Making the economics of worker displacement work for everyone

Below I model the economics of a worker displacement project that works for everyone. To combat inequality, the business and employee both share the project saving. I will show that by sharing the project saving both the business and former employee can end up with acceptable outcomes.

By worker displacement projects I mean any project where the employee loses his job. Automation and artificial intelligence projects are both worker displacement projects.

The model below is simple – this is a good thing.  A model like this is designed to provoke thought and hope in the reader.

I first assume an annual savings breakdown of the worker displacement project. We are displacing an employee that costs the business $40k. This includes tax that is not paid to the employee and any marginal expenses associated with employment.

I then assume a small maintenance cost increase for the business and a saving from efficiency improvements. All three of these net out at an annual saving of $50k for the business from this project.

If we decide to share this saving 50/50, the business ends up only saving $25k. This will double the project payback period.  As we expect automation or AI projects to have decent paybacks (i.e. 2 years or less) we would expect the new payback period to be at most 4 years.  This is still likely to be an acceptable use of capital. It depends on variables such as interest rates and alternative projects the company could finance.

The net financial impact for the employee is more complex than just the lost wages. We would also expect a small decrease in expenses that occur related to work. Our employee also receives a share of the saving from his old employer.

The net result is no financial impact for the employee from being displaced by a machine. The business is left with a project that while not as attractive as it could be, is still acceptable for many business as a use of capital.  Both sides end up with acceptable outcomes.

A key assumption here is the breakdown of the project savings. Technology will improve the ratio of maintenance costs to efficiency improvements. Efficiency improvements should increase as the projects enable more machine intelligence (rather than pure automation based on human heuristics).

We could also see reductions in machine maintenance costs. Alpha Go Zero showed an impressive decrease in computation costs over it’s previous iteration. It would be reasonable to expect that machine O&M costs will decrease over time.

The point of this analysis is not to show exactly zero net impact. It could be possible that the employee would need to accept a small decrease in net income.  Any impact needs to be offset against the non-financially quantifiable benefits and drawbacks that also occur when a worker is displaced.

It’s not clear whether the non-financial impacts would be be net positive or negative. Having more choice over how you spend your time might be offset by the lack of intellectual or social stimulation we get from our work today.

The specific mechanism for value sharing requires though.  The real mechanism for sharing the saving will be complex to implement in the real world. One mechanism would be a universal basic income funded by taxes on projects that displace workers.  This would most likely be a tax on the capital cost, as quantifying savings would be more challenging.

What I am trying to show is that it is possible to share value, rather than default to the business taking all of the value of the project and leaving the employee without any significant source of income.

The capitalist default of today is not acceptable due to the inequality it creates.

We must share the benefit of automation and machine intelligence throughout society.  The key to doing this is to balance between an acceptable return on capital on the business side with quality of life of society.

You can download the Excel spreadsheet here.