{"id":49407,"date":"2021-05-04T00:00:00","date_gmt":"2021-05-04T00:00:00","guid":{"rendered":"https:\/\/www.techopedia.com\/the-promises-and-pitfalls-of-machine-learning\/"},"modified":"2021-08-17T21:20:27","modified_gmt":"2021-08-17T21:20:27","slug":"the-promises-and-pitfalls-of-machine-learning","status":"publish","type":"post","link":"https:\/\/www.techopedia.com\/2\/31657\/technology-trends\/big-data\/the-promises-and-pitfalls-of-machine-learning","title":{"rendered":"The Promises and Pitfalls of Machine Learning"},"content":{"rendered":"

More people would have died in the pandemic had it not been for Robovision’s<\/a> international Imaging COVID-19 AI <\/a>initiative. “Our algorithm helps radiologists accurately diagnose COVID-19,” Erik Ranschaert<\/a>, co-founder of that machine learning (ML)<\/a> program told me. "Physicians all over the world will use our deep learning platform to settle questions like: What’s the probability that this is COVID, should this patient be rushed to the ICU, and how deep is this lung tissue affected?”<\/p>\n

Repeated in the retail, educational and hospitality industries, among others, it was our ML-trained robot counterparts that eased our lives, healed us, educated us, fed us, shopped for us and so forth. Machine learning certainly has its advantages. On the flip side, ML has its disadvantages, too.<\/p>\n

What is Machine Learning?<\/span><\/h2>\n

Data scientists<\/a> have this ambitious project of training machines to think like us. That includes the capabilities of detecting, predicting and recommending or prescribing solutions. Right now, more human-like abilities (like emotion or creativity) are beyond them, but in the past 40 years, or even in the last five years, machines have come an incredibly long way. (Read also: What is the Impact of AI on Art?<\/a>)<\/strong><\/p>\n

Machine learning is done by scientists feeding hundreds of thousands of images of an item into the machine algorithms so that the algorithm recognizes the differences between that item and different items. Algorithms are tested and retrained until they pass their tests. These algorithms are then put to work in real life to achieve their purposes.<\/p>\n

Machine learning is famously used in innovations like voice recognition systems, digital customer assistants (e.g., Alexa and chatbots), self-driving cars, credit card fraud detection systems and virus and spam detection software.<\/p>\n

In addition, ML is proving itself to be an event-driven defence against cybercrime<\/a>. ML first gains an understanding of what is normal (measured against a baseline) then actively detects and prevents attacks perpetrated by cybercriminals. It does this by actively blocking traffic from suspicious IP addresses, or preventing malicious activity against network files and maintaining confidentiality, integrity and availability of data.<\/p>\n

Machine Learning Benefits<\/span><\/h2>\n

1. Machine Prediction<\/h3>\n

Machines are better and faster at analyzing huge data sets with complex variables than any human. In fact, researchers say predictive modeling techniques can detect illnesses better than doctors<\/a> and determine the best treatment with 40 percent better patient outcomes.<\/p>\n

Just from recording our voices or gait, machines can tell whether humans are more likely to die from cancer<\/a> in the next few years or get neurological diseases<\/a> like Alzheimer's, ALS and Parkinson's. Their predictions help doctors prevent illness and death.<\/p>\n

When it comes to COVID-19, studies show<\/a> ML algorithms like those deployed by Robovision predicted onset Covid with 95% accuracy.<\/p>\n

2. Machine Detection<\/h3>\n

Machines outperform humans by detecting objects five percent more accurately than us<\/a> – an ability that helps them help us across industries. Hailey Peng<\/a>, former Marketing Manager at the technology company, DJI<\/a>, told me how ML-trained drones choked forest fires in the German town of Hechingen, <\/a>in August 2018, and saved 765 firefighters. Accurately analyzing the situation, the drones helped Hechingen’s fire chief dispatch crews faster to the scene with precise manpower, units and supplies.<\/p>\n

“The biggest advantage came to light during the search for hotspots and extinguishing them,” Hechingen’s Fire Chief Commander Bulach later reports<\/a> DJI: “The simultaneous deployment of the XT and X4S provided me with exact information about where to delete the hotspots and how long until we reached a safe state.”<\/p>\n

3. Machine Prescription<\/h3>\n

Modern machines can analyze data and come up with solutions 100 times faster than any human<\/a>. Using this ability, models help farmers and agronomists identify, prevent and treat problems such as soil erosion and irrigation issues, unhealthy plants, and livestock disease. It also helps them apply the precise amount of chemicals to fungible crops. (Read also: Adventures in AgroTech: 7 Can't-Miss Developments<\/a>.)<\/strong><\/p>\n

In 2010, Vijay Bhaskar Reddy of India created a mobile device to help farmers monitor their pumps and save their fields from flooding. “Travelling 14 miles multiple times a day to just water the fields takes a lot of time and a lot of petrol.”<\/p>\n

A farmer from Telangana’s Karimnagar district told me, “Since I started using this KisanRaja app about five years back, I no longer have to guess when to switch on the pumps and go back and forth to my home and wake up late at night to go in the fields among the snakes and switch on the pumps. I can turn them on from wherever I am, even driving my daughter to school.”<\/p>\n

ML is used across industries in countless ways. These include:<\/p>\n