On March 29, 2018, Laurence Bradford writes on Forbes:
There have been a lot of sci-fi stories written about artificial intelligence. But now that it’s actually becoming a reality, how is it really affecting the world? Let’s take a look at the current state of AI and some of the things it’s doing for modern society.
pexels.comCreating New Technology Jobs
According to Indeed research, demand for workers with AI skills has experienced steady growth over the past few years. When you add the fact that there’s currently a shortage of job seekers who can meet that need, it only makes the skills more valuable for those who do possess them or would like to learn.
What kinds of jobs are being created, specifically? Obviously, they’re mostly tech-related, but there’s actually some variety when you break it down. Job listings that most frequently included “artificial intelligence” or “machine learning” include data scientists, software engineers, software architects, and full-stack developers.
A few non-tech roles made the list as well, including research scientists and product managers, so there are certainly options for others who want to enter the field.
Plenty of big companies like Amazon are doing the hiring, but there are also startups finding new and creative ways to utilize AI.
Using Machine Learning To Eliminate Busywork
Just about everyone has experienced that feeling of not having enough hours in the day to accomplish everything they need to. By enabling smart computers to complete certain tasks, workers can free up their time for their more important work.
According to a DigitalOcean report, while only 26% of developers are currently using AI or machine learning tools in their workflows, 81% are interested in learning more about them.
Those in non-developer roles stand to benefit here too, of course. For instance, perhaps accountants could use machine learning to fill out forms. Or clothing companies could use smart algorithms to make outfit recommendations. Or customer service teams could use it to answer basic questions on a support ticket or live chat session.
Preventing Workplace Injuries With Automation
According to this study by Injury Claim Coach, thousands of injuries and fatalities could be avoided by automating the hazardous elements of certain jobs.
The study discovered that across all industries, 5,190 people died from workplace injuries in 2016 (and many more suffered non-fatal injuries). That averages out to 100 people per week.
Particularly hazardous careers included motor vehicle operation and construction (trailed distantly by grounds maintenance). These careers also happen to be quite likely to experience automation in the not-too-distant future.
So, how many lives could automation save? Well, assuming just 14% automation, it could be as high as roughly 3,500 per year by 2030.
So rather than thinking in terms of AI taking jobs away, it might be more accurate to think about how many dangerous jobs humans won’t need to do anymore. Protecting lives (and freeing up those workers to pursue safer careers) is definitely a powerful use case for automation. However, just so you don’t end up in a phased-out career, work on becoming irreplaceable now.
Reducing Human Error With Smart Algorithms
While the human brain is a powerful thing, no one makes perfect decisions all the time. It’s frankly impossible for us to store enough data about past situations, actions, and outcomes, and evaluate the probability of each one occurring, in the time it takes us to make a choice. We’re simply operating with limited data-sets, which hinders our abilities to select the optimal decisions.
With computers, that’s not the case. If an AI can draw upon a database with thousands or millions of scenarios, it can process that information to figure out what decisions are most likely to result in successful outcomes. “That is much of what machine learning and AI is all about–taking complex information and organizing it to help make the correct decisions fast,” says Mark McFarland, Team Lead of Technical Recruitment at Relativity.
Of course, this won’t work for all types of decisions (at least in the current state of AI), as some decisions require uniquely human considerations. But especially in the business world, it can certainly enable businesses to optimize their decision-making as logically as possible.
This is just a fraction of the potential use cases AI could have in the future. If all this has you interested in pursuing a machine learning career, start by developing these key skills to succeed.
Laurence Bradford is a product manager at Teachable and the creator of Learn to Code With Me, a blog and podcast for those wanting to transition into a tech career later in life.
Gary Reber Comments:
Yes, there will be new AI-related job opportunities but the non-human AI implementation overall will significantly eliminate the necessity for masses of human labor. While the national focus is always on job creation instead of ownership creation, our scientists, engineers, and executive managers who are not owners themselves, except for those in the highest employed positions, are encouraged to work to destroy employment by making the capital “worker” owner (“IT machines”) more productive. How much employment can be destroyed by substituting machines for people is a measure of their success –– always focused on producing at the lowest cost. Only the people who already own productive capital are the beneficiaries of their work, as they systematically concentrate more and more capital ownership in their stationary 1 percent ranks. Yet the 1 percent is not the people who do the overwhelming consuming. The result is the consumer populous is not able to get the money to buy the goods, products, and services produced as a result of substituting “machines” for people. And yet you can’t have mass production without mass human consumption made possible by “customers with money.”
