The Use of AI in Economics and the Legal Concerns

Sevin Karabulut


In my previous blog, Using AI to Forecast Economic Data, I took an optimistic view of how AI could be used by economists, policymakers, and businesses as an effective tool to generate precise economic data, which could be applied in a myriad of industries. While I certainly believe AI is highly advantageous for the reasons I mentioned, what particularly interests me is the legalities, or lack thereof, concerned with AI. This is because AI used to be merely a theoretical concept just twenty years ago, and yet over the past few years, its progress has been dangerously rapid with many businesses becoming reliant on it with little to no regulation in place.

My interest in this topic began after Mark O’Conor, a partner and global co-chair for the technology sector at the law firm DLA Piper, was a guest speaker in one of my lectures and made a presentation on a report from DLA Piper; “AI governance: Balancing policy, compliance and commercial value” (DLA Piper, 2023). More recently, after speaking to him at an event earlier this month, he gave me the idea to write about AI in economic forecasting for a blog. Therefore, for this blog, I will refer to the findings from the report to discuss the use of AI in economics and the legal issues concerned with this.

Liability: Who’s Responsible for AI Errors?

The DLA Piper report reveals that 72% of corporations are currently using AI programmes, thus as businesses and policymakers increasingly rely on AI, for important tasks, such as economic forecasting, the question of liability for errors is becoming a critical legal and ethical issue (DLA Piper, 2023). Given that an AI program generates inaccurate or biased forecasts, businesses and policymakers that rely on this data could experience substantial financial losses, and this begs the question: who is responsible? Let’s consider a realistic scenario: a business that relies on AI for certain operations faces a costly error, the stakeholders are the AI users, their managers, employers, and the AI developers themselves. Exploring the first layer of accountability presents us with the AI users themselves. Here, users in business settings must understand the limitations of the AI and maintain oversight over the work generated. Moving onto the managers, managers must ensure that teams are adequately trained to use the AI program as well as monitor the use of it. Lastly, AI developers, like OpenAI, hold the largest level of responsibility as they must ensure that the AI is designed and trained effectively, without bias, and with safety measures.

Under current laws, liability hinges on how the AI program was used; that is whether the negligence lies within its design or deployment. For example, the EU’s Artificial Intelligence Act, the first comprehensive regulation by a major regulator, assigns AI to three risk categories. These risk categories are unacceptable risk, high-risk, and other applications that are not risky are left unregulated. The act also establishes that vendors must demonstrate due diligence in developing and testing AI programs. However, while this act does provide guidelines, it does not include liability, and thus the effectiveness is ultimately restricted.

Governance of AI and its Economic Implications

While I do believe that some regulation for AI is crucial, it is still important to consider the economic implications that excessive regulation could result in. One key concern is that excessive regulation in western countries could cause stifles in competition. Currently, the US, China, and the UK are among the leading countries in terms of AI power and innovation. The US and the UK are taking a regulatory, but flexible, approach to AI, to encourage growth and innovation while maintaining control. Meanwhile, China has heavily subsidised the AI sector. For example, China has the Artificial Intelligence Industry Alliance (AIIA), and its sole purpose is to promote rapid growth in the Chinese AI industry. Works from the AIIA is demonstrated when Chinese AI company, iDeepWise, received $75,400 in cash and $3 million in subsidies over three years after they won an AIIA competition in 2018 (CSET, 2021). These are not substantial sums in terms of investment for AI, however it is still crucial to note how they do ultimately help start-up companies. Moreover, this is just a microscopic example of how the Chinese government are subsidising and helping private firms.

Alternatively, if Western countries impose excessive regulations, it could strain innovation, giving other corporations with more resources abroad an advantage. This is because if only a limited number of companies can afford to meet regulatory standards, and other companies abroad are receiving subsidies with little to no regulation foreseeable, it may result in them dominating the market. This could effectively create an AI monopoly. More importantly, having a single nation or small group of companies dominate the AI industry results to concerns around data privacy and political influence globally. This concern is demonstrated within the social media market, shown through the popular Chinese social media platform TikTok as it has faced intense scrutiny over data privacy issues.

The following blog will continue to explore the idea around the ethics and issues in the monopolisation of AI, as well as how there is a disruption in the market due to the large subsidies given to Chinese companies as opposed to the lack of in Western countries.

References

DLA Piper. (2023) AI governance: Balancing policy, compliance, and commercial value. Available at: https://www.dlapiper.com/en-gb/insights/publications/2023/09/ai-governance-balancing-policy-compliance-and-commercial-value (Accessed: 30 October 2024).

CSET. (2021) In (and out of) China: Financial support for AI development. Available at: https://cset.georgetown.edu/article/in-out-of-china-financial-support-for-ai-development/ (Accessed: 30 October 2024).


About the author

Sevin is a Business with Law student in her second year. With an interest in law, economics, and business operations, she will aim to explore ways the law influences economic policies and current affairs.

Contact details for any questions or collaboration: bs23254@qmul.ac.uk

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