Source – entrepreneur.com
The term “machine learning” might not mean much to you. You might imagine a computer playing chess, calculating the multitude of moves and the possible countermoves. But, when you hear the term “artificial intelligence” or “AI,” however, it’s more likely you have visions of Skynet and the rise of our inevitable robot overlords.
But, the truth of artificial intelligence — and particularly machine learning — is far less sinister, and it’s actually not something of the far-off future. It’s here today, and it’s shaping and simplifying the way we live, work, travel and communicate.
In fact, it’s shaping our everyday lives and the decisions we make. In part, it is even how you came across this article.
What is machine learning?
Machine learning is one element (perhaps the driving force) of AI, whereby a computer is programmed with the ability to self-teach and improve its performance of a specific task. In essence, machine learning is all about analyzing big data — the automatic extraction of information and using it to make predictions, decipher whether the prediction was correct, and if incorrect, learning from that to make a more correct prediction in the future.
Google, Amazon, Netflix and other monolithic online platforms use it to deliver semantic results based on algorithms that analyze a user’s search, purchase and viewing history to predict what is it they’re looking for or more likely to want.
The data they have at their disposal is massive. A recent global digital reportpublished by We Are Social and Hootsuite states that the number of people using the internet to search has hit 4 billion people in 2018. Every second, there are approximately 40,000 searches processed, which equates to 3.5 billion a day, or an incredible 1.2 trillion searches per year. Each year, humanity spends the equivalent of 1 billion years online.
That’s a staggering amount of data gathered every day, and it would be impossible to analyze without the help of machine learning. But, the implications of machine learning go far beyond satiating our seemingly unquenchable thirst for knowledge and cat GIFs. Machine learning is being increasingly integrated into all industries and every facet of our workday and leisure time — through the automation of manual labor, improving our connectivity and the way we live and shaping the future of AI and the internet of Things (IoT).
How machine learning affects work life
The implications of machine learning on industries, professions and the workforce are considered miraculous by some and catastrophic by others. Your opinion will largely depend on your profession and the work you do. Machine learning has the potential to automate a large portion of skilled labor, but the degree to which this affects a workforce depends on the level of difficulty involved in the job. Machine learning at present allows the automation of singular tasks, whereas many jobs involve multiple tasks and even multitasking at a level machine learning isn’t capable of yet.
Education
Teachers are required to wear many hats: educator, diplomat, analyst, counselor, mentor, ally, referee and plenty more. There’s no computer or robot that can fulfill those functions yet, but through machine learning, some of those tasks can be automated.
Computers can be programmed to determine individual study plans, specific to each student’s needs. Algorithms can analyze test results, drastically reducing the time teachers spend in their leisure time on grading. A student’s attendance and academic history can help determine gaps in knowledge and learning disabilities. These applications won’t necessarily translate to a teacher-less classroom (though there is that hypothetical, as well), but will facilitate the teaching and learning environments to enhance the outcomes and ease the burden on both teacher and student.
Law
Legal firms are increasingly turning to machine learning to process massive amounts of data related to legal precedents. J.P. Morgan, for example, uses a software program dubbed COIN (Control Intelligence) to review documents and previous cases in seconds that would otherwise take 360,000 hours.
As with our teachers above, it’s unlikely machine learning or AI will replace lawyers any time soon, given the necessity of rebuttal and human logic / appeal, but the incorporation of machine learning will surely reduce the time taken to put together a case, and it could expedite trials, speeding up the processes of the court.
Skilled and manual labor
The automation of industries is the most obvious shift we can expect from machine learning. Functions and tasks that were once undertaken by trained workers are increasingly being mechanized, in particular jobs that involve some element of danger or potential harm, such as work in factories and mining. There are already driverless trucks operating in mining pits in Australia, operated remotely from a distant control center.
More and more machinery is taking the place of labor. You need only visit your local supermarket to see more self-service kiosks and fewer staff). But, here again, there is a limit to how far a person is willing to deal with a machine, and the human ability to quickly fix a problem isn’t something machines are capable of yet.
Health
Machine learning is taking a bigger part in our health and well-being on a daily basis, and it is already being used for faster patient diagnosis. Even the prevention of illness in the first place have been aided by predicting the potential health problems one may be susceptible to, based on age, socio-economic status, genetic history, etc.
The use of programs to analyze and cross-reference symptoms against databases containing millions of other cases and illnesses has led to faster diagnoses of illness and disease, saving lives through quicker treatment and decreasing the time a patient spends in the health system. Hospitals are currently using AI algorithms to more accurately detect tumors in radiology scans and analyze different moles for skin cancer, and machine learning is being adapted to accelerate research toward a cure for cancer.
Transport
The self-control of our transport industries is steadily becoming more reliant on machine learning and AI, and it is expected that within the next decade, the majority of our shipping and rail networks will be controlled autonomously. China is currently testing driverless public buses.
Meanwhile, Rolls Royce and Google have teamed up to design and launch the world’s first self-driving ship by 2020. The vessel will use Google’s Cloud Machine Learning Engine to track and identify objects at sea. While Google’s self-driving car replaces one driver, the autonomous ship’s AI will need to carry out the tasks usually requiring a crew of 20.
Several Canadian aviation companies are also putting big money into developing pilotless commercial aircraft. And the sky isn’t even the limit, with NASA having successfully launched and landed an autonomous space shuttle, with plans to develop a model that could one day carry passengers.
How machine learning affects home life
Machine learning and the IoT is enhancing the way we communicate and live our daily lives. Impressive advancements are being made in mind-reading technology, such as the AlterEgo headset that responds to our brainwaves to control appliances around the house. This tech has been in development for some time, and while the AlterEgo is still a little awkward looking, it isn’t difficult to picture how its wearability will be improved over the next decade. It’s exciting to imagine the implications for these advancements to change the way you operate the appliances in your home.
The automation of our domestic lives is already occurring. Amazon’s Echo and Alexa allow for the voice-activated control of your smart-home (the dimming of lights, closing of blinds, locking of doors, etc., all at your command).
Even the humble fridge has been given the 21st-century makeover and is now connected to the internet. You can be at work and still see inside your fridge to know exactly what food you’re running low on. You don’t even necessarily need to go to the shop to restock. Your groceries can be ordered on the road and delivered to your door at your convenience.
In the very close future, we can expect the automation of practically every aspect of your home. You can be stuck in traffic on your way from work and cozy your home from the car, turning the heat on, dimming the lights and having your favorite song playing as you step through the door.