For decades, artificial intelligence, or AI, was the engine of high-level STEM research. Most consumers became aware of the technology’s power and potential through internet platforms like Google and Facebook, and retailer Amazon. Today, AI is essential across a vast array of industries, including health care, banking, retail, and manufacturing.
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But its game-changing promise to do things like improve efficiency, bring down costs, and accelerate research and development has been tempered of late with worries that these complex, opaque systems may do more societal harm than economic good. With virtually no U.S. government oversight, private companies use AI software to make determinations about health and medicine, employment, creditworthiness, and even criminal justice without having to answer for how they’re ensuring that programs aren’t encoded, consciously or unconsciously, with structural biases.
Its growing appeal and utility are undeniable. Worldwide business spending on AI is expected to hit $50 billion this year and $110 billion annually by 2024, even after the global economic slump caused by the COVID-19 pandemic, according to a forecast released in August by technology research firm IDC. Retail and banking industries spent the most this year, at more than $5 billion each. The company expects the media industry and federal and central governments will invest most heavily between 2018 and 2023 and predicts that AI will be “the disrupting influence changing entire industries over the next decade.”
“Virtually every big company now has multiple AI systems and counts the deployment of AI as integral to their strategy,” said Joseph Fuller, professor of management practice at Harvard Business School, who co-leads Managing the Future of Work, a research project that studies, in part, the development and implementation of AI, including machine learning, robotics, sensors, and industrial automation, in business and the work world.
Early on, it was popularly assumed that the future of AI would involve the automation of simple repetitive tasks requiring low-level decision-making. But AI has rapidly grown in sophistication, owing to more powerful computers and the compilation of huge data sets. One branch, machine learning, notable for its ability to sort and analyze massive amounts of data and to learn over time, has transformed countless fields, including education.
Firms now use AI to manage sourcing of materials and products from suppliers and to integrate vast troves of information to aid in strategic decision-making, and because of its capacity to process data so quickly, AI tools are helping to minimize time in the pricey trial-and-error of product development — a critical advance for an industry like pharmaceuticals, where it costs $1 billion to bring a new pill to market, Fuller said.
Health care experts see many possible uses for AI, including with billing and processing necessary paperwork. And medical professionals expect that the biggest, most immediate impact will be in analysis of data, imaging, and diagnosis. Imagine, they say, having the ability to bring all of the medical knowledge available on a disease to any given treatment decision.
In employment, AI software culls and processes resumes and analyzes job interviewees’ voice and facial expressions in hiring and driving the growth of what’s known as “hybrid” jobs. Rather than replacing employees, AI takes on important technical tasks of their work, like routing for package delivery trucks, which potentially frees workers to focus on other responsibilities, making them more productive and therefore more valuable to employers.
“It’s allowing them to do more stuff better, or to make fewer errors, or to capture their expertise and disseminate it more effectively in the organization,” said Fuller, who has studied the effects and attitudes of workers who have lost or are likeliest to lose their jobs to AI.