10 misconceptions about AI—dispelled

3 min read

Hand holding AI circuit

No longer relegated to the status of science fiction lore, AI is now thoroughly integrated into our everyday lives. But there are a lot of misconceptions surrounding this technology – ranging from the absurd to the all too plausible. To help set the record straight, here are 10 misconceptions about AI.

1. AI will replace human workers

As companies across sectors continue to adopt automation, many people are understandably concerned about the possibility of losing their jobs. While some jobs will be lost to automation, the idea that robots will largely replace humans is far from true. Just as the cotton gin and printing press resulted in job losses that paved the way for new career opportunities, so too will AI.

In fact, an in-depth study by Gartner found that by 2020 there will be 2.3 million new jobs available thanks to AI. Workers in sectors where AI will have the most significant impact like manufacturing, data processing, and retail, will see their job efficiency improve as automation takes over the most predictive tasks, complementing human workers.

2. AI can solve any problem

When it comes to AI, people seem to fall into one of two opposing categories: those who believe the technology is a death knell for humanity and those who believe that it will save mankind. AI has a wide breadth of applications some of which can indeed bring about powerful changes to society. Image recognition for cancer detection, predictive analytics, optimized crop production, and self-driving vehicles that improve road safety all come to mind. But AI isn’t a panacea for the ills of the world. Indeed, problems that don’t involve data, computation, or computer vision are unlikely to be improved by AI.

3. AI is infallible

Most people seem to understand that a tool which utilizes data will eventually make a mistake. However, some mistakenly assume that AI is all nuts and bolts, so to speak, making it inherently better than ourselves. But this type of thinking misses the essence of the technology. All non-sentient (i.e. true AI) systems are trained by a human, specifically, the data selected and curated by humans. If this data is cherry-picked, incomplete, or compromised in any way, so will be the AI and results obtained from it.

4. AI and machine learning are the same

Artificial intelligence is an umbrella term that includes machine learning, robotic process automation, deep learning and natural language processing. Machine learning is the statistical-based methodology used for training AI systems. Supervised learning (i.e. fitting data into a known category) and unsupervised learning (i.e. analyzing data to identify patterns or categories) are the two main branches of machine learning and utilize algorithms like SVM, K-means, regression and classification, or others, depending on the type of data used and desired outcome. Deep learning is a further subset of machine learning that uses multilayered neural networks able to solve more complex problems in a more “human-like” way.

5. LOF companies use AI

Many people may be surprised to learn that true AI does not yet exist. A true AI would be capable of independent thought with reference to its own experience, knowledge base, or environment. It wouldn’t need to be trained or tested by humans in order to come to some type of meaningful conclusion about a given scenario.

The technology that the most advanced companies use, including the likes of IBM’s Watson and Amazon’s Alexa would be more accurate to describe as augmented intelligence systems. They can extrapolate some information about the world around them but are still dependent on humans for the vast majority of data/information input, making them not quite true AI.

6. AI will be the end of humanity

Since the release of the first Terminator movie in 1984, people have been afraid of Skynet-like artificial intelligence that would extinguish mankind. But much like the misconception about robots replacing humans in the workforce, this claim is little more than smoke and mirrors. As we’ve already said, today’s AI is nothing like the fully-capable “true” AI of science fiction. The creation of a self-conscious and fully autonomous system is hardly possible at all, at least at the current level of technological development.

7. AI is expensive

Implementing a fully automated system at the enterprise level isn’t cheap. Neither is building an analytics team to make sense of terabytes of data. But depending on the needs and goals of the organization, it may be entirely possible to adopt AI and get the desired insights without breaking the bank. The key is for each business to figure out what they want and apply AI as needed, with respect to their unique goals and company scale.

8. AI yields immediate results

Too many businesses implement AI-based resources with the expectation that they can “set it and forget it.” Approaching AI in this manner is sure to lead to disappointment and, potentially, a significant loss in ROI. AI is complex and requires a significant time investment in order to properly work and produce any sort of meaningful result. No matter how sophisticated it is, an AI system is only as good as the training that it receives.

9. AI is for tech giants only

AI is just for big companies like Google and Amazon, right? Wrong. Whether a business is an enterprise or a sole proprietorship, if it uses and collects data from its customers, there’s a good chance that it could benefit from at least machine learning. With an in-depth analysis of consumer data, a company can gain better insight into customer behavior, identify new market segments and even improve social media and ad engagement rates.

10. AI is just a fad

It may be one of the most talked about topics of the 21st century (so far) but AI is a lot more than a passing fad. According to a report by PWC, 72% of business leaders survey identified AI as a “business advantage”. As business and consumer sentiment about this becomes increasingly positive, AI’s place in the modern world becomes ever-more assured—well into the foreseeable future.

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