2018 Evidence Meeting 6 – Trade – Overview
Please download PDF Evidence Meeting 6 Overview here.
Video recording of the Evidence Meeting available below.
- Date: 15 October 2018
- Time: 5:30 – 7:00 pm
- Location: Committee Room 1, House of Lords
- Participants: 104 registered attendees
The All-Party Parliamentary Group on Artificial Intelligence (APPG AI) was set up by co-chairs Stephen Metcalfe MP and Lord Clement-Jones CBE to explore the impact and implications of Artificial Intelligence.
In 2018, the APPG AI has decided to focus on building a roadmap to understand the practical steps for addressing key AI implications. The group has prioritised six policy areas: data, skills, accountability, innovation & entrepreneurship, infrastructure, and trade. Each meeting will explore one of the six policy areas’ respective economic, social, and ethical implications.
Evidence Meeting 56concentrated on: Trade
- Opening Remarks
- Questions and Answers (39:16)
IV. Questions for Inspiration
- How has AI changed trade internationally and within national borders?
- How can industries shift their business models to adopt AI?
- How do we shift from e-commerce to ai-commerce?
- What changes have to be made to UK taxing frameworks?
V. Background: Setting the Scene
Globally, AI is changing the factors for success across all industries – completely transforming the productivity of organisations in developed, emerging, and frontier markets. Overall, AI can enhance the quantity and quality of available goods and services – and also improve the speeds they are made available.
AI technologies have the capability to offer products and services tailored to the personalised preferences and needs of each customer. Also, AI technologies can make products and services accessible to a wider group of individuals – breaking conventional geographic and social boundaries.
For UK to benefit from these two key AI trends, the nation needs to build an innovative trade ecosystem which encourages the shift from e-commerce to AI-commerce. We can map a technology trade trajectory from analogue trade (broadcasting and phone orders) to e-commerce where the Internet sparked a revolution for procurement through online catalogues, the shopping trolley, new business models around peer-to-peer auctions, price comparison sites and online payments. The current revolution in AI commerce disrupts everything once again – particularly all we know related to supply and demand economics about how markets work. Conventionally, markets tend to be classified by their degree of competition or the number of buyers and sellers bargaining a price. The e-commerce revolution enforced this model; however, AI-commerce serves as a completely disruptive force, transforming these specific market structures.
Supply chains are being completely reconfigured and most commercial market transactions underpinned by AI commerce do not take place in competitive market arenas as we now know them. Individuals and businesses are involved in ongoing, more intensive bilateral relationships in which they exchange data and information. The new market institutions in which trade itself is conducted are ‘intelligent agents’ (such as chatbots and Alexa) interacting directly with consumers and clients, ‘Internet of things’ organizing the buyside (e.g. via connected homes and smart grids), ‘information exchanges’ via online emerging data driven platforms, and the contract itself, which will be processed through a blockchain mechanism and smart contracts.
The drivers of AI commerce are transaction cost efficiency as trade processes increasingly become faster and ‘smarter’ via connected data. Despite being automated, trade will also become personalized and customer-centric. Most of all, it has the potential to become much cheaper.
This trade transaction is different from the exchanges in traditional markets, as we commonly tend to think of them. Till now, the market offerings of products and services – the conventional source of market competition – were the most important element for organisations. However, now these market offerings have become less significant and other factors are critical to survive and thrive in today’s competition. The relational exchanges between buyers and sellers are still competitive but the focus now lies on the first factor, personal and business data access. We can think of it as a ‘social contract’ underpinning the trading contract, as you cannot trade unless you disclose your data in public or privacy commons. The ‘social contract’ for data exchanges will probably underpin all AI trade contracts in goods and services in the future. The second factor in market competition is the AI technology capabilities of the trading organizations, and the ability to build and control unique platforms (the third factor) on which users can connect. We need to ensure that UK invests in the new market institution platform solutions which the public and private sector can subscribe to or adopt in their route to markets. In consequence, organisations regardless of size will be equipped to reap the benefits of AI and to compete in the emerging trade scene.
For international trade, the trade models that are likely to be most useful in understanding the impact of AI are those that account for the points of scale, knowledge creation, and the geography of knowledge diffusion. These models suggest that whether AI-focused trade policies are optimal will depend very much on the presence of scale and the absence of rapid international knowledge diffusion.
VI. Meeting Overview
On 15 October 2018, the APPG AI community – made up of policymakers, industry, academics, and representatives of the wider society – met to discuss AI’s impact on trade. Co-chaired by Stephen Metcalfe and Lord Clement Jones, the group aimed to address how AI has changed trade in the UK and internationally – as well as how organisations can use AI to boost trade.
For industry to pick up on AI solutions and thrive in this transforming market arena, the panel and audience pinpointed a few areas government and regulators can assist. First, policymakers can help reduce perceived risk around adopting AI – particularly for small and mid-size companies. One of the largest barriers to AI adoption is the lack of trust in the ecosystem. Government can help build this trust, protecting organisations from some of the existing perceived risks. Second, government must incentivize public and private investment to help UK start ups scale. Third, policymakers must address critical data issues including privacy and explainability. Fourth, policymakers can help increase the understanding of AI technologies across UK sectors, industries, and regions. Only once the civic society understands AI and its use cases will they be able to adopt it successfully in their organisations.
First to speak was Dr. Mike Short, the Chief Scientific Advisor for the Department of International Trade. AI is key in today’s transactions, Dr. Mike Short argued, and it will be increasingly so in the future as AI will be used more and more in online transactions, automated and driverless cars, health, finance, and across all industries. The Department of International Trade is therefore making sure they support the adoption of AI domestically and overseas.
For AI to be adopted though, the government must increase access to data. “Organizations need access of data both nationally and internationally” Dr. Mike Short said, recommending that the policymakers address this urgent matter.
Dr. Matthew Howard, Deloitte’s Director of AI and Cognitive Analytics, agreed with Dr. Mike Short that access to data is key for UK businesses to operate and trade in the future. In addition, he added three main areas that UK policymakers must address to help businesses use AI in their day to day operations. First, he asked for a more proactive coordination plan between academia, business and government to bridge the existing skills gap. Second, he called for greater prioritisation of scalable pan-industry solutions for investment. And, lastly, thinking of a post Brexit UK, he urged for government to pass favourable policies for the flow of data, people, ideas and services amongst partners worldwide.
The third to speak was Andrew Burgess, AI advisor and author of the Executive Guide for AI. As AI has the potential to improve the lives for all and improve organisations across sectors and industries, stakeholders must ensure it is available easily and without restrictions. Andrew called for government to push for democratized AI – where access to create AI is easily available and delivers real value to society. For AI to work, he says: “AI will work best if it is a grassroot movement.”
One of the chief roles for government is to equip individuals with the right skills to reap the benefits of AI, Andrew argues. This means restructuring educations systems in classrooms and jobs.
The last speaker was Anna Dingley, Executive Director of industrial AI company SparkCognition. Addressing the question of how AI is changing trade nationally and internationally, she noted the transformations AI technologies are bringing for both developed and developing countries. Due to the economic potential of AI, AI can be adopted by all to increase efficiency, reach wider markets, and boost productivity.
She called for the UK to build taxing frameworks that can easily adapt to change. Regulation doesn’t have to stifle with innovation and we need consistent messages to be open to business.
Once the four panelists finished their oral evidence, Stephen Metcalfe MP and Lord Clement Jones opened the floor for questions and comments. In whole, the panel and audience agreed regulation can actually help companies adopt AI and ensure the full potential is tapped.
VII. Written Evidence
VIII. Annual General Meeting and Advisory Board Meeting Minutes
The Evidence Meeting followed the APPG AI Annual General Meeting and Advisory Board Meeting. Click here to download minutes.