6 THE CAAR COMMUNICATOR derstand their workforce’s present and future needs, identify professional and skills development opportunities, and partner with employers and employees to future-proof their organizations in an evolving global economy. Headquartered in London, UK, Pearson also has offices in the US and Canada. We talked with Jonathan Finkelstein, founder of Credly and the Senior Vice President of Workforce Skills at Pearson. He explained what Gen AI is and how various sectors can use it. “Until recently, organizations mainly used artificial intelligence for statistical analysis, processing vast amounts of data and offering outputs that would have taken humans far more time and energy to complete,” noted Finkelstein. “The advancement of deep-learning models, which allow AI to classify text and images and transcribe audio automatically, has given rise to Gen AI. “Gen AI is a kind of artificial intelligence that— rather than analyzing or applying rules to data—produces something new: text, images, video, code, and other content,” he added. Deep-learning models trained on massive amounts of data power Gen AI’s outputs. The AI model “learns” to generate a statistically probable output based on reconciling the prompt it receives against the data it’s been fed. As Finkelstein explained to CAAR, Gen AI produces text relying on a large language model (LLM) trained on a high volume of text to develop patterns and probabilities of word choice and order concerning a given prompt. “Much like autocomplete on a smartphone, models like ChatGPT generate words one at a time (very quickly), with each subsequent word based on the previous one.” Models that produce code, images, and video also do so based on vast amounts of training data, influencing the outputs. “In this way, Gen AI produces a new work that shows traces of its training data,” said Finkelstein. “When you ask a Gen AI model like ChatGPT to write you a song about Wednesdays in the style of Dolly Parton, for instance, it will use its data about the genre of a song, the style of Dolly Parton, and social commentary about Wednesdays to write what it deems to be the most statistically probable text that satisfies your prompt’s parameters.” He said that Pearson believes Gen AI can positively impact how people understand and prepare for the changing world of work. AI’s surge forward in our personal and professional lives has changed our perception of what’s possible. It’s also changing the reality of what’s necessary in the world of work. Thanks to Gen AI, tasks that have long seemed inextricably intertwined with particular jobs are now being cast in a new light. “Our research (https://resources.credly.com/hubfs/ Pearson%20Skills%20Outlook%20(AI)%20-%20 Q4%202023/U.S..pdf) focused on how generative AI will affect roles such as farm product buyers by automating or significantly reducing the amount of time spent on daily tasks,” related Finkelstein. “Most generative AI models that have gained popularity are conversational AI chatbots, so rather than a “talking AI with a face,” these models use natural language processing to understand requests and questions and respond in writing.” Finkelstein said that these models have the potential to automate repetitive tasks in the agriculture sector, which will make quick work of responsibilities such as scheduling and documentation. Generative AI models trained on high-quality data can also offer data-driven insights and recommendations, allowing ag companies to work even more efficiently and use past experiences to inform projections like yield forecasts and product demand. He continued: “Our research anticipates that within blue-collar jobs, farm product buyers will experience the greatest impact of generative AI, based on the tasks associated with the role and AI’s ability to reduce the time spent on those tasks. “With the right data sets and prompts, a generative AI model can use past buying trends, current inventory, and projected demand insights to make product buyers’ work more efficient,” added Finkelstein. “By reducing the time spent on manual tasks like maintaining and reporting transaction and inventory data, generative AI will allow farm product buyers to use more of their uniquely human skills—communication and problem-solving, for instance.” With generative AI utilized as an accelerator for repetitive tasks, farm product buyers will now have more time to spend on higher-value work requiring additional skill sets. Pearson has developed data on AI. But where did it come from? For the “Gen AI Proof Jobs” installment of their Skills Outlook series, Pearson used a combination of census and other workforce datasets to form a comprehensive view of the current workforce across the US, UK, Australia, India, and Brazil. “Using our proprietary occupations ontology of GENERATIVE AI
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