Companies using controversial AI software to help hire or fire employees - and gauge whether they like their boss
- In the past, companies have used technology to increase employee productivity
- Now, more and more firms are relying on artificial intelligence for hiring, firing and compensation decisions, as well as to learn about employee wellness
- But critics argue that using AI in human resources could exhibit harmful biases
Sometime soon, artificial intelligence could be to blame for you getting hired or fired.
A growing number of employers have turned to AI to make hiring and firing decisions, as well as to determine how people feel about their bosses, according to the Wall Street Journal.
One of the most popular kinds of workplace-focused AI software out there is called Xander and it can determine whether an employee feels optimistic, confused or angry, among other things.
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In the past, companies have often used technology to keep track of employee actions and increase productivity. But recently, they've begun using AI for hiring, firing and compensation
Xander, which is developed by tech firm Ultimate Software, is being used at steel processor SPS Companies in Manhattan, Kansas, the Journal noted.
SPS used Xander to efficiently analyze and categorize employee responses to a confidential survey.
But it's not all negative: SPS was able to use the AI-analyzed results from the survey to improve its health care plan after staffers indicated that the current offerings were confusing and overwhelming.
To do this, Xander analyzes responses to open-ended questions, assigning attitudes or opinions to employees based on language and other data, the Journal said.
In the past, companies have often used technology to keep track of employee actions and increase productivity.
It's only recently, however, that AI has increasingly become a useful tool for measuring employee sentiment, as well as in hiring, firing and compensation.
Experts and employment lawyers have grown concerned that AI may contain biases that could lead to workplace discrimination. AI has been proven on several occasions to exhibit bias
More than 40% of global employers have used AI processes of some kind, according to the Journal.
At the same time, the emergence of AI in human resources has some regulators worried.
Experts and employment lawyers have grown concerned that AI may contain biases that could lead to workplace discrimination.
And other employees simply don't want to be tracked with AI.
AI still faces some issues recognizing all human emotions, like depression and sarcasm.
Algorithms have been shown on numerous occasions to be susceptible to racial biases.
AI still faces some issues recognizing all human emotions, like depression and sarcasm. But companies like DeepMind's AI technology are working to make it smarter
A hiring algorithm may pick up on a higher rate of absences for people with disabilities and recommend against hiring them, the Journal said.
So it's unsurprising, then, that the Equal Employment Opportunity Commission determined in 2016 that the technology can potentially create new barriers for opportunities.
While AI is nowhere near as smart as a human, the technology has continued to advance in recent years.
For example, a new artificial intelligence that is learning to understand the 'thoughts' of others has been built by Google-owned research firm DeepMind.
The software is capable of predicting what other AIs will do, and can even understand whether they hold 'false beliefs' about the world around them.
HOW DOES ARTIFICIAL INTELLIGENCE LEARN?
AI systems rely on artificial neural networks (ANNs), which try to simulate the way the brain works in order to learn.
ANNs can be trained to recognise patterns in information - including speech, text data, or visual images - and are the basis for a large number of the developments in AI over recent years.
Conventional AI uses input to 'teach' an algorithm about a particular subject by feeding it massive amounts of information.
AI systems rely on artificial neural networks (ANNs), which try to simulate the way the brain works in order to learn. ANNs can be trained to recognise patterns in information - including speech, text data, or visual images
Practical applications include Google's language translation services, Facebook's facial recognition software and Snapchat's image altering live filters.
The process of inputting this data can be extremely time consuming, and is limited to one type of knowledge.
A new breed of ANNs called Adversarial Neural Networks pits the wits of two AI bots against each other, which allows them to learn from each other.
This approach is designed to speed up the process of learning, as well as refining the output created by AI systems.
DeepMind reports its bot can now pass a key psychological test that most children only develop the skills for at around age four.
Its proficiency in this 'theory of mind' test may lead to robots that can think more like humans.
Most humans regularly think about the beliefs and intentions of others, an abstract skill shared by a fraction of the animal kingdom, including chimps and orangutans.
This 'theory of mind' is key to our complex social interactions, and is a must for any AI hoping to imitate a human.
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