The enormous potential of artificial intelligence (AI) and machine learning systems has been much in the news lately with the development of chatbot ChatGPT.
ChatGPT is a free (for now) AI ‘chatbot’ which can be used to perform a wide variety of tasks, from researching and writing your company’s latest five point strategic plan, to writing papers and penning letters of appreciation. It even has the capability to mimic particular stylistic tics.
While in the early statges of development, its potential is clearly enormous, and observers have hailed it as one of the biggest technological advances since the invention of the computer or the internet. However, such a huge leap forward in technology has also caused considerable disquiet, given that OpenAI, the Microsoft-backed tech firm that created the software, claims that 80 % of the US workforce could have at least 10% of their work impacted by the technology.
Their research also found that 19% of workers could see as much as 50 per cent of their tasks impacted.
The study adds: “Our analysis indicates that the impacts of LLMs (large-language models) like GPT-4, are likely to be pervasive.”
In addition, researchers found that jobs with higher wages—which can involve the worker performing many software-based tasks—could face more exposure to potential disruption from AI-powered chatbots.
“We discover that roles heavily reliant on science and critical thinking skills show a negative correlation with exposure, while programming and writing skills are positively associated with LLM exposure,” the study says.
OpenAI researchers catalogued which professions could see the most disruption using various measurement rubrics. The most affected professions included interpreters and translators, poets, lyricists and creative writers, public relations specialists, writers and authors, mathematicians, blockchain engineers, accountants and auditors, along with journalists.
The paper also breaks down the ChatGPT impact by industry. Sectors including data processing hosting, publishing industries, and security commodity contracts, saw the most potential exposure to disruption. In contrast, industries known for manual labour—food services, forestry and logging, social assistance, and food manufacturing—saw the least potential impact.
Revolution in the world of work?
The research relating to ChatGPT comes after Microsoft co-founder Bill Gates warned that AI will radically change people’s lives as much as computers, the internet and mobile phones have already done. In a recent blog post, ge said he believes AI will revolutionise the world of work, learning, travel, healthcare, and communication.
Gates described how he was left amazed by ChatGPT after challenging OpenAI to train an artificial intelligence to pass an advanced biology exam last year: “I thought [that] would keep them busy for two or three years. They finished it in a few months,” Gates said. “I watched in awe as they asked GPT 60 multiple-choice questions from the AP Bio exam and it got 59 of them right.”
“Once it had aced the test, we asked it ‘What do you say to a father with a sick child?’ It wrote a thoughtful answer that was probably better than most of us in the room would have given. I knew I had just seen the most important advance in technology since the graphical user interface.”
Threat to underwriting?
Clearly certain professions, especially those which are predicated on research and the written word, will watch the development of ChatGPT with a keen and perhaps nervous interest. But, as we have noted previously, the advancement of AI will have multiple implications for the (re)insurance market. We leave you with a possible scenario postulated in a recent paper from McKinsey:
“In 2030, underwriting as we know it today ceases to exist for most personal and small-business products across life and property and casualty insurance. The process of underwriting is reduced to a few seconds as the majority of underwriting is automated and supported by a combination of machine and deep learning models built within the technology stack. These models are powered by internal data as well as a broad set of external data accessed through application programming interfaces and outside data and analytics providers. Information collected from devices provided by mainline carriers, reinsurers, product manufacturers, and product distributors is aggregated in a variety of data repositories and data streams. These information sources enable insurers to make ex ante decisions regarding underwriting and pricing, enabling proactive outreach with a bindable quote for a product bundle tailored to the buyer’s risk profile and coverage needs.”
The paper this research is taken from, titled An Early Look at the Labor Market Impact Potential of Large Language Models, can be found on the OpenAI website.