In the 90’s when an Artificial Intelligence (AI) machine beat a chess world champion for the first time, it was an incredible achievement for machine intelligence. IBM’s “Big Blue” beat Gary Kasparov because chess is a game; it was able to crunch the data of a vast number of moves, having been programmed with the rules, it then performed calculations and worked out the best move to make at each turn beyond the capability of any human.
With the phenomenal rise of ChatGPT, a Natural Language Processing (NLP) AI tool by OpenAI (which gained more than 1 million users within 5 days of launching last December) a new star was born.
Interest in AI has now resulted in a heated debate about whether AI is a force for good or not
This is a live economic experiment of a magnitude that we’ve never seen before. 1.24 billion people are about to move into generative AI as Google releases AI-based products such as Med-PaLM, which performed better in medical exams than medical students, and Microsoft, thanks to its relationship with OpenAI, incorporates it into Office 365.
That’s what GPT-4, the language model, has done. It’s read everything on the internet and a huge amount of all the text that ever existed and it’s discerned deep, underlying patterns in the structure of language.
The next stage is Artificial General Intelligence (AGI), the representation of generalised human cognitive abilities in software so that, faced with an unfamiliar task, the AGI system can find a solution.
There will be many changes to the way we work. How do we navigate that over the next decade?
Generally, people will live longer, be more productive and have more per capita income. In the new digital age. There are clear investable journeys in every sense of the word. What does this mean to the individual?
Many people value the personal relationships they have with their financial advisors and estate planners. AI lacks the emotional intelligence and empathy that is essential in financial and estate planning. For example, AI can give general advice but cannot yet be specifically tailored to suit individual circumstances. If the data sets used to train AI contain inherent biases, such as gender or racial biases, this could lead to biased advice being given to clients.
There are further limits on many AI’s knowledge bases. Many AIs have knowledge bases that stop at a certain date.
There are also limits to an AI’s knowledge base. Most AI models are language models, meaning they do not have a numerical computation engine built into their programming. The model is able to generate human-like text based on patterns and examples which is why an AI like ChatGPT may be able to understand 2+2=4.
This is an incredible tool for human amplification
Until now, as we can see from the chess example, machine intelligence has been good at highly structured, domain specific tasks with a very clear set of rules and a procedural technique that can be applied. It’s very hard to make sense of what that means for knowledge workers. It’s the most deflationary event ever. So many human activities that have remained impervious to falling prices via technology such as financial advice, where specialist skills are required in order to tailor specific advice to the individual client.
It doesn’t have to be so rule bound and we don’t have to teach an AI machine the rules. That’s the big revolution that is machine learning – neural networks and, generally, transformer models that are fueling things like GPT-4 and are built on top of these neural networks where you can throw unstructured data at the AI model, tell it nothing about that data or the rules and it will look at it and draw rules of its own from complex, nuanced, submerged patterns existing within that data.
We have augmented humans, not by asking Google Search, but by asking a mentor
The computer doesn’t have imagination, and that’s where the human comes in. Humans are going to be smarter and have more longevity from the knowledge-based economy. Wearable devices will get humans closer to neural links. So, we will have health, longevity, intelligence, and robots.
We are on a journey now, though, that is much more flexible than those original chess playing days. We are moving from a world where the banks were organisations that were too big to fail. Now we are at a point where the computational power of computing AI is so far beyond that of human intelligence; a point where the average AI is something like 10,000 times more intelligent than the most intelligent human who has ever lived.
Financial advisors will need to work with AI, recognising that it can empower humans to be able to build their own sets and models that reflect their own values.
- Firms not developing AI capabilities have already begun incorporating AI into their services. JP Morgan, for example, reportedly used a Chat-GPT-based language AI model to analyse 25 years of Fed speeches.
- AI is forecasted to potentially increase global GDP by 7% and productivity growth by 1.5% over a decade according to Joseph Briggs, Economist at Goldman Sachs.
- A fictional investment fund generated by ChatGPT at finder.com outperformed the average of the UK’s 10 most popular funds.
From the consumer’s viewpoint right through from the customer of a retail bank to investment via a wealth management system, this is what they are asking for and the financial adviser very much has a value-added and values-based role to play in advising and guiding clients.
We are still in the early days of AI development
There’s a long road ahead, maybe 10 or 20 years. The flexibility of a portfolio of currencies and access to a variety of investment vehicles throughout the financial ecosystem, will provide greater stability for the individual during this transformative era, the biggest revolution after the invention of the Gutenberg printing press, the steam engine, and the internet.
Jesse Pitts has been with the Global Banking & Finance Review since 2016, serving in various capacities, including Graphic Designer, Content Publisher, and Editorial Assistant. As the sole graphic designer for the company, Jesse plays a crucial role in shaping the visual identity of Global Banking & Finance Review. Additionally, Jesse manages the publishing of content across multiple platforms, including Global Banking & Finance Review, Asset Digest, Biz Dispatch, Blockchain Tribune, Business Express, Brands Journal, Companies Digest, Economy Standard, Entrepreneur Tribune, Finance Digest, Fintech Herald, Global Islamic Finance Magazine, International Releases, Online World News, Luxury Adviser, Palmbay Herald, Startup Observer, Technology Dispatch, Trading Herald, and Wealth Tribune.