Artificial Intelligence

Artificial intelligence, AI, is a new user interface to the computer.  Large language models (LLMs) make the computer easier to use.  They permit us to describe the result that we want in natural language. improving productivity and enabling new applications.  AI will improve intellectual productivity as much as the internal combustion did for manual productivity.  In response to internal combustion, and more specifically the tractor,  we shortened the work week from 72 hours to 44 and invented vacations and retirement.  In the process, we killed off two generations of young men and still suffered 25% unemployment.  Said another way, increases in productivity are disruptive.  

The computer, with or without AI, is a tool.  Tools vary in quality, utility, usability, and use.  The user is responsible for the selection of the tool, the purpose to which it is put, and for all the properties of the result.  This is true whether the user is an individual or a group.  An enterprise must be responsible and accountable for everything that results from its application of this powerful technology. We call this security and we forget any part of it at our peril. We must not impute authority or autonomy to the tool; we must not anthropomorphize the tool.  "The craftsman does not blame his tools."  We must hold people accountable for how we use this powerful new tool.  

In the near term we should focus on embedded application specific implementations of AI.  We should follow the example of IBM, a pioneer in the field.  IBM trains the engine, think Watson, on application specific curated data; they build in governance and transparency from the ground up.

Public policy must soften the impact of the disruption.  This will include shortening the work week to spread the work and the leisure.  It should include a guaranteed minimum income to ease transition from old jobs and skills to new ones.  Finally, it should include changes in tax policy from labor to capital, people to robots, and production to consumption, to more securely and equitably finance the social safety net.  

"Women and Children First"

As we approach autonomous cars, some have posed the question "In accident avoidance should the car prefer its passenger or the pedestrian?"  It is posed as a difficult ethical dilemma.  I even heard an engineer suggest that not only does he not want to make the decision but that he would like Congress to make it as a matter of law.  

This is really just another instance of an ethical dilemma that humanity has faced forever.  It has many illustrations but one that has been used in teaching ethics is called the "life boat" problem.  If there is not enough room in the lifeboat for everyone, who gets in?  If there is not enough food and water, who gets preference?

The simple answer is "women and children first."  Human drivers will steer away from a woman with a baby carriage even if they do not have time to evaluate the alternative.  It is built into the culture, all but automatic, but the reason is that it is pro life.  Children are the future of the species.  Women can nurture and reproduce.  Men can sow but they cannot reap.  While the male role takes minutes, the female role takes months.  Life needs more females than males.

The reason that we do not apply this pro life rationale to the autonomous automobile is that we assume that the consideration is beyond its capability.  However, most of what one expects of an autonomous car today was beyond its capability a decade ago.  For the moment, most may not be able to consider all the factors we might like.  For example, they may not recognize age and gender, much less consider them.  Ten years from now, they certainly will.  

In this context it is useful to consider how such systems make a decision.  They identify a number of scenarios, depending upon the time available, assign an outcome and a confidence level to each, and choose statistically.  The kind of ties implied by the strawman dilemma will be vanishingly rare, even more so as the computers become faster and the number of things the can consider increases.  

Compare the autonomous car to the human driver.  In the two tenths of a second that it takes a young adult to recognize and react, the autonomous car will evaluate dozens of possibilities with as many considerations.  Like the human driver, the autonomous car may confront instances when there are simply no good options but the whole reason for using them is that they are less likely than the human driver to overlook the least damaging.