A simple definition for machine learning could be that it “is an application of artificial intelligence (AI) that provides systems the ability to automatically learn and improve from experience (without explicitly being programmed to do so). Machine learning focuses on developing computer programs that can access data, analyze it and use it to learn.”
It’s innovation and business potential is not restricted to company’s like Google and Facebook, to help us find better search results or to suggest, a person to add to our Facebook list of fans, or a video that might be of interest to us.
Actually the role of machine learning and Artificial Intelligence is much more exciting, and with a huge potential in areas like healthcare, for instance:
to diagnose cancer https://www.forbes.com/sites/bernardmarr/2017/05/16/how-ai-and-deep-learning-is-now-used-to-diagnose-cancer/#11ebc308c783 ) thought “teach (with a lot of data) how to spot images which indicate danger. In this case, this data would be previous CT scans which led to a diagnosis of lung cancer.”
to spot suicidal users on Facebook (https://www.bbc.com/news/technology-39126027 ) - “The social network has developed algorithms that spot warning signs in users' posts and the comments their friends leave in response.”
Machine learning also turned the concept of real-time into a reality, allowing “companies to analyze tons of data in real time, 24/7, getting deep insights.”
Machine Learning in HR
Nowadays machine learning already does some repetitive and time-consuming HR functions, that can save us a lot of time to allocate, for example in human interactions or on projects that need a more strategic approach.
We leave bellow a list of some examples, that you can explore in detail here, (https://gethppy.com/hrtrends/the-impact-of-machine-learning-in-hr) of functions that Artificial intelligence software’s already can do:
- Scheduling of HR functions such as interviews, performance appraisals, group meetings and a host of other regular HR tasks.
- Analytics and reporting on relevant HR data
- Streamlining workflows
- Improve recruitment procedures
- Reducing staff-turnover
- Personalize training
- Measure and manage engagement
- Enhance rewards and recognition programs
A middle ground between Artificial Intelligence and Preventing mental health problems at work
This technology has a really exciting potential. To think that machine learning can help detect earlier stages of cancer is really something.
However, it does need you to have some routine exams or due to any other reason for data to be available for processing.
Somewhere in between routine health checks and our daily life, there’s work to be done.
And in our daily lives, we often have the feeling of being exhausted due to mental or physical work, and those permanent patterns can lead to some predictable health issues.
All because sometimes we lack a good management of working hours. We often don’t remember/don’t know when to stop or, even worse, the company policy/culture doesn’t see it with good eyes.
But machine learning applications can help HR in preventing some work-related health issues.
Performetric (https://performetric.net/product) application, for example, does the learning through user interaction patterns with the computer interfaces (keyboard and mouse interaction) and then has the ability to identify and alert users (in real-time) at the onset of fatigue and burnout, providing recommendations that can prevent mental fatigue, fatigue or mental health problems.
It will also help the employees to improve their performance: reducing stress, preventing accidents and reducing errors. It’s a win-win situation, where employee engagement increases and by consequence productivity increases too.