What the birth of the spreadsheet teaches us about generative AI

What the birth of the spreadsheet teaches us about generative AI 7th March, 2024

When the spreadsheet launched in 1979, it was a bewildering piece of software. People had no idea what they were looking at. A computer screen, filled with a grid of numbers? As Keith Houston explains in his new history of the pocket calculator, Empire of the Sum, they hadn’t realised that the rows and columns of a spreadsheet could be functional rather than decorative. Accustomed to writing numbers by hand on an 11-by-17 inch sheet of gridded paper designed for accountancy, they would type the same numbers into the computer grid and then do what they had done for the past couple of decades: figure out the sums with a calculator.

This posed quite the problem to Dan Bricklin, the inventor of the digital spreadsheet, and his colleagues Bob Frankston and Dan Fylstra. When Frankston presented their product, “VisiCalc”, at the National Computer Conference in 1979, the audience consisted almost entirely of friends and associates. Frankston counted only two strangers in the audience, both of whom left before the end.

Last week, I argued that for a glimpse at the future of generative AI, we should look for parallels in older technologies. By examining several earlier innovations, we can get some idea of the opportunities and the dangers ahead. This time, I want to examine Bricklin’s brainchild, the digital spreadsheet.

Despite its stuttering beginning, VisiCalc quickly became a phenomenon. Watching those two strangers walk out of his presentation in 1979, Bob Frankston could hardly have dared to hope that, three years later, Apple II computers were being sold as “VisiCalc accessories” — the $2,000 entry fee to get access to the spreadsheet, a $100 miracle. Unsurprisingly, it was the accountants who caught on first and drove demand.

Bricklin recalled in a 1989 interview with Byte magazine, “if you showed it to a person who had to do financial work with real spreadsheets, he’d start shaking and say, ‘I spent all week doing that.’ Then he’d shove his charge cards in your face.”

There is one very clear parallel between the digital spreadsheet and generative AI: both are computer apps that collapse time. A task that might have taken hours or days can suddenly be completed in seconds. So accept for a moment the premise that the digital spreadsheet has something to teach us about generative AI. What lessons should we absorb?

First, the right technology in the right place can take over very quickly indeed. In the time it takes to qualify as a chartered accountant, digital spreadsheets laid waste to a substantial industry of cognitive labour, of filling in rows and columns, pulling out electronic calculators and punching in the numbers. Accounting clerks became surplus to requirements, and the ability of a single worker to perform arithmetic was multiplied a thousandfold — and soon a millionfold — almost overnight.

The second lesson is that the effect on the labour market was not what we might have expected. The Bureau of Labor Statistics estimated that there were 339,000 accountants and accounting clerks working in the US in 1980, around the time VisiCalc started to take off. By 2022, the bureau tallied 1.4mn accountants and auditors. These two numbers aren’t directly comparable, but it is hard to argue that accountancy was decimated by the spreadsheet. Instead, there are more accountants than ever; they are merely outsourcing the arithmetic to the machine.

The spreadsheet also illuminates something we don’t yet know about generative AI — will it favour the underdog or the top dog? Will it reshape jobs to make them more interesting, or will it leave humans with the tedious tasks?

The digital spreadsheet is an example of a technology that automated the more tedious tasks in accountancy, burnishing jobs that were already well-paid and interesting. It may be that generative AI does something similar on a grander scale, letting the humans deal with the big creative questions while the machine handles the nagging details.

Generative AI has been tried in a variety of workplace experiments, for example, helping online tech-support workers troubleshoot customer problems. Early trials strongly suggest that the latest chatbots add to everyone’s productivity, but particularly to the productivity of the least skilled staff. That is encouraging, even if the current pace of change makes it too early to be entirely confident about the next step.

It’s that pace of change that gives me pause. Ethan Mollick, author of the forthcoming book Co-Intelligence, tells me “if progress on generative AI stops now, the spreadsheet is not a bad analogy”. We’d get some dramatic shifts in the workplace, a technology that broadly empowers workers and creates good new jobs, and everything would be fine. But is it going to stop any time soon? Mollick doubts that, and so do I.

Looking at the way spreadsheets are used today certainly suggests a warning. They are endlessly misused by people who are not accountants and are not using the careful error-checking protocols built into accountancy for centuries. Famous economists using Excel simply failed to select the right cells for analysis. An investment bank used the wrong formula in a risk calculation, accidentally doubling the level of allowable risk-taking. Biologists have been typing the names of genes, only to have Excel autocorrect those names into dates.

When a tool is ubiquitous, and convenient, we kludge our way through without really understanding what the tool is doing or why. And that, as a parallel for generative AI, is alarmingly on the nose.

Written for and first published in the Financial Times on 9 February 2024.

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