Professor Gregory O'Hare:

I thank the Cathaoirleach. While artificial intelligence has garnered heightened interest in recent months, it is a technology that has existed for some considerable time. The origins can be traced back to none other than Alan Turing. In 1950, in a seminal paper entitled Computing Machinery and Intelligence, he postulated how to construct an intelligent machine and, significantly, how one might attest to the existence of such intelligence. The latter became known as the Turing test. The Dartmouth Summer Research Project on Artificial Intelligence conference, hosted by John McCarthy and Marvin Minsky five years later in 1956, was to become a key milestone. At this conference Allen Newell, Cliff Shaw and Herbert Simon presented their Logic Theorist computer programme, which sought to mimic human problem-solving. It is considered to be the first artificial intelligence programme.

Interestingly, the subsequent journey for artificial intelligence has witnessed twists and turns with many false dawns and unrealised promises counterbalanced by many landmark moments. I will provide exemplars of the latter. On 11 May 1997, IBM's Deep Blue defeated the reigning world chess champion, Garry Kasparov. On 8 October 2005, a Stanford-designed vehicle won the Defense Advanced Research Projects Agency's grand challenge of autonomously driving 211 kilometres across the desert. On 25 May 2017, Google's DeepMind AlphaGo defeated the world No. 1 ranked Go player, Ke Jie. On 12 October 2017, David Hanson's humanoid robot, Sophia, was granted citizenship of Saudi Arabia. On 30 Nov 2022, OpenAI released the open source generative AI tool, ChatGPT, where GPT stands for generative pre-trained transformer. On 27 and 28 March 2023, deep fakes of Donald Trump being arrested and Pope Francis in a white puffer jacket went viral. On 17 April 2023, Boris Eldagsen's AI generated work entitled "Pseudomnesia: The Electrician" won a Sony World Photography Award. On 18 April 2023, "Heart on My Sleeve", a generative AI track purported to be a collaboration between Canadian music superstars Drake and The Weeknd, was released online and went viral. On 1 May 2023, Geoffrey Hinton, the 2018 Turing Award winner and father of deep learning, resigned from Google to enable him to speak out freely about the risks of AI.

AI is a profoundly disruptive technology. History is strewn with examples of technological anxiety which accompanied key advances such as the wheel, the loom, the printing press, the combustion engine, the mobile phone, robotics, gene editing and now artificial intelligence. The latest generation of AI, generative AI as typified by ChatGPT, is underpinned by large language models, LLM, built and subsequently refined using both supervised learning and reinforcement learning with human feedback. While such models do not understand their inputs, they are nevertheless able to establish statistical patterns and learn correlations from data sets of unimaginable scale that enable them to generate content that exhibits contextual relevance and appropriateness.

ChatGPT is the fastest growing technology in history, having amassed more than 100 million users in two months. By way of comparison, the time taken to reach 100 million users by mobile phones was 16 years, iTunes six and a half years, Twitter five years, Facebook four and a half years, and TikTok nine months. Generative AI differentiates itself from previous AI offerings in that it originates content. Previous AI technologies typically inferred correlations, identified heuristics, provided recommendations, detected faults or performed diagnosis. These technologies resulted in automation and robotic deployments, typically addressing physical and assembly line tasks and predominantly displacing blue-collar workers, while assistive and advisory technologies typically complemented white-collar workers, enabling their performance of tasks to be faster and-or more accurate.

By contrast, generative AI is giving birth to new content and will have far-reaching effects on knowledge and white-collar workers. Professions such as journalism, media, the law, academia, marketing, architecture, engineering and the creative industries will all be profoundly affected. A recent Goldman Sachs report of March 2023 concluded that two thirds of US occupations will be impacted to some degree by AI-empowered automation and that generative AI could replace one fourth of all work-related tasks. Specifically, it predicts 44% of legal tasks being automated.

New businesses are already emerging. Examples include companies such as Anthropic, Deeper Insights, Stable Diffusion, Cohere and Stability AI. Such companies offer services by which to train generative AI on proprietary data sets generating new rich mixed-media content. A 2023 Littler report, which rather interestingly attributes ChatGPT as a co-author, points to the emergence of new roles, such as prompt engineers with skills to craft queries which will induce highly relevant and accurate responses from generative AI platforms.

AI in the workplace can manifest itself in a myriad of ways, including application screening, analysis and monitoring of facial expressions, eye contact, voice tone and cadence in video-recorded interviews, automation of tasks, monitoring engagement and biometric identification and classification. According to a 2023 OECD report, 49% of workers in finance and 39% in manufacturing said their company's application of AI collected data on them as individuals or how they perform their work.

Legislation is required. When passed, the EU's AI Act will seek to be the world’s first AI legislative framework. The Act is framed around input from the high level expert group of the EU on ethics guidelines for trustworthy AI.

It adopts several ethical principles, including respect for human autonomy, prevention of harm, fairness and explainability, the last of which demands system transparency, system auditability and system traceability. This will enable individuals to contest decisions of particular AI systems and seek redress as a result of such decisions.

The velocity of AI technology is, alas, fast exceeding the rate at which the law around AI can be framed.