Key Issues


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Artificial intelligence (AI), particularly machine learning, is spreading steadily and inexorably into business and industry. From financial services trading and modelling to the rise of autonomous vehicles, intelligent technology is being deployed to make life easier.

But people still have a critical role to play in directing, shaping and controlling these technologies. Only through detailed, complex and extensive human-led work can AI tools access the right data, generate the right outcomes and secure understanding and trust in the teams who use these tools.

Although the objective is often simplicity and automation, the adoption of AI is typically a front-loaded process. Significant investment of time and expertise is needed from the earliest design stages, all the way through to overseeing the curation of appropriate datasets, to build the best tools possible.

A versatile technology

The scope of AI use-cases is wide-ranging and ever growing. The technology can feed into every aspect of a business, from the customer interface to management tools, personalisation of products, advanced design, optimisation of processes to advanced predictive analytics. Artificial intelligence and machine learning technologies are starting to underpin and strengthen applications across the entire commercial and industrial landscape.

It's no surprise that AI is contributing to the coronavirus response on multiple fronts – searching for possible treatments, supporting vaccine development, mapping disease outbreaks, modelling how people move through spaces to optimise their design for social distancing.

Taking the lead in shaping legal responses

Our AI team is an early leader in this field, not least because our legal expertise is underpinned by technical understanding of the technology. Able to see through the hype and misconceptions, we add value for clients by analysing with clarity the legal issues and regulatory risks which our clients face in their AI projects.

We are also providing thought leadership for enterprise and public policy decision-makers in ways which are more than merely legal, and encompass the ethical questions arising from use of these technologies.

The legal questions raised by AI range widely.

Massive datasets are required to shape, train and direct AI towards the required outcomes. So it’s important for our clients to understand data licensing, data sharing, and data trust models as well as inherent data privacy challenges. The need to avoid overt and covert bias in AI-driven outcomes is ever present.

Compliance is also an on-going requirement. AI tools in regulated sectors, or which are generating regulated outcomes, need to be designed to be compliant. To be successful, regulatory expertise must be brought into the decision-making process from the outset and the use of "black box" algorithms and other opaque technologies needs to be handled with care.

Part of the legal challenge around this new technology is that it doesn’t sit easily in the current framework for intellectual property rights or data protection. Our management of the resulting exposures is driven by a knowledge of how such systems function. We understand the problems and provide our clients with initial advice to avoid the pitfalls, and we structure liability and contractual protections accordingly.

Finally, clients are investigating their many options in terms of AI infrastructure, tools, and training datasets. These can be built and curated in commercial partnerships, sourced ‘as a Service’ from AIaaS providers in the cloud or developed ‘on premise’ by specialist in-house technical teams. We help them decide on the right model for their business, deal with the legal arrangements for licensing across their enterprise, as well as providing clear frameworks for developing and integrating their chosen AI-driven systems in a compliant and efficient manner.