Recent advancements in artificial intelligence e.g. ChatGPT and the introduction of Google's Bard chatbot, brings with it various possibilities across all different sectors.
By 2030, it is predicted that the number of cashiers in the retail sector could halve, as self-checkouts and self-scanning become more prominent in the retail sector. Retailers are currently experimenting with AI powered systems to spot gaps on shelves, pick and pack products, and automate price changes on shelves.
In the Energy industry, AI has the potential to predict and identify faults at power plants, use weather forecasts to identify locations of offshore windfarms and track carbon emissions of companies for sustainability planning.
Experts envisage the financial services sector will be the most susceptible to disruption from AI. Machines could have the potential to run customer background checks as part of the onboarding process for new clients, as well as update learning programmes with new regulatory guidelines to flag potential breaches or shortfalls in a company's system.
So how does AI impact legal risk?
If the use of AI is increasing, it is important to understand whether legislation is keeping up with the pace. Some associated risks to be considered before introducing AI into a business may include:
- 1. Liability. Whilst AI looks to streamline processes, remove human-error and predict issues, it is safe to say that AI will not be error-proof and therefore when considering legal persons/personalities in relation to how legal elements such as liability are dealt with, AI itself cannot be attributable. It is therefore important to consider what elements of liability need to be attributable to which parties in a supply chain e.g. is it the AI developer of the AI user who is liable?
- 2. Intellectual Property. Using AI-produced output requires careful analysis of the datasets used to teach the system to ensure that companies do not open themselves up to third party infringement claims. For example, where system owners seek to rely on copyright exemptions to acquire datasets free of charge, the application of such exemptions is not uniform across the world and copyright creators have been vocal in challenging the legality of relying on those exemptions in the first place. On the other hand, it is not clear how and to what extent AI-generated output can be protected, which means that companies may not be able to prevent others from using the output.
- 3. Competition/Antitrust Issues. Whilst it is widely recognised that AI increases competition through the use of algorithms, such as helping consumers find the lowest prices, there are concerns that such algorithms can also make price-fixing more effective – such parallel behaviour may not be with intention, but purely as a result of using AI in the first place.
- 4. Data Privacy. AI tools involve processing a vast amount of data, some of which could be personal data. This raises concerns in relation to identification from such data – whether through analysis or the use of AI itself to de-anonymise anonymised data.
So where is the law currently in terms of considering these risks?
On the one hand, the UK government published a white paper on 29 March 2023 "to guide the use of artificial intelligence in the UK, to drive responsible innovation and maintain public trust in this revolutionary technology" and have said they want to "avoid heavy-handed legislation which could stifle innovation". The white paper outlines 5 principles that regulators should consider to best facilitate the safe and innovative use of AI in specific industries:
- Safety, security and robustness: applications of AI should function in a secure, safe and robust way where risks are carefully managed;
- Transparency and explainability: organisations developing and deploying AI should be able to communicate when and how it is used and explain a system’s decision-making process in an appropriate level of detail that matches the risks posed by the use of AI;
- Fairness: AI should be used in a way which complies with the UK’s existing laws, for example the Equality Act 2010 or UK GDPR, and must not discriminate against individuals or create unfair commercial outcomes;
- Accountability and governance: measures are needed to ensure there is appropriate oversight of the way AI is being used and clear accountability for the outcomes;
- Contestability and redress: people need to have clear routes to dispute harmful outcomes or decisions generated by AI [1].
On the other hand, the European Commission has proposed legislation in the form of the Artificial Intelligence Act (the "Act"), to govern the development, marketing and use of AI in the EU. The Act will aim to manage AI applications using risk categories whilst aiming to work with current GDPR to "boost research and industrial capacity while ensuring safety and fundamental rights" [2]. Unlike the UK's more innovative approach, the Act will impose different legislative obligations at all stages development and use of an AI system.
With such accelerated developments in AI, it is difficult to predict whether the differing approaches by the UK and EU will have their desired impact, as well as seeing how innovation in the space deals with such a divergent legislative landscape.