‘Artificial Intelligence’ and its acronym- AI- have become widely used in recent years, almost becoming something of a ‘buzz phrase’. The true definition of AI becomes lost, and people might picture a world of autonomous robots where humans have become obsolete!
Essentially, AI describes technology systems that exhibit intelligent behaviours such as understanding text, images, and other data. We are quite some way from humans being taken over by computers. In fact, we’re much more likely to find ourselves working alongside AI technology systems in our daily work, helping us to be more efficient and effective.
Let’s look at some common AI myths and uncover the truth about the current state of AI and what we can expect from the future.
Myth 1: Data is all you need for AI to work
Truth: A few years ago, ‘big data’ was a hot topic, as business leaders began to understand that collecting data is important for making informed decisions. From there, it was a natural progression for people collecting data to start applying AI to make sense of it. From there, we get a myth that collecting the right data is all you need to apply AI and get value from it.
While it’s true that strong, clean data is critical, AI systems also require advanced algorithms and high-performing computer platforms to work effectively. These, along with the data, are all equally important for an AI system to perform and produce valuable outputs.
Myth 2: AI is the ‘new electricity’ and we should use it everywhere we can
Truth: In the long-run, AI certainly has the potential to penetrate deeply into many areas of business and society. However, attempting to implement AI with abandon is risky. In the very least, it can be extremely costly, and not every business function or process needs it. For example, an airplane is the fastest commercial vehicle available to us, but it’s probably not best suited for your commute to work. Similarly, an elevator is needed in a skyscraper, but much less so in a two-storey home.
Business leaders who apply AI without properly considering its capabilities and limitations might not see the results they were hoping for, which can make them wary of investing in the future. A more cost-effective way for businesses to apply AI is to identify the best existing solutions for each area of the business.
Myth 3: AI systems can only be developed by machine learning (ML) scientists, and we don’t need anyone else
Truth: Advanced AI systems are incredibly complex, and ML scientists are only one part of what makes them work. We need teams of engineers, scientists and project managers to build and operate them effectively, creating great career opportunities for people with the right skills. Just as we have seen for hundreds of years, as new technologies automate daily tasks, new opportunities arise for people to oversee that technology, or simply spend their time on more productive endeavours.
Myth 4: AI is surpassing human capability – we are becoming irrelevant in the decision-making process
Truth: By and large, AI technology still lacks many of the attributes that we typically ascribe to humanity. For example, AI still generally lacks the ability to feel compassion or empathy and is not able to detect nuance. This means that for big decisions — a medical diagnosis, for example — while AI can be immensely helpful in saving a doctor’s time, he or she will still need to look at the data, rely on their past experiences and education, and make the final decision and communicate the information to the patient in a compassionate way.
Myth 5: With the current speed to technology development, we’ll soon be living in a world where robots and computers are in charge
Truth: Most successful AI systems only function in very narrow areas- we are far from a ‘general AI’ that can proactively take on many tasks at once, like people. Perhaps more importantly, the next phase of AI development will be human-centred AI, which refers to AI systems that are designed with the end human user in mind.
We don’t need AI to act exactly like humans- we already have humans for that! Instead, AI needs to be like a teammate who is good at the things that we are not so good at. In designing human-centred AI, we want tools and solutions that are good at logic, scale and speed to work alongside human beings, who are good at things like emotion, compassion and creativity. This way, human intelligence and artificial intelligence will achieve much more together than either entity could do by itself.
Rather than feel trepidation about the continued implementation of AI, we should feel the excitement! New technologies such as AI will lead us into a world where our products and services are better customized to suit our needs and our mundane tasks are automated so we can spend more time on the things important to us.
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