AI and the future of digital global supply chains (UNCTAD)
6 Dec 2023 11:30h - 13:00h UTC
Knowledge Graph of Debate
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Jan Hoffmann
Artificial Intelligence (AI) has emerged as a transformative technology with significant impacts on trade logistics. It has the potential to revolutionize various aspects of the industry, making it more efficient, secure, and transparent. AI algorithms can analyze massive amounts of data to find the most efficient routes, taking into account factors such as fuel consumption, distance, and traffic. This optimization process allows for the reduction of costs and the improvement of overall operational efficiency.
In addition to optimizing routes and scheduling, AI can also enhance demand forecasting in trade logistics. By analyzing historical data and market trends, AI can provide accurate predictions of future demand, enabling companies to make informed decisions regarding inventory management and supply chain operations. This capability can result in reduced waste, improved customer satisfaction, and better overall resource allocation.
Furthermore, AI has the potential to enhance security in trade logistics. While the exact details were not provided in the speech, AI can play a crucial role in detecting and preventing potential security threats. By analyzing patterns, anomalies, and data from various sources, AI systems can identify potential risks and vulnerabilities, enabling proactive measures to be taken to ensure the safety of goods, shipments, and personnel involved in the trade logistics process.
Another important aspect where AI can bring significant improvements is in supply chain transparency. AI can provide real-time updates, thus improving visibility and allowing stakeholders to have a clear understanding of the status and location of goods throughout the supply chain. This increased transparency can lead to more efficient and reliable operations, reduced delays, and better decision-making.
However, there are concerns about potential job losses due to increasing automation and modernization brought about by AI. While historical examples show that structural changes have often led to the creation of new jobs in the long run, there is uncertainty about the scale of job losses this time. The book “The Coming Wave” by Mustafa Suleyman suggests that automation may lead to more job losses than it creates. This concern highlights the need for addressing the challenges that vulnerable societies and developing countries may face in implementing AI and ensuring that the benefits of this technology are inclusive and equitable.
In conclusion, AI has emerged as a powerful tool that can significantly impact trade logistics. It can optimize routes and scheduling, enhance demand forecasting, improve security, and provide supply chain transparency. However, there are concerns about potential job losses, especially in an era of increasing automation. Addressing these challenges and promoting capacity building and awareness about emerging technologies will be crucial in ensuring that AI’s benefits are harnessed effectively and that the potential negative impacts are minimized. Furthermore, promoting structural change and adaptation will be necessary to create new job opportunities and ensure sustainable economic growth in the trade logistics industry and beyond.
Emanuel Gunn
Artificial intelligence (AI) and related technologies have the potential to significantly reduce trade costs by optimizing various logistics procedures such as routing, scheduling, loading, and storing, resulting in savings in fuel, money, and emissions. Moreover, the adoption of AI can enable better optimization of the entire supply chain. It has also been found that AI can improve processes in customs clearance, agriculture, and financial services, further contributing to the reduction of trade costs. Therefore, there is a positive sentiment towards the argument that AI can effectively reduce trade costs.
However, the adoption of AI in trade faces major barriers. These include the lack of expertise, high costs, absence of good practices, and the absence of a government strategy. A survey conducted with the World Customs Organization revealed that 44% of customs authorities are already using AI and machine learning, while another 33% have plans to do so. This indicates a positive sentiment towards the potential of AI in trade. Nevertheless, the identified barriers pose challenges to the wider adoption and implementation of AI in trade.
Another important aspect to consider is the uncoordinated global race to regulate AI, which may lead to regulatory fragmentation. Different countries have their own approaches to regulating AI, which can result in inconsistencies and challenges in harmonization. This highlights the need for increased international cooperation in regulating AI to avoid fragmentation, and this sentiment is negative towards the current regulatory environment.
On the other hand, it is argued that AI can help fill development gaps in developing countries, especially in areas like medical diagnostics. This positive sentiment suggests that AI can offer these low-income emerging markets an opportunity to bridge the gap in services. However, it is also important to note that the rapid development of AI could potentially have a negative impact on services-led emerging markets. The development of chatbots using AI could jeopardize services offered by countries where such services are outsourced. This highlights a negative sentiment towards the potential negative impact of AI on these markets.
Additionally, there is a concern regarding the digital divide and related issues in developing countries. It is estimated that there are still 1.7 billion people without access to the internet, and many users in developing countries have limited bandwidth and skills in utilizing AI tools. This negative sentiment highlights the risk of developing countries being left behind in the AI revolution. Thus, urgent action is required to address this issue, and a new digital pact is suggested to bridge the digital divide.
As for the World Trade Organization (WTO), while it does not directly provide capacity building on AI for small businesses, it plays a vital role in connecting them to existing resources. The WTO can direct small and medium-sized enterprises (SMEs) towards existing courses and platforms like ‘Trade for Miss Miss’, which offer essential resources and freely accessible online courses. Moreover, plans for capacity building on AI and digital trade rules and regulations within the WTO are in their early stages, indicating a positive sentiment towards enhancing skills and understanding in these areas.
In conclusion, AI and related technologies have the potential to reduce trade costs by optimizing logistics procedures and improving processes in various sectors. However, there are barriers in adopting AI, such as lack of expertise and high costs. The uncoordinated race to regulate AI may lead to regulatory fragmentation, requiring increased international cooperation. AI can help fill development gaps in developing countries, but its rapid development could have negative impacts on services-led emerging markets. The digital divide and related issues pose risks of leaving developing countries behind, calling for urgent action. The WTO is instrumental in linking SMEs to resources and is planning capacity building efforts on AI and digital trade rules and regulations.
Philipp Isler
Artificial intelligence (AI) is identified as a game changer in trade facilitation, with the potential to greatly improve various aspects of the trade process. It can enhance goods classification, risk management, non-intrusive inspection, and post-event audits. For instance, the classification of goods using Harmonised System (HS) codes can be difficult and prone to errors, leading to fines. However, AI, in combination with machine learning, can increase the accuracy and effectiveness of goods classification, reducing errors and streamlining the process. Furthermore, risk management, which has traditionally relied on if-then-else statements, can significantly benefit from AI technology. AI can analyse vast amounts of data, identify potential risks, and provide proactive solutions, enhancing the efficiency and effectiveness of risk management in trade.
In addition to classification and risk management, AI can also enhance non-intrusive inspection and post-event audits. The use of advanced scanners and AI technology can improve the effectiveness of non-intrusive inspection, enabling more thorough checks and reducing the need for physical inspections. Moreover, AI can help enhance the audit capability of post-event audits, facilitating a more efficient and accurate assessment of trade activities. The more widespread use of scanners is seen as beneficial, and AI can further enhance the capabilities of these inspections, making them faster and more reliable.
Another area where AI can provide significant value is in transforming unstructured data into an IT structure. Many trade-related processes still heavily rely on paper-based documentation, which can be time-consuming to process. AI has the potential to assist in converting this unstructured data into a digital format, reducing manual effort and improving overall efficiency.
However, there are concerns and hesitations surrounding the adoption of AI in trade facilitation. Some argue that AI is not yet suited for mission-critical operations, and there is a level of discomfort among individuals, especially in the trade facilitation sector, towards relying on AI. There is a need to address these concerns and build trust by ensuring that AI is introduced in a structured and methodical manner, and that it is viewed as a solution to existing problems rather than a technology looking for problems.
International organisations such as the United Nations Conference on Trade and Development (UNCTAD), the World Trade Organization (WTO), and the World Economic Forum are beginning to consider and incorporate AI into their thinking. However, there is a lack of concrete courses or programmes focusing specifically on AI technology in these organisations. Instead of positioning AI as a standalone course, it is suggested that learning about AI should be woven into understanding the existing challenges and solutions in the field.
Furthermore, e-learning and AI have the potential to significantly contribute to capacity building and training. AI can add a layer of flexibility and scalability to e-learning platforms, allowing for the efficient delivery of training to a large number of individuals. This can help address the existing imbalance in access to capacity building resources, particularly in the developing world.
However, infrastructure challenges in developing countries pose a significant hindrance to the implementation of AI technology. Without proper infrastructure in place, the full potential of AI may not be realised. Nonetheless, if infrastructure challenges are addressed, developing countries can also benefit from AI technology. Communities in these countries already have access to tools like chat GPT, highlighting the potential for AI to support learning and development in these regions.
It is important to note that while AI holds promise, it is not without its challenges and potential drawbacks. There is a concern that automation, driven by AI, may lead to job displacement. However, there is also a perspective that questions the necessity of jobs in the future, suggesting that AI may usher in a new era where work is redefined and new opportunities are created.
In conclusion, AI has the potential to revolutionise trade facilitation by improving goods classification, risk management, non-intrusive inspection, and data transformation. However, hesitations and concerns remain, and it is crucial to introduce AI in a structured and methodical way, addressing fears and building trust. International organisations should incorporate AI into existing challenges and solutions rather than offering standalone courses. E-learning and AI can significantly contribute to capacity building, but infrastructure challenges need to be addressed for widespread adoption. Despite potential challenges, it is evident that AI, when used appropriately, can bring about transformative changes that benefit global trade.
Audience
In the realm of artificial intelligence (AI), there is a growing interest in providing tailored training and business development services for small and medium enterprises (SMEs) in developing countries. However, it has been observed that government and other entities lack knowledge and strategy in addressing this issue.
A major concern raised is the main challenges faced by AI in segments such as trade facilitation in Switzerland. A representative from a Swiss IT company is curious about whether these challenges are primarily technological or legal in nature. This inquiry highlights the need for a deeper understanding of the obstacles that may impede the expansion of AI technology in various industries.
In terms of capacity building, the government of Singapore is proactively supporting SMEs and individuals by offering training and resources in AI and related fields. Through the government initiative known as MySkillsFuture, 920 AI courses have been introduced, including training in project management with AI and machine learning. This proactive approach not only bridges the knowledge gap but also helps mitigate potential job losses resulting from the integration of AI into different sectors.
In conclusion, there is a growing interest in AI training and business development services for SMEs in developing countries. The challenges faced by AI, particularly in trade facilitation, warrant a deeper examination of whether they are rooted in technological or legal aspects. The positive role played by the Singapore government through capacity building initiatives demonstrates the potential for government support in helping individuals and businesses navigate the AI landscape.
Clovis Freire Jr.
Artificial Intelligence (AI) has the potential to revolutionize global supply chains through process innovation and the creation of new products. By leveraging AI technology, existing processes can become more efficient and productive. Furthermore, AI can be used to develop new products and services that fulfil the evolving needs of both humans and technology.
AI’s impact on trade logistics and trade itself is influenced by economic growth and the structure of economies. The adoption of AI optimizations to reduce trade costs may not necessarily change what is being traded, but it can greatly impact the efficiency of trade processes. Additionally, the adoption of new technologies in the production sectors may take longer to reach developing countries compared to developed countries, potentially leading to disparities in trade logistics.
Technological revolutions driven by AI have the potential to bring about transformative changes in trade. These revolutions have the capacity to not only change productive processes but also influence consumption patterns, infrastructure, and institutions. Countries that are at the beginning of a new paradigm have greater opportunities to catch up with technological developments and reap the benefits of these transformations.
Leapfrogging, a term referring to the ability of developing countries to bypass older technologies and directly adopt newer ones, can be facilitated by AI. Specifically, AI can enable people in developing countries to interact with technology without requiring extensive IT skills or literacy, opening up immense possibilities for advancement.
It is worth noting that there is a distinction between modernisation and development. While countries can consume new technologies, achieving development necessitates the productive use of these technologies, an area where developing countries often lag behind.
Governments in developing countries play a crucial role in fostering technological progress. They need to understand the importance of being at the forefront of adopting new technologies rather than catching up late in the game. Governments can guide technological development towards sustainability by implementing policy interventions and creating “green windows of opportunity.”
The use of basic technology and Information and Communication Technology (ICT) is currently lacking in Small and Medium Enterprises (SMEs), particularly in countries like Brazil where over 50% of businesses do not utilise basic technology. Efforts should focus on bringing SMEs into the digital era and providing them with access to and support for utilising basic technologies.
Innovation hubs in universities that are closely linked to the industry can play a significant role in promoting technological innovation. These hubs can collaborate with larger companies to introduce new technologies such as AI and nurture a culture of innovation.
AI has the potential to create new jobs, as demonstrated by historical records. However, the distribution of jobs is expected to undergo significant changes, with a shift towards more research and development (R&D) and innovation roles. Modelling and exercise data suggest that more people with R&D skills will be needed compared to those with production skills.
Developing countries may face capacity issues in accommodating the shift from production-oriented jobs to R&D-driven jobs, resulting in potential challenges for employment opportunities. It is crucial to address these challenges and ensure adequate support and training are provided to promote a smooth transition and inclusive growth.
In conclusion, AI holds immense potential to transform various aspects of global trade and development. However, it is essential to acknowledge the specific needs and considerations of developing countries. Governments, businesses, and educational institutions must collaborate to ensure that the benefits of AI are harnessed in a sustainable and inclusive manner, closing the technology gap and enabling developing countries to thrive in the AI-driven future.
Speakers
A
Audience
Speech speed
182 words per minute
Speech length
401 words
Speech time
133 secs
CF
Clovis Freire Jr.
Speech speed
163 words per minute
Speech length
3003 words
Speech time
1103 secs
EG
Emanuel Gunn
Speech speed
178 words per minute
Speech length
3437 words
Speech time
1161 secs
JH
Jan Hoffmann
Speech speed
144 words per minute
Speech length
3105 words
Speech time
1289 secs
PI
Philipp Isler
Speech speed
197 words per minute
Speech length
3390 words
Speech time
1034 secs
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