In a 1938 article, MIT’s president argued that technical progress didn’t mean fewer jobs. He’s still right.

In a 1938 article, MIT’s president argued that technical progress didn’t mean fewer jobs. He’s still right.

Compton drew a sharp distinction between the consequences of technological progress on “industry as a whole” and the effects, often painful, on individuals.

For “industry as a whole,” he concluded, “technological unemployment is a myth.” That’s because, he argued, technology "has created so many new industries” and has expanded the market for many items by “lowering the cost of production to make a price within reach of large masses of purchasers.” In short, technological advances had created more jobs overall. The argument—and the question of whether it is still true—remains pertinent in the age of AI.

Then Compton abruptly switched perspectives, acknowledging that for some workers and communities, “technological unemployment may be a very serious social problem, as in a town whose mill has had to shut down, or in a craft which has been superseded by a new art.”

  • @WombleOPEnglish
    2•10 months ago

    Humans were the best at weaving until looms came along, humans were the best at welding components together until industrial robots came along. Humans were the best at doing double entry accounting until digital computers came along.

    I just don’t see this current wave of AI of being any different than previous technological advances that became tools better at specific tasks than humans.

    This is one-way, hunans don’t win back ground.

    No they dont they open up new gound as technology increases the range of the possible, as the article talks about

    One critical wild card is how many new jobs will be created by AI even as existing ones disappear. Estimating such job creation is notoriously difficult. But MIT’s David Autor and his collaborators recently calculated that 60% of employment in 2018 was in types of jobs that didn’t exist before 1940.

    • @tabularEnglish
      1•10 months ago

      When you know the goal but do not know how to functionally get there then an artificial neural network can be useful. To get Chinese Go artificial opponent working was done by making the program run many games against many iterations of itself to adjust itself towards the correct moves for any situation. The biggest difference is the scope of problems this type of tool is capable of solving.

      Technology creating more jobs in the industrial revolution isn’t a valid argument that automating intelligence will create more jobs. Even if we grant that it does, are you assuming that it will create more jobs that it nullifies forever? If we can agree there’s a point where it stops being positive then we just disagree on the time it will happen.

      If we assume jobs are created and they too complex to be suitable for the majority of people (who mostly work in transport) then we have the same societal problem: job available, apply within (humans need not apply). If we’re to take the industrial revolution as gospel then most people leave the workforce when the jobs are automated.