging visitors to respect and appreciate local cultures and traditions. For example, the National Geographic VR app allows users to immerse themselves in 360-degree adventures and experiences on land, air, and sea. The app is available on Oculus Go, Oculus Quest, and Gear VR. With the app, users can travel as a National Geographic explorer with a mission to discover and photograph two of the most iconic locations on the planet: Antarctica and Machu Picchu, Peru. This interactive experience lets the entire family discover the world without ever leaving home.

In the same vein, AI can be used to create virtual tours of destinations that allow travelers to get a sense of the area before they even arrive. For example, the Faroe Islands is just one destination using new technologies to create a virtual tourism experience. Virtual travel can also help visitors experience destinations that are remote, difficult to get to, or need to be preserved without humans trampling around all over the place. AI could thus be applied to provide ‘real-time’ insight into the impact of their tourism activities, as well. This could help tourists to choose activities with lower environmental and cultural impacts, as well as understand and identify sustainable accommodations, attractions, and transportation options prior to their departure.

Finally, AI may also trigger further development of natural language processing (NLP) technologies. NLP tools have advanced significantly in recent years, changing common notions of what this technology can do. NLP is focused on how computers can process language like humans do. It has been used for simple analytics tasks, such as classifying documents and analyzing the sentiment in blocks of text, as well as more advanced tasks, such as answering questions and summarizing reports. NLP is so core to the development of AI that it was one of the very first sets of tasks that researchers attempted to tackle with intelligent systems. Conversational AI trends are affecting machine-to-human, human-to-machine and back-and-forth human and machine interactions. This could potentially enable tourists to communicate with cultural heritage sites using natural language. This can be achieved through the use of chatbots or virtual assistants that can provide tourists with information on cultural heritage sites, answer questions, and even act as tour guides. Chatbots and virtual assistants are commonly used in the tourism sector to facilitate information and recommendation retrieval, such as opening hours of local restaurants. They can also handle customer care support. In the domain of cultural heritage, virtual assistants have been applied to virtual visits of cultural sites. They can be deployed in real or virtual environments as virtual guides to engage visitors and deliver a comprehensive learning experience.

But what about the Cons?

It is important to recognize that AI is not a silver bullet for all tourism-related issues. While AI has the potential to improve environmental sustainability in many ways, there are also some concerns of potential drawbacks and challenges associated with its use, which I will briefly consider, although keeping a positive outlook with solutions for mitigation.

Energy Consumption: AI requires a significant amount of computing power and energy to operate, which can have a negative impact on the environment. The energy needed to run data centers and AI models can contribute to greenhouse gas emissions and climate change. One potential solution to this issue is the use of renewable energy sources, such as solar or wind power, to run data centers and power AI models. Another way to address the energy consumption issue is to develop more energy-efficient AI models and algorithms. For instance, researchers are exploring the use of sparsity in deep learning to reduce the amount of computing power needed for AI training and inference. Sparsity refers to a matrix of numbers that includes many zeros or values that will not significantly impact a calculation. Researchers have been trying to pull out as many unneeded parameters as possible from a neural network without unraveling AI’s accuracy. The goal is to reduce the mounds of matrix multiplication deep learning requires, shortening the time to good results. Sparsity can reduce the memory footprint of regular networks to fit mobile devices, as well as shorten training time for ever-growing networks. In a paper by Torsten Hoefler et al., they survey prior work on sparsity in deep learning and provide an extensive tutorial of sparsification for both inference and training. They describe approaches to remove and add elements of neural networks, different training strategies to achieve model sparsity, and mechanisms to exploit sparsity in practice.

Cost and Access: Implementing AI systems can be expensive and may require specialized skills and knowledge, which can limit their accessibility to smaller tourism businesses and destinations. This could widen the economic divide between larger and smaller tourism businesses and destinations, leading to further economic inequality. However, the long-term benefits of implementing AI systems in the tourism industry may outweigh the initial costs. AI can improve efficiency, reduce costs, and enhance the overall visitor experience, leading to increased revenue and competitiveness. Additionally, initiatives to provide training and support for smaller businesses and destinations can help bridge the gap in accessibility and promote more widespread use of AI in the industry, by collectively investing in upskilling. This can lead to increased trust between employers and employees, citizens and governments, and across broader society. Companies can also develop their own courseware for reskilling and upskilling employees. Several online learning platforms such as Coursera, Udacity, and Udemy have promised to help businesses stay ahead of digital disruption by offering courses in areas including data science, machine learning, and AI.

Data Bias: AI systems rely on data to make decisions, and if the data used is biased, it can lead to unfair and inaccurate conclusions. For example, if an AI system is trained on data that is biased against certain groups or regions, it may not accurately represent the needs and perspectives of those communities. To combat this issue, it's important for AI developers to carefully consider the data sets they use and ensure that they are representative of diverse perspectives. Additionally, ongoing monitoring and testing of AI systems can help identify and address any biases that may arise. By prioritizing fairness and accuracy in AI development, we can work towards creating more equitable and just systems. One approach to reducing bias in AI is to increase diversity in the teams that develop and test these systems. This is because a more diverse team can bring a wider range of perspectives and experiences to the table, which can help to identify and mitigate potential sources of bias in AI systems. For example, if none of the researchers building facial recognition systems are people of color, ensuring that non-white faces are properly distinguished may be a far lower priority.

Additionally, incorporating ethical principles and guidelines into AI development can help ensure that these systems are aligned with values of fairness, transparency, and accountability. To develop ethical AI, it is important to identify potential pitfalls, understand human biases, enable control, ensure transparency and accountability, and anticipate AI’s impacts on the workforce with upskilling. Organizations should educate and raise awareness about AI, be transparent, control for bias, make it explainable, make it inclusive, and follow the rules. There are many frameworks and guidelines that exist to help organizations create and implement more ethical AI. For example, UNESCO’s General Conference adopted the Recommendation on the Ethics of Artificial Intelligence in November 2021 which is the very first global standard-setting instrument on the subject. The European Union also has Ethics Guidelines for Trustworthy Artificial Intelligence which put forward a set of 7 key requirements that AI systems should meet in order to be deemed trustworthy.

Inequity: AI systems may also be biased against certain groups, leading to inequitable outcomes. If an AI system is used to allocate resources such as hotel rooms or tour bookings, it may prioritize certain tourists over others, leading to unequal treatment and potentially exacerbating social and economic inequalities. This bias can be introduced due to a variety of factors, such as biased training data or a lack of diversity in the team that created the AI system. To address this issue, it is important to regularly audit AI systems and ensure that they are being used in an equitable manner. Additionally, efforts should be made to increase diversity in the AI industry to prevent these biases from being introduced in the first place. Incorporating human oversight into the decision-making process can help to ensure that AI systems are being used in a fair and equitable manner. According to an article from Fitch Solutions, human oversight is a useful tool to reduce risks associated with possible errors and final decisions should rest with natural persons. This maintains the value of human expertise which can be used to eliminate errors in training data and improve accuracy. The EU Artificial intelligence (AI) regulation proposal itself states that AI systems should empower human beings, allowing them to make informed decisions.

Human biases are well-documented and can make their way into artificial intelligence systems with harmful results. AI can help identify and reduce the impact of human biases, but it can also make the problem worse by baking in and deploying biases at scale in sensitive application areas. Therefore, it is important for institutions to ensure human oversight and compliance with data regulations and monitor their algorithms to avoid bias.

Lack of Transparency: AI models can be complex and difficult to understand, making it challenging for stakeholders to evaluate the decisions they make. This lack of transparency can make it difficult to trust AI systems and could lead to unintended consequences. To address this issue, researchers and developers are working to create more explainable AI models. These models use techniques such as feature visualization, attention mechanisms, and interpretable decision rules to provide insights into how they make decisions. Explainable AI (XAI) tools analyze the inner workings of a model and translate its behavior into human-understandable terms. Hard as it may be, by increasing transparency and understanding, stakeholders can make more informed decisions about the use of AI systems. Explainable AI models can also help identify and mitigate biases that may be present in the data used to train the model. In truth, despite their capabilities in simplifying and explaining model behavior, many prominent XAI tools lack features that could be critical in detecting bias. However, some researchers have created a framework for evaluating explainable AI tools with respect to their capabilities for detecting and addressing issues of bias and fairness as well as their capacity to communicate these results to their users clearly. This can help developers suggest modifications needed in their toolkits to reduce issues like fairwashing. By understanding how the model makes decisions, it becomes easier to identify when the model is making decisions based on biased or incomplete data. This can help to ensure that AI systems are used ethically, responsibly and more transparently.

Privacy Concerns: AI systems require large amounts of data to operate, and there are concerns about how this data is collected, stored, and used. If tourists' personal information is collected and used without their consent, it could lead to privacy violations and a loss of trust in the tourism industry. To address these concerns, it is important for AI systems in tourism to adhere to strict data privacy policies and regulations. Tourists should be informed about what data is being collected, how it will be used, and given the option to opt out if they do not wish to participate. Additionally, AI systems should use secure methods for storing and processing data to prevent unauthorized access and ensure the protection of personal information. One way to ensure data privacy in AI systems is through the use of encryption techniques. By encrypting data, it is much more difficult for unauthorized individuals to access and use personal information. Encrypting data at rest and in transit (both structured and non-structured) is already common practice within companies, to protect confidential, secret and proprietary information. Encrypting data while in use, however, is a less common practice. Data in use is data that is stored in a non-persistent digital state and/or that is being processed, like in the lifecycle of a machine learning (ML) model. Two of the most promising emerging protocols used for encrypting data are secure multiparty computation (SMPC) and homomorphic encryption (HE). Secure multiparty computation (SMPC) is the act of jointly computing a function while keeping the inputs private.

Additionally, AI systems can implement several anonymization methods to remove personally identifiable information (PII) from data sets and protect tourists’ privacy. Data anonymization is the process of protecting private or sensitive information by erasing or encrypting identifiers that connect an individual to stored data. Some common techniques include data masking, pseudonymization, generalization, data swapping, and data perturbation. These techniques can help retain the data while keeping the source anonymous.To maintain trust in the tourism industry, it is crucial for AI systems to prioritize data privacy and security.

Job Displacement: AI can increase efficiency overall in the tourism industry, but it could also lead to job displacement, particularly in industries such as manufacturing, hospitality and transportation. This could have a negative impact on local economies, communities, and cultural sustainability, particularly if the displaced workers do not have access to alternative employment opportunities. For example, local artisans and craftspeople may feel the threat of AI, if tourists rely on AI-generated souvenirs and products rather than purchasing locally made goods. However, it is important for companies and destinations to consider the potential impact of AI on local communities. One solution could be to use AI to enhance the production process for local artisans rather than replace them entirely. AI can help improve efficiency in manufacturing environments, leading to better performance and results. For example, using AI and machine learning, systems can test hundreds of mathematical models of production and outcome possibilities, and be more precise in their analysis and results. This can help local artisans improve their production process and increase their competitiveness. Additionally, promoting the unique cultural value and quality of locally made goods can help encourage tourists to support the local economy and preserve cultural traditions.

It is also important to note that while AI may displace some jobs, it can also create new job opportunities in fields such as data analysis, software development and AI maintenance. It is vital for individuals and organizations to be proactive in developing the skills necessary to adapt to these changes and take advantage of new opportunities that arise.

Cultural Appropriation and Inaccurate Representations: AI systems may perpetuate cultural appropriation by reducing cultural practices and traditions to stereotypes and commodifying them. This can lead to a loss of cultural identity and authenticity, and can be disrespectful to local communities. Namely, AI systems that are trained on biased or incomplete datasets can perpetuate harmful stereotypes and contribute to cultural appropriation. Moreover. AI systems that rely on biased or incomplete data can lead to inaccurate representations of local cultures and communities, heritage sites and artifacts. This can perpetuate stereotypes and reinforce existing biases, rather than promoting understanding and respect. It is important to ensure that AI systems are developed and trained in a way that respects and values diverse cultures and traditions, and that the input data is representative and inclusive. One way to do this could be to involve members of the local communities in the development and implementation of AI systems. This can help ensure that AI systems are designed with a diverse range of perspectives and experiences, reducing the risk of bias and discrimination. Another approach is to use data-driven methods to identify and address instances of bias and discrimination in AI systems. Additionally, using model-based and knowledge-based AI that operationalizes socio-ethical and legal principles can also help prevent cultural appropriation and inaccurate representations .

Lack of Personalization: While AI can improve efficiency and reduce costs, it may also lead to a loss of personalization and customization in the tourism experience. If tourists feel that their experiences are too standardized or impersonal, it could lead to a decline in tourism and economic sustainability. However, AI can also be used to enhance personalization by providing tailored recommendations and experiences based on individual preferences and behavior. This can lead to a more enjoyable and satisfying travel experience for tourists, ultimately contributing to the growth and sustainability of the tourism industry. Therefore, it is important to strike a balance between the use of AI for efficiency and personalization. Tourism businesses should consider integrating AI with human touchpoints, such as customer service representatives, to ensure that tourists feel valued and heard throughout their travel experience. AI can enhance tourism experiential services and act as an effective complementary dimension to the future of tourism. AI offers travel services that can be better automated, customized and insightful. AI allows travelers to learn about their behaviors, interests and inclinations and provide a personalized experience. However, AI cannot surpass the human touch which is an essential determinant of experiential tourism. Therefore, it is important for tourism businesses to consider integrating AI with human touchpoints, such as customer service representatives, to ensure that tourists feel valued and heard throughout their travel experience.

Lack of Authenticity: AI can generate simulations and virtual representations of cultural heritage sites and artifacts, but these may lack the authenticity and nuance of the real thing. This could reduce the value of cultural heritage sites and artifacts and lead to a loss of cultural identity. One way to address this issue is to work with experts in the field, such as archaeologists and cultural heritage specialists, to ensure that the virtual representations are as accurate and authentic as possible, and to humanize the AI-generated content by using techniques such as writing in the tone of humans, infusing emotions and sensory details, including human-generated images and graphics, making it less jargon, and creating fictional stories. Another way is to use AI-generated content as a first draft and then have a human review and edit it to ensure that it sounds natural and authentic.

Additionally, it may be necessary to include educational materials and context with the virtual representations to help users understand the significance and context of the cultural heritage sites and artifacts. Another way to address this issue is to use AI to augment and enhance the visitor experience of cultural heritage sites and artifacts, rather than replacing it. For example, virtual reality and augmented reality technologies can be used to provide visitors with additional information and insights into the history, significance, and context of the cultural heritage sites and artifacts. Virtual reality (VR) and augmented reality (AR) technologies are increasingly being applied in museums and cultural heritage sites to improve visitors’ experience and learning. These technologies allow for high interactivity and can provide visitors with additional information and insights into the history, significance, and context of cultural heritage sites and artifacts. Also, mixed reality (MR), which encompasses both augmented reality and augmented virtuality, provides hybrid environments where real and virtual objects coexist, interact, and can be manipulated by users. This unlocks unprecedented capabilities for organizations to provide their target audiences with exhilarating, meaningful, and inclusive cultural experiences fostered by emerging technologies.

The digital acquisition of artifacts generates accurate 3D replicas that can be displayed via different digital media. This allows visitors to virtually explore real objects or buildings using AR. The employment of MR by cultural organizations offers a wide range of opportunities for learning, communication, and entertainment. These new tools and techniques can enable new means of exploration, interaction, and interpretation of culture and heritage. This can help users develop a deeper appreciation and understanding of the cultural heritage, while also preserving the authenticity and nuance of the real thing.

Lack of Human Connection: AI could reduce human connection and cultural exchange in the tourism industry, leading to a loss of authentic cultural experiences for both tourists and locals. As AI technology takes over certain tasks in the tourism industry, such as language translation and trip planning, there is a risk that human interaction and connection will become less important. This could lead to a homogenization of the industry, with less emphasis on unique, local experiences and cultural exchange. However, if AI is used thoughtfully and in conjunction with human interaction, it could actually enhance cultural exchange and provide more authentic experiences for tourists and locals alike. It is important to strike a balance between the use of AI technology and human interaction in the tourism industry. One way to achieve this is by using AI to enhance human interaction, such as using more advanced language translation technology to actually facilitate communication between tourists and locals when needed. Another way is to ensure that AI is used in a way that promotes local culture, such as by recommending local restaurants and experiences to tourists. Ultimately, the goal should be to use AI as a tool to enhance, not replace, human connection and cultural exchange in the tourism industry by promoting and preserving cultural elements. The UNWTO provides support to its members in strengthening cultural tourism policy frameworks, strategies and product development. It also provides guidelines for the tourism sector in adopting policies and governance models that benefit all stakeholders. Cultural tourism is one of the largest and fastest-growing global tourism markets. Culture and creative industries are increasingly being used to promote destinations and enhance their competitiveness and attractiveness.

Dependence on Technology: Last but not least, relying on AI to solve environmental, economic, social or cultural sustainability challenges could lead to a dependence on technology rather than addressing the root causes of problems. It is important to also focus on sustainable practices and policies that prioritize the well-being of local communities and economies, preservation and celebration of local cultures, as well as reduction of waste and protection of the environment. While AI can be a powerful tool in addressing sustainability challenges, it should not be seen as a silver bullet solution. Rather, it should be used in conjunction with sustainable practices and policies that prioritize the long-term health and well-being of our planet and its inhabitants. As we continue to develop new technologies and rely on them to solve sustainability challenges, it is important to recognize that these technologies may also have unintended consequences. It is crucial to assess the potential risks and benefits of these technologies before implementing them on a large scale. Additionally, it is important to involve local communities and stakeholders in the decision-making process to ensure that their voices are heard and their needs are met.

Last thoughts

The tourism industry holds immense potential for driving economic growth, cultural exchange, and environmental conservation. In my opinion, AI has the potential to transform the tourism industry while promoting more efficient sustainable tourism practices. In other words, AI can play a very important role in helping the tourism industry evolve into a more sustainable and responsible industry, which we all need. By providing better insights and access to data, AI can help to optimize existing sustainable tourism practices, create new and innovative experiences, and empower travelers to make more informed decisions.

AI can quickly becoming a key player in optimizing sustainable tourism practices, streamlining operations, and helping to protect natural resources and cultural heritage. By integrating AI into the tourism industry, sustainable practices can be significantly improved. AI can provide access to detailed analytics and insights into areas such as energy consumption, resource management, and guest engagement. This allows for better decision-making and improved operational efficiency. AI can also help to automate mundane, time-consuming tasks, freeing up staff members to focus on more important, strategic activities. Furthermore, AI can be used to create intelligent applications that predict and analyze customer preferences, which can help optimize both customer satisfaction and resource conservation.

AI can also help to minimize the negative impact of travel on the environment and local communities while maximizing the benefits for all stakeholders. It is a powerful tool for ensuring that tourism activities contribute positively to local communities' economic growth and development. It can support the tourism industry in achieving a more sustainable and responsible approach, creating a win-win situation for tourists and local communities.

Harnessing the power of AI in tourism can help to ensure that tourism's economic benefits are shared more widely and sustainably, making tourism a catalyst for economic growth and development. Ultimately, by embracing AI responsibly and promoting sustainable tourism practices, we can help to create a more equitable, prosperous, and livable future for all.

Therefore, it is essential for stakeholders in the tourism industry to leverage AI's potential to promote environmental, social, economic and cultural heritage sustainability. To achieve these goals and fully realize the potential of AI in tourism, tourism stakeholders must work together and prioritize responsible use and governance of these technologies. This includes ensuring transparency, accountability, and ethical considerations in AI development, as well as involving local communities and stakeholders in decision-making processes, and ensuring that the development and integration of AI-based services prioritize the well-being of guests and service providers. They must consider the potential loss of jobs, data privacy, and the importance of human touch in tourism services. Only by striking a balance between technological advancements and social well-being can the tourism industry leverage AI to achieve sustainable development.

While technology can play a crucial role in addressing sustainability challenges, it is important to remember that it is not a panacea. We must also recognize and address systemic issues such as inequality, overconsumption, and unsustainable practices that contribute to these challenges in the first place. It is only through a comprehensive approach that we can truly create a sustainable future for all.

AI has many more potential applications in the tourism industry, such as flight forecasting, smart pricing, sentiment analysis, facial recognition and biometrics. These applications can help optimize operations, reduce costs, increase revenue, enhance security and protect the environment. However, AI also poses some challenges and risks for the tourism sector, such as ethical issues, social impacts, legal implications and technical limitations. Therefore, it is important to balance the benefits and drawbacks of AI in tourism, and ensure that it is used responsibly and ethically.

🔴 Viewpoint is a random series of spontaneous considerations about subjects that linger in my mind just long enough for me me to write them down. They express my own often inconsistent thoughts, ideas, assumptions and speculations. Nothing else. Quote me at your own peril.