In the Oscar-winning Little Miss Sunshine, the crucial Act One turning point hinges on the revelation that mother of the family Sheryl (played by Toni Collette) can only drive an automatic car, not a stick-shift VW camper. But her automatic isn’t big enough for the journey. So her husband (Greg Kinnear) is forced to drive them in the camper. Which means the rest of the extended family will also have to join them on the road trip to the California beauty pageant.
Sometimes, it turns out, it helps to know how to do things manually.
Gen AI and the automation tipping point
The rise of generative artificial intelligence is reshaping the debate between automation and manual processes. The explosion in use cases is taking us closer to an AI tipping point, and raising (sometimes controversial) questions about just how far down the automation road we should go.
My copywriting career was founded on promulgating automation. Many of my clients over the years have been technology companies. The sales pitch is simple and rational: using software to automate error-strewn manual processes would save firms money, improve outputs and free up staff to focus on more interesting, “higher-value” activities. A win-win.
But business automation, going back to the early days of the Industrial Revolution, has also brought losers. That was the price of progress. The Luddite fallacy, economists argue, is a mistaken belief that technological unemployment caused by the introduction of new technology will lead to higher overall joblessness. While rapid technological change may cause some short-term temporary unemployment, “economic theory suggests that jobs lost as a result of technological change will be created in different, new industries.”
That may be true in aggregate. Individuals though are not endlessly adaptable and mobile. Long-neglected, deindustrialised areas left behind by change breed angry, disillusioned citizens – as is all-too-evident in elections around the world this year.
Many white-collar workers haven’t faced the same fear of technological unemployment. Automation, and the loss of jobs that came with it, was some other industry’s problem. Now, with the rise of AI, it’s coming for us too – for the software engineers, the consultants, the call centre staff, the sales and marketers, the financial analysts, the writers.
What we lose with automation
Which highlights two issues businesses, politicians and society at large will at some point need to address. What might we lose in the process? And who are we doing it for?
Automation in many fields has brought, and will continue to bring, welcome benefits. Yet we need to maintain a human understanding of how those automated processes work if we are to fix issues when things go wrong – not least in an AI era.
As Yiannis Antoniou, Head of Data, AI, and Analytics at consultancy Lab49, argued: “Traceability — the ability to track and understand the data, processes, and decisions made by AI algorithms — is crucial in designing AI systems to course-correct after potential errors and fine-tune models for better long-term performance.”
If we outsource everything to a black-box machine, who will have the knowledge in a generation’s time? Some skills are worth holding on to. In the words of Arrested Development: “Give a man a fish and he’ll eat for a day, teach him how to fish and he’ll eat forever.”
Automation, but not too much?
With an aging population and shrinking workforce, progressive automation will be essential – as Japan is demonstrating. But there are no neat rules or clearcut boundaries for where and how much automation is needed.
Businesses want to maximise profits, so the cost and productivity benefits will incentivise ever greater automation. Staff, understandably, want jobs. Without being Marxian about it, you can see where those interests could come into progressive conflict. Today’s political turmoil, with the rise of populists on the right and left, is a reminder that the debate remains as alive now as it was two centuries ago.
Progress, and adaptation to it, are a feature of life. AI and other automation advances will continue. Embracing change is key to success. But we must be careful not to throw out crucial human skills in the process.
Where’s the line? Is there a line? Should there be a line?
That discussion will define the age.