Event round-up - Future Visions: ChatGPT
techUK recently hosted the next event in its Future Visions series - The series explores the next-generation technologies at the cutting edge of research and development that are set to disrupt industries, challenge incumbents, and act as a catalyst for growth. It offers the opportunity to learn about the latest advances in technology from those at the heart of its development, and what this might mean for your business.
The industry briefing below covers key aspects of ChatGPT including the numerous questions that have been arising from its uses. Questions are related to ChatGPT’s uses within business operations, its relation to human decision-making, and how future regulation and Government policymaking may shape the technology’s varying use-cases.
The session’s speakers included;
- Darren Fleetwood, Head of Data and Analytics at Madano
- Katherine Holden, Head of Data Analytics, AI and Digital ID at techUK
- Bea Longworth, Government Affairs EMEA at NVIDIA
- Hugh Milward, General Manager, Corporate, External and Legal Affairs at Microsoft UK
- Lewis Wood, Algorithm Developer at MeVitae
View recording here:
The briefing’s key themes included:
Specifying definitions and use-cases
The first challenge exists within defining and comprehending generative AI’s technical meaning, and its possible/future use-cases;
- ChatGPT is understood to be a natural language processing tool driven by AI technology that enables users to develop human-like conversations with the bot’s knowledge production. Built via OpenAI's GPT-3.5 and GPT-4 large language models (LLMs), the tool has been fine-tuned (via transferring knowledge) using both supervised and reinforcement learning techniques.
- The technology will not replace human decision-making, rather – the tool will be used to evolve more accurate and rational behaviour within various tasks, including academics’ literature review research, and briefing document writing. As such, this unlocks human intelligence, freeing up time for strategy and ideational thinking within the business and/or research proces
Generative AI’s capabilities and limitations
The technology’s various uses-cases have resulted in ground-breaking transformations in ways of working across business and academia;
- Within HR/hiring processes, the tool has been generating job descriptions, CVs, and streamlining hiring managers’ decision-making.
- The technology’s application also requires important considerations to inherent biases, particularly within business operations including recruitment and HR proceedings. This also includes the tool’s generated association with specific social groups and negative/harmful stereotypes, which requires methods of de-biasing angular models and datasets.
- The tool’s application in upskilling remains a key success story, enabling technical specialists’ to learn new skills in coding within an easily accessible and highly responsive manner.
Generative AI’s short-term/long-term impact on society and economy
Ensuring businesses and researchers develop new innovative solutions and capabilities which consider the positive impacts of the tool;
- The tool can be used and further developed to produce highly complex and sophisticated operations to tackle wider societal issues including climate change, for example – integrating determinations of required infrastructure via heat-map analysis of high-areas of flooding and earthquakes.
- Complementing and enhancing the responsibilities within entry-level roles.
- Possible solutions/considerations to bad actors obtaining access and usage of the technology, ensuring responsibility of relevant organisations and technical users develop the tool in the most ethical and accurate way possible.
- Changes to attitudes and norms may enable further societal adoption of the technology, altering citizens’ expectations of direct human interaction within specific scenarios – including charity call-centres’ communication via AI-developed tools including ChatGPT.
Considerations for future legislation and regulation
The central challenge exists to understand pre-existing policymaking structures, standards, and regulations, which can be applied to generative AI – while ensuring rules-making enables innovation across its varying use-cases;
- Institutions and Government must determine future policymaking frameworks that give clear, accurate guidance on model end development and use-cases’ effects businesses and wider society.
- Guidance and education for both developers and consumers, ensuring best practice and correct use are clearly marked in order for businesses and end-users to manage risks involve.
- Policymakers ensuring innovative and creative ways of regulation, including ideas for potential watermarking of generative AI developed content, ensuring accountability and visibility.
Click below to view our other Supercharging Innovation series:
Click below to view our other Unleashing Innovation series:
