Articles — Apr 16, 2019
Artificial Intelligence: Top 5 Myths Debunked
Artificial intelligence (AI) is evolving, and as a result, its uses are continuing to expand. With virtual assistants in our pockets, most of us rely on AI in our daily lives and it may not even cross our minds. Think about when Netflix suggests a show for you, Spotify suggests a song based on your preferences or Amazon shows you a product you may like: all of this is AI at work. In fact, Pegasystems found that only 33% of consumers think they’re using an AI-powered device or service, while 77% actually are.
While AI is helping us boost efficiency and productivity in our personal lives, it’s also doing the same for businesses. According to a survey conducted by PwC, 72% of business leaders believe AI to be fundamental in the future, referring to it as a “business advantage”. AI can not only help businesses make better and more informed decisions, but can help make them even quicker. Plus, by automating simple or administrative tasks, your workforce can be more efficient with their time and focus more heavily on major tasks contributing to your overall business strategy.
However, with such a rapidly advancing concept can come a lot of misunderstanding. Let’s take a look at some of the most common myths surrounding AI.
AI takes the “human” out of human resources.
According to a survey conducted by the Human Resources Professional Association, 52 percent of respondents reported that their organizations were not likely to adopt AI into their HR departments. Often, businesses are hesitant to integrate AI into their HR processes as they fear that it may reduce the personalized interactions and experiences associated with such a people-focused field. However, PwC reports that nearly two-third of business decision makers feel that AI can provide a “superior one-to-one personalized experience”.
When it comes to the HR space, technology has the potential to not only maintain the “human” aspect, but may even be able to enhance it. Often, what is referred to as “AI” in HR and other fields is actually IA, or intelligent automation. While the technology behind both concepts is identical, the goals of both differ. AI aims to automate processes to eliminate human involvement, while IA supplements the work we do in order to enhance our productivity.
IA can simplify many tasks which may normally take HR professionals a great deal of time and energy. This includes tasks related to talent acquisition, onboarding, benefits enrollment and day-to-day administrative responsibilities. As a result, HR professionals are able to complete routine tasks more efficiently, allowing them to dedicate more time toward projects that help to create a positive and empowering work environment for their employees.
AI is the ultimate “answer”.
On the other side of it, there is a common misconception that AI is the “answer” to any business issue that is thrown its way. In reality, it’s up to us to set AI up for success. Ultimately, we are all responsible for defining clear parameters for how AI will be leveraged in our businesses.
Instead of viewing AI as an “answer” we should instead reframe our mindset to understand AI as a “tool”. In other words, AI is a means to help us resolve a problem or achieve a certain goal, not the actual solution. Ideally, we want to learn from the rationale an AI system uses to help us reach these goals. However, AI is often a “black box”, meaning that it’s difficult to uncover the reasoning behind the results it produces. While there is no definite solution for this lack of transparency, businesses must do what they can to design their systems to fit within the confines of their expectations and norms. Keep in mind that even if we’re able to have our AI systems produce an explanation for its rationale, it should be always taken with caution.
According to MIT Sloan Management Review, only 39% of companies have an AI strategy in place. If you intend to incorporate AI into your business processes, be sure to first develop a detailed strategy for how your business can leverage AI in order come closer to achieving their goals.
AI can make sense of anything you feed it.
With so much buzz surrounding AI, organizations are often keen on adopting it before carefully understanding and assessing their data. Keep in mind that data is the core of AI. Consider the unique data within your organization and how this information can be leveraged to drive intelligence. Think about where your data is housed, which data sources can enhance your data and how data drives your organization’s decision-making. Remember, it comes down to both quantity and quality: not only does your organization require enough data to train the AI models, but it’s also essential to have a diverse set of data in order to reduce the risk of bias.
AI, machine learning and deep learning are all the same concept.
While all three are interrelated, they’re all different concepts. Here’s the gist: machine learning is a subset of AI, and deep learning is, in turn, a subset of machine learning.
The goal of artificial intelligence is to have a machine mimic human intelligence in some way. But how can this be achieved? By first understanding and mimicking the way humans learn. Instead of spending time hard-coding a machine to perform a certain way, machine learning lets this happen in an unsupervised manner, reducing the amount of human involvement needed. Machine learning involves feeding a computer algorithm data, defining some rules and letting the machine recognize patterns and draw conclusions, improving over time.
Deep learning is a form of machine learning modeled off the neural network we have in our brain. When we receive a piece of information, our brain tries to compare it to what we already know in order to understand it. This is the same concept that deep learning algorithms use
So, what’s the key difference between these two? When trying to recognize a certain object, for example, machine learning needs to be fed data about the object’s characteristics in order to classify it. Deep learning, on the other hand, can automatically discover these characteristics and classify the object on its own (but requires a lot more data to do so!)
AI will displace your job.
Despite the rapid technological advances happening in the world today, it’s impossible for all business processes to be completely technology-based. A certain level of human involvement will always be required in business functions, no matter how advanced AI eventually gets. Along the same vein, as the saying goes, everything in moderation. Recognizing that AI has its limitations and viewing it as a supplemental tool to human work that can help boost efficiency for your business will keep unrealistic expectations of AI at bay.
Ultimately, the takeaway here is that while some jobs will be affected by the rise of AI, it’s also true that new sectors will emerge and drive growth as a direct result of artificial intelligence, technology and automation.