• Deborah

Put simply, Artificial Intelligence (AI) leverages computers and machines to mimic the problem-solving and decision-making capabilities of the human mind. Well, in practice it is ‘a bit’ more complicated than that…


Alan Turing, considered as the founding father of AI, defines it as “the science and engineering of making intelligent machines, especially intelligent computer programs.”


The UK Information Commissioner (ICO) defines AIas an umbrella term for a range of algorithm-based technologies that solve complex tasks by carrying out functions that previously required human thinking. Decisions made using AI are either fully automated, or with a ‘human in the loop. As with any other form of decision-making, those impacted by an AI supported decision should be able to hold someone accountable for it.’


An AI technology combines and utilises mainly machine learning (ML) and other types of data analytics methods to achieve artificial intelligence capabilities.

AI can have many uses including

  • In asset management to improve portfolio management, trading, and risk management practices by increasing efficiency, accuracy, and compliance

  • In policing to target interventions

  • In healthcare to detect early signs of illness and diagnose disease

  • In marketing to target products and services to consumers

Although AI can pose a risk to data privacy considering the amount of personal data organizations have to process to meet their business needs. Thus, Policy makers and regulators around the globe are increasingly imposing certain limits (e.g., Bill 64 in Quebec or GDRP in the EU).


Want to know more about AI and what are the implications for your organization? Have a look at the UK Information Commissioner’s (ICO) Guidance on AI and Data Protection that outlines best practices for data protection-compliant AI, and provides ICO’s interpretation of data protection law as it applies to AI systems that process personal data. The Guidance also includes a toolkit providing practical support to organisations auditing the compliance of their own AI systems.


You can also read our article on this Guidance.


The Guidance will be of interest for those with a compliance focus (e.g., data protection officers (DPOs), general counsel, risk managers, senior management) and technology specialists, including machine learning experts, data scientists, software developers and engineers, and cybersecurity and IT risk managers.


We also recommend the International Organization of Securities Commissions’ (IOSCO) Final Report providing guidance to its members on the regulation and supervision of the use of AI & ML by market intermediaries and asset managers. We also write about it here


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