WTF is AI?
Quick note before you immerse yourself in: This post contains some doom and gloom about the negative effect on your life and career that artificial intelligence may have. The last thing I want is to let you feel freaked out, so try reading to the end where I'm talking about the potential AI that needs to change your work for the better. If you can't make it that far, save it later or share it with a friend so you remember reading it in the news the next time you hear about AI or automation. You take a step to prepare yourself and a friend to be more successful in the future, anyway. You guys rock
By now you already know that artificial intelligence has the power to transform our work and industries every single one of us.
For certain instances, AI is used to remove those jobs entirely. For others, it'll just affect how they're handled or whether they're for demand. And in other cases, it will pave the way for creating new jobs — including those that none of us can imagine yet.
This post's goal is to help you understand what artificial intelligence is, and the jobs & aspects of work are most likely to be automated by AI, so you know how to position yourself in the near future for success.
Quick Navigation: WTF Is AI: The concept of artificial intelligence, its contexts, forms, and techniques causes a lot of ambiguity. How AI Will Automate Certain Jobs Out of Existence: Every week, multiple articles about the jobs being killed by automation are written down. I 'm providing examples of the skills that would be easiest for AI to automate in the short term, and some of the industries where impacts will be felt.
WTF Is Artificial Intelligence Anyway?
The more you understand what artificial intelligence is, the more you can understand whether your work is in danger of automation or not. The ambiguity (and deliberate misuse) around the word has, sadly, made life difficult for everyone.
First, there are two types of artificial intelligence: Artificial General Intelligence, that is, a computer capable of doing anything a human can. That is in contrast to Artificial Narrow Intelligence, in which a computer does what a human can do, but only within narrow bounds.
At all logical tasks (Artificial General Intelligence) it does not take a robot that is stronger than humans to remove those work. It will only take a form of existing AI-enabled software, which is better at one or two tasks than humans, such as driving from place A to place B, to be introduced into the market.
How AI Will Automate Certain Jobs Out of Existence?
“”By learning from a greater volume of information than we [humans] can process in our own lifetimes, AI software gives us the ability to reach new heights when solving complex problems. AI shows us that today’s state-of-the-art solution is no longer a global maximum, but in fact only a local maximum.”
The AI-related stories that land in your Facebook and Twitter feeds are all about the predictions of doomsday Artificial General Intelligence. They distract from the more pressing issue at hand though interesting.
AI-driven automation will generate new opportunities and enable people to be more efficient, but the harsh fact is that AI-driven automation would disrupt hundreds of millions of people across the globe, both individual work practices and entire industries. The “60 percent of all occupations have at least 30 percent of operations that are theoretically automate-able, ” and “ 47 percent of U.S. workers are at risk of being replaced by AI technologies” in the next 10–20 years.
If a organization stands to reap massive financial benefits from automating a certain task, and that task is automated using current artificial intelligence techniques, you can expect it to be automated soon. When a function is just to perform the particular task, then you can expect humans to be replaced by AI software rather than augmented. While automation is extremely traumatic for us losers of work, it can also increase the quality of life and save the lives of hundreds of millions of people in some cases.
Below are the events, jobs, and sectors that experts expect will encounter in the next 5 years the impacts of AI-driven automation.
Recognizing known patterns:
If you, or someone you love, have ever suffered from a medical problem that has gone undetected by doctors, you know the importance of detecting good injury and disease. Diseases are a class of "patterns" that an AI algorithm could help recognize humans.
There are ~38,000 radiologists in the US alone who make an average of $490,000 per annum. Such radiologists look at 39,275,011 mammograms annually to identify breast tissue anomalies which require further review, according to recent FDA statistics.
Previously, the UK's National Health Service found that routine tests on breast cancer are not adequately sensitive to identify ~17 per cent of cases. That's why people were so excited about Google's recent announcement that it had developed a "flag [potential breast cancer] algorithm that a person would miss."
“The algorithm helps you localize and find these tumors. And the doctor is really good at saying, ‘This is not cancer.’ The technology will be especially useful in parts of the world where there’s a shortage of physicians. For patients who don’t have access to a pathologist, an algorithm — even if imperfect — would be a meaningful improvement.”
If the technology makes it out of the laboratory and into hospitals, early diagnoses and treatment for patients could save many thousands of lives and millions of dollars — when procedures are most effective. Although the ability to automate this skill is immense, an AI is more likely to support a radiologist than to automate her out of work.
Unlike other jobs which consist largely of a single task, radiologists have many responsibilities. As well as identifying trends in medical photos, they are tasked with advising physicians to guide the care of patients and collaborating with doctors from various fields to agree on potential therapies to consider. None of these activities are likely to be automated soon, meaning that radiologists will be increased by a machine long before it puts them out of work.
Driving Cars and Delivering Goods:
Morgan Stanley predicts that self-driving truck technology will save $168 billion a year for the freight industry and Boston Consultancy Group predicts that self-driving cars will generate a $42 billion market by 2025.
Freight companies will save $70 billion annually by eliminating jobs for many of the 1.6 million+ people who drive heavy trucks in the US. And, it is estimated that they save $36 billion from reduced accidents: in 2015 alone 3,852 people died in large truck crashes.
The Obama White House estimated that drivers of ~1.4 million workers (taxi, bus, self-employed, etc.) are at risk from autonomous vehicle technology. Researchers also estimate that self-driving automobiles will reduce traffic deaths by ~90%. By the figures for 2015, that's almost 1,125,000 lives saved worldwide in a year, 11,250,000 saved over a decade, and 56.3 million fatalities prevented in a half-century.
Just put this into perspective, autonomous vehicles will save the combined populations of Fiji and The Bahamas, Belgium's entire population in 10 years, and the combined populations of South Africa and Botswana in 50 years in a single year.
The risk of AI automating driving and distribution jobs is so high because of the firm's simple cost (and life) savings opportunities that find a way to eliminate people from the picture. The biggest challenge for society is to prepare the drivers for new jobs. So far, there has been much discussion of skills being automated in lower wage careers, but skills will also be automated in high paid careers (such as the example of a radiologist).
Much has been written about Amazon using robots that rely on narrow AI to dominate its competition and cut operating expenses in warehouses by 20 per cent (that's billions of dollars). The little robots speed through the floors of the fulfillment center, lifting heavy goods and bringing them to human workers at Amazon so that they don't have to waste time walking in search of a product. It is not difficult to imagine robots of similar kinds finding their way into other industries.
For example , major U.S. companies in the waste industry will be encouraged to replace 48,620 waste collectors (as of May 2015) who earn $34,610 annually with AI-enabled robots that reduce costs to make their largest revenue center even more profitable (how fast the industry seizes the opportunity is another matter). Replacing humans in this role could benefit the environment by making waste disposal more efficient and picking up routes. It will also restrict the amount of backbreaking, thankless work that garbagemen and women do — but in the meantime, many people would lose their jobs.
Searching for and gathering information:
AI-driven automation can be felt not only in faraway truck yards, but also in the office building that you're actually sitting in right now. Knowledge workers spend at least 600 million hours searching for and collecting information each year, an activity that a machine can do better (faster and more efficiently).
We now have a methodology to automate people in these [white collar] roles. What this means is that if I have a company, I may not fire people — companies tend to try to minimize firings. But I may dramatically slow the rate at which I hire new people and instead invest in automation. Ultimately, this leads to fewer job opportunities in the long term in these areas.
You can imagine the excitement of a manager who says that narrow AI makes it possible for software to show its salespeople the information they need, to improve their productivity by allowing them to spend the 2 hours they lose every day searching for an activity that is much more valuable to the business as well as to automate narrow AI software — helping a new customer to have a be.
The salesperson (and many other types of knowledge workers) is more than their ability to track information, like the radiologist whose job has layers beyond spotting abnormalities in a medical image. She is thus more likely to be complemented by AI than automated — more in the next section on this. For example , demand for analysts, who are primarily tasked with conducting research, will probably shrink as a "mix of machine learning algorithms and distributed labor" can replace much of their work.
Most knowledge workers spend less than half of their time doing things they’re really good at (i.e., what they’ve been hired to do). The rest is spent doing research, arranging meetings, coordinating with other people, and performing other minutia of office life. These tasks could be done just as well by a machine intelligence service.
The reality is, there would be both positive and negative effects of AI-driven automation. Although some workers are especially vulnerable to being completely automated and missing a human need in the process, it is more likely to automate specific tasks without taking the rest of the job with it.
Only time will tell if our society will find a way to employ the people who suffer the most from automation. It is not worth devoting time and energy to mastering the activities mentioned above. In the very near future, AI-software would be stronger than most humans. A better use of your time will be to focus on the following skills, which are highly complementary to AI 's development.
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