Someone reminded me recently that 2024 is the thirtieth anniversary of the triple bottom line, dating back to an essay I did for the California Management Review on “win-win-win” solutions. Within a few years, we saw a number of defining corporate controversies helping to crystallise the new change agenda, among them Shell in the oil sector and Nike in sportswear. I was closely involved in both, as both an outsider and insider.
Now, in what may prove to be a defining moment for the rapidly emerging AI world, Elon Musk has filed suit against OpenAI and its CEO, Sam Altman, accusing them of betraying the firm’s founding mission by developing AI for profit rather than the for the wider benefit of humanity.
In a key passage, the lawsuit alleges that, “OpenAI Inc has been transformed into a closed source, de facto subsidiary of the largest technology company in the world: Microsoft. Under its new board, it is not just developing but is actually refining an AGI [artificial general intelligence] to maximize profits for Microsoft, rather than for the benefit of humanity.”
Although he was a founding board member of OpenAI, the company behind ChatGPT, Musk has long argued that AGI represents “a grave threat to humanity.”
One way to look at this spat between AI pioneers is to recall the media hype about a possible “cage fight” between Musk and Facebook founder Mark Zuckerberg. But another is to look at it through the lens of the emerging science oil cliodynamics.
As described by Daniel Hoyer, an historian and complexity scientist at the University of Toronto, cliodynamics aims to treat history as “a natural science, using statistical methods, computational simulations and other tools adapted from evolutionary theory, physics and complexity science to understand why things happened the way that they did.”
Over the decades, I have often quoted Mark Twain’s insight that “history doesn't repeat itself, but it often rhymes.” And in my own work since 1994 on societal change waves I have explored how such repeating patterns impact both present and future realities.
Cliodynamics suggests that one of the most common patterns is the emergence of extreme inequality in nearly all the major crises studied. And one repeating feature of such periods in history is for such inequalities to have corrosive effects not just between elites and wider societies, but within the elites themselves. “The accumulation of so much wealth and power,” Hoyer suggests, “leads to intense infighting between them, which ripples throughout society.”
In an age of “polycrisis,” it is worth asking whether apparently ridiculous invitations to “cage fights” are just high jinks between high-testosterone innovators and entrepreneurs, or whether they represent the strengthening of darker currents in our societies.
In this “super year” for democratic elections worldwide, at time of what has been dubbed a global “democracy recession,” it is hard not to see another recurrent (and malign) historical pattern at work.
As Hoyer notes, “One of the really common historical pattern is that as people accumulate wealth, they generally seek to translate this into other forms of ‘social power’: political office, positions at top firms, military or religious leadership. Really, whatever is valued most at that time in their specific society.” He references Boris Johnson’s honors list as a very British case in point, with privileges circulated among a narrow group of corrupt—and corrupting—people who had stumbled into power for a brief moment of historical time.
When it comes to Donald Trump, Hoyer sees him as “only one recent and fairly extreme version of this motif that pops up time and again during ages of discord. and if something isn’t done to relieve the pressure of such competition then these frustrated elites can find masses of supporters. Then the pressures continue to build, ignoring anger and frustration within more and more people, until it requires some release, usually in the form of violent conflict.”
Whatever your reading of all this may be, and however the Musk vs. court battle turns out, it is increasingly clear that we live in consequential times. And the outcome will also give us a useful sense of whether triple bottom line thinking can come to permeate the AI world, or not.