The highest paying college major in the world, computer science, will hold very little value for employers in the future," said Mark Cuban.

The article discusses the impact of artificial intelligence (AI) on the job market. While AI is increasingly making some jobs obsolete, the need for computer science degrees is also predicted to increase as the understanding of AI systems becomes necessary. The article highlights a protest by Hollywood’s Writers Guild of America against the use of AI for writing scripts, citing the need for proper attribution and copyright. The article also discusses the views of experts who suggest that AI will not cause instant mass unemployment but will displace jobs over time and make people more productive. Companies like IBM are already replacing jobs that can be done by AI. Overall, the article suggests that the future impact of AI on jobs is uncertain, and there may be a need for humans to be trained like AI models to be unbiased, capable, and proficient in them.

  •  pancake   ( @pancake@lemmy.ml ) English
    2•1 year ago

    Current AI are regression models, they are trained on some input and thus encode any rules and patterns that may govern this input. So, by definition, it does have conceptual understanding, as any information that may constitute this understanding is encoded within the model in a form in which it may use it for any purpose it needs.

    For example, if you give an AI many examples of long multiplication, it will eventually learn the rules that govern it, and it will be able to perform any multiplication by itself. There’s no practical difference between this and actual understanding (also it doesn’t help that our brains are just analog tensor-multiplication machines, much like the AI we’re creating).

    •  pingveno   ( @pingveno@lemmy.ml ) English
      0•1 year ago

      But long multiplication and software development are two different breeds. Long multiplication is just one set of very mechanical behaviors. Software has to be highly specialized to the task at hand.

      Take a project I maintain, an access request system. I had to:

      • Get a concept of what was needed
      • Review the access request system that I was replacing
      • Model the database
      • Draft email templates
      • Make REST API calls to systems for provisioning access
      • Handle authentication and authorization
      • Fill in a tree of requestable items
      • Work on a deployment process

      All this required that I have a very deep understanding of this specific application, how it works with the rest of our systems, and how it works with our business processes. Access request systems are a dime a dozen, but getting it honed to our specific requirements took precise knowledge and some creativity.