Sunday, January 8, 2017

Maybe the Jobs of the Future don't exist yet

You can find lots of articles on the web written about jobs that can be done by a machine versus a person.  As I've written in the past, I tend to be pretty optimistic about the future, but I don't believe anyone can know how the nature of jobs will transform over the years as people determine how automation can be introduced into various aspects of life.

Here's an article from Fast Company that appeared 3 1/2 years ago.  I don't think it's aged well.  Here are four things it listed:

1) Unstructured problem-solving: solving for problems in which the rules do not currently exist. Examples: a doctor diagnosing a disease, a lawyer writing a persuasive argument, a designer creating a new web application
When looking at the examples given, I think diagnosing a disease is probably the first one to be taken over by a machine.  But, depending on how you frame the problem, an AI could be written to determine which styles of argument may be most likely to succeed in certain scenarios.  Neither, eliminates the need for a doctor or lawyer, but they are definitely tools that reduce time spent by the primary doctor or lawyer, which could have significant downstream effects on the number of doctors, lawyers, research aids, paralegals, etc.  Really, AI and machine learning are tools.  By themselves they don't do what a person can do, but they change the nature of the work, and the downstream effects of that are what is really unknown.

2) Acquiring and processing new information, deciding what is relevant in a flood of undefined phenomena. Examples: a scientist discovering the properties of a medicine, an underwater explorer, or a journalist reporting on a story.
Machine learning is all about determining what data is relevant.  A person sets the parameters of what kind of data is relevant, but machines are best determining the specific data that is relevant.  As I've noted before, even some forms of journalism aren't safe.

3) Nonroutine physical work. Performing complex tasks in 3-D space, from cleaning to driving to cooking to giving manicures, which is thought of as relatively low-skilled work for humans, but actually requires a combination of skill #1 and skill #2 that is still very difficult for computers to master.
This is true, be we constantly break tasks down to their simplest essentials and teach machines to do that one task.  Then we start layering the automated processes on top of each other.  I think, the rise of self-driving cars, is a great illustration of this.  It's been true for a while that machines are better at routine driving than people would are (machines don't daydream or get distracted), but people are better at the unexpected (icy patch on a road).  But, at a far greater rate than most people thought even a couple years ago, these problems are being solved.  When a car hits an icy patch, it will be able to determine, based on various sensors and algorithms, what options are best when encountering something unexpected.  Now, it's true, that if something is completely unexpected or has never been considered before, a machine won't make the same kind of value judgements that a person would.  But, once self-driving cars become common place, they will continue to learn.

4) Being human: Expressing empathy, making people feel good, taking care of others, being artistic and creative for the sake of creativity, expressing emotions and vulnerability in a relatable way, making people laugh.
True.  Machines will never be human.

AI will change the face of the workplace.  The problems that you'll find with articles that try to predict what jobs will be safe, is that they think of the jobs as they exist for humans.  But, AI won't do the exact same jobs as people do, they'll do different jobs that will in turn change the jobs that people will be needed for.

I changed the title based on an experiment I'm noticing with retweet bots.  More later.

No comments:

Post a Comment