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The AI cure for Baumol's cost disease

Updated: Mar 6

Image by Alan Warburton / © BBC / Better Images of AI / Medicine / CC-BY 4.0

A photographic rendering of medical swabs and pills in a jar seen through a refractive glass grid, overlaid with a diagram of a neural network.

Efficiency. It’s a value that is driving the investment and adoption of AI systems. The desire to automate is underpinned by an ideal of efficiency. Through more efficient processes we can drive down costs, scale and increase profits. We've seen this happen already for product manufacturing. But, for industries that have relied to a greater degree on people to deliver a service, we have not been able to drive the same kinds of efficiencies as we have in producing products.

William Baumol wrote about this decades ago in a paper that explained how the cost of a human intensive service - his example being a symphony orchestra - would continue to rise with no corresponding rise in productivity. The salaries of orchestra members (or healthcare workers, educators and other professional service providers) needed to keep pace with the rising labour market. This resulted in increasing costs to produce the same output, a problem that became known as Baumol’s cost disease. His work speaks to why costs in labour-intensive fields like healthcare and education (and the performing arts) have continued to increase and why these sectors face issues of affordability. Baumol passed away in 2017 and the Vox article that announced his passing stated:

“At least until we invent robotic professors, teachers, doctors, and nurses, we should expect these low-productivity sectors of the economy to get more expensive.”

Isn’t that what we are trying to do with AI right now? While calls for ChatGPT to become the robotic professor, teacher or doctor are overblown, in the longer run AI is being touted as the cure for Baumol’s cost disease by turning services into goods.

To cure Baumol’s cost disease, we would have to transform the industry’s professional human labor into something that can be manufactured, commoditized, industrialized, and automated…. AI creates a new opportunity: to transform services into goods.” - Vijay Pande, A16Z

Generative AI technology like ChatGPT can churn out a bigger piece of the work product outcomes of knowledge workers such as text, audio, video or code. As we productize services, we’ll see productivity gains, increased efficiencies and lower costs. AI uses optimization and speed to deliver these efficiencies. It provides a probabilistic assessment or prediction about an optimal choice as defined by the model. It does this fast and at scale. It's turning services into goods.

Clearly there are benefits to this approach. If we look at all of this through a set of business values, which also inform governments and not for profits, we might think of efficiency, optimization and speed only as positives. But when we put a bigger societal lens on these questions, there are clearly costs as well. I would love to see financial cost reductions as well as better access to a wide range of services including healthcare and education but not at the expense of breaking society. We need to think carefully about the impacts of this approach on humanity, not only through the lens of human labour. There are other important values we need to protect that don't involve optimizing for efficiency. In fact, they might be the antithesis of efficiency.

Human relationships are not efficient. They are often messy and problematic, time consuming and difficult. They are also the essence of our human connection, of joy and love - the things that make life worth living.

Canadian singer songwriter, Terra Lightfoot reminds us in her song No Hurry - that we LIKE to "waste" our time with <insert names of favourite humans here>!

There are human benefits in making less than optimal choices and by defining optimal in ways that aren’t just about being efficient. Perhaps spending/wasting time together with other human beings is just another way of expressing this thing we call LIFE.

Is there a middle ground here? I think there can be. The work I’m doing seeks to find the balance.

By Katrina Ingram, CEO, Ethically Aligned AI


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