Developing countries may need their own strategies to cope with job-taking robots
Governments could constrain automation through policy measures such as disincentivization — by, say, taxing the use of robots — or reducing the cost of human labor through tax breaks or cutting minimum wages.
The problem is that disincentivizing automation could just push it into other nations. Developing countries are likely to feel unable to implement those kinds of constraints, for fear of companies or even entire sectors relocating to regions where the use of robots isn’t penalized.
Mr. Schlogl told DealBook the impact of automation could be felt acutely by sectors that are labor-intensive in developing countries, irrespective of where robots are put to use. Cheap goods can be built by machines in one location and distributed worldwide; a single country could mechanize agriculture and flood a subcontinent with affordable produce.
As for cutting labor costs, it’s unclear exactly how much lower wages can get in many developing countries before they become unethical.
The second way for governments to cope with the disruption caused by automation is to implement strategies that deal with the effects. That includes retraining workers to give them skills required for future jobs, or providing citizens with a basic income to make up for stagnant wages or job losses.
Retraining would be hard to implement in developing nations, argue Mr. Schlogl and Mr. Sumner, because they typically have limited education sectors in place through which to deliver it. And a universal basic income, they argue, would be hard to finance in developing countries, as it assumes the existence of a highly productive services sector from which to siphon money, which is often missing in such economies.
There are some potential routes forward. One idea suggested by Mr. Schlogl and Mr. Sumner is a so-called global universal basic income — administered internationally, and paid for in developing countries via aid. This plan, says Mr. Schlogl, ”has the advantage of being only politically impossible.”
Another might be for developing countries to build out labor-intensive sectors that look set to be resistant to automation over the coming decades — such as social care, education, health care, tourism or infrastructure construction. But this is a risky approach, requiring large upfront investment without a guarantee of protection from automation in the long-term.
That makes the pair’s ultimate conclusion — that ”we need to ask different policy and research questions” about how automation will affect the developing world — seem justifiable.