Nick McDonald, Senior Account Director at Fujitsu, says Generative AI presents many opportunities but organisations need to take a considered approach to how they leverage its potential.
The topic of AI is dominating the industry right now, but do we really understand what it is and the upsides – and downsides – it presents?
“Businesses understand that AI can have a seismic impact on all aspects of their operations, from internal processes and procedures to the solutions, tools, services and consumer experiences they provide. There’s an awareness that while AI brings many positives but there are also negatives to contend with, such as authenticity, reliability and security. This has dampened some of the initial hype and excitement and has left a lot of organisations nervous about AI and how they should approach the technology. Deepening the understanding of AI, and how to mitigate the risks it presents, will be key to helping organisations leverage its full potential.”
The term artificial intelligence is broad so what types of AI are most beneficial to online gambling operators and suppliers?
“You’re right. There are different types of AI, each with different use cases. This includes Narrow AI, General AI, Super AI, Reactive Machines, Limited Memory, Theory of Mind and Self-Awareness. The category of AI most businesses are interested in is Narrow AI, specifically Generative AI.
“Generative AI can create new data such as texts, images, videos and more. It does this by learning the structure and patterns of its training data to come up with new ideas with similar characteristics. It can be trained to understand human language, programming languages, art, chemistry, biology, law and countless other complex subjects. Large AI models, often referred to as foundation models, power Generative AI and can perform tasks like summarization, classification and answering queries. This makes it just as effective for a game designer as it is for a compliance specialist.”
When most people think of Generative AI, they think of ChatGPT. Is this the best example of Gen AI in action?
“Yes, ChatGPT is the most well-known example of Generative AI and stands as a good example of its capabilities. Its rise has been phenomenal, reaching 100 million users in just two months – a milestone that took Facebook almost five years to achieve. ChatGPT is a chatbot powered by large language models trained on huge amounts of data to produce texts that humans can understand. Users ask a question and ChatGPT breaks down the query into smaller components to analyse their meaning and to determine what the user is actually asking for. It then returns words and sentences it believes best answer the query, based on the data it has been trained on. ChatGPT has highlighted the benefits of Gen AI but it has also exposed some of its risks.”
What are the risks associated with Generative AI?
“There are a few but one of the most concerning is the accuracy and consistency of the outputs being generated. Other concerns include bias, a lack of explainability and even threats to security, privacy and intellectual property. As more people use ChatGPT more of its limitations are being revealed, especially those using it in a professional capacity. It’s important to remember that ChatGPT consumes information and data as well as shares it, so those inputting sensitive information are contributing to the data it is trained on and uses.
“Other users are also getting caught out by its hit-and-miss accuracy such as the lawyer who used ChatGPT to search for legal precedents for a document submitted to a judge. The judge then checked the legal precedents referred to in the document, only to find they didn’t exist. The judge put this to the lawyer who came clean about using ChatGPT and was ultimately struck off.”
Should examples such as this make organisations reconsider their use of Generative AI?
“Yes and no. It shouldn’t stop organisations from embracing Gen AI and the benefits it can bring to their operations, solutions, services and products. From enhancing game development to driving personalisation and even improving customer support and helping legal teams submit licence applications – there are plenty of use cases for Gen AI. What organisations need to consider is how they can integrate it and use it safely, securely and compliantly. And this is what we offer with our Private GPT, which works in the same way as ChatGPT but instead of using publicly available data, it sits on top of the company’s data warehouse.”
This sounds incredibly interesting. Tell us more.
“Because our Private GPT uses the company’s proprietary data, teams and employees can ask questions and queries and have answers generated based on the organisation’s own insights. The data can be siloed within the warehouse so that individuals and teams can be given specific levels of access – the marketing team doesn’t need to be able to ask questions of the same data sets as the CFO, for example. The use cases for a Private GPT are endless, too. This includes being able to ask questions, chat with company data, find new answers and insights and foster deeper collaboration between individuals, teams and the vast insights the company has. More importantly, it allows organisations to harness the capabilities of Gen AI safely and without any negative repercussions.”
Will products such as your Private GPT push Gen AI into the mainstream over the coming 12 months?
“I believe so. I think most organisations now understand the power and potential of AI, they just need the tools to be able to leverage it and our Private GPT has been developed to allow them to do just that.”
