Artificial intelligence is a set of algorithms and intelligence aimed at imitating human intelligence. The AI field was founded on the assumption that human intelligence “can be so precisely described that a machine can be made to simulate it.” This raises philosophical arguments about the mind and the ethics of creating artificial beings endowed with human-like intelligence. These issues have been explored as myths, fiction, and philosophy since the past ages. Let’s take a look at the myths.
Have you heard that AI will displace humans in all working sectors? How true is this assertion? AI is no different from other technological advances in that it helps humans become more effective and processes more efficient.
AI needs to be thought of as an enhancement rather than complete automation and replacement, thus, helping the human force to work in newer and smarter ways. Humans simply engage machines to make things easier.
The European Union advocated for artificial intelligence for economic benefits, including “improving healthcare (e.g., making diagnosis more accurate, enabling better prevention of diseases), increasing the efficiency of farming, contributing to climate change mitigation and adaptation.
Another myth is that “Cognitive AI” technologies can understand and solve problems like the human brain. “Cognitive” technologies can’t solve problems they weren’t designed to solve. AI cannot make sense of data that is too broad or has not been processed in a way that makes it digestible. Cognitive technologies address problems that require human interpretation and judgment.
Did you ever think that AI algorithms could make sense and interpret all data? The most important input for an AI tool is data, not just data, but the right data. That means the right data is only relevant to the problem being solved and specific to a set of instructions and a domain of knowledge.
AI cannot make sense of data that has not been processed or programmed for specific purposes that make it digestible by the system. An algorithm is a program, and programs need good data.
Here is another myth for you to consider. You need data scientists, machine learning experts, and huge budgets to use AI for business. AI technology does require deep expertise in programming languages and sophisticated techniques. However, the business value lies in using existing AI tools to address components of the application and configuring those components to the business’s specific needs. That process requires less data science expertise and more knowledge of core business processes and needs.
Finally, you may be wary of this myth – AI will lead to the takeover of the human race by superior robotic machines. Physicist Stephen Hawking and tech entrepreneur Elon Musk have made it very clear they believe the danger is real. However, at the moment, it’s highly unlikely anyone would think about building or deploying a machine with the ability to “make up its mind” to hurt and turn against its human creators.
AI will not take over the globe or humankind since it can’t operate devoid of human direction.