Common Misconceptions of AI – and Why They Must Be Overcome

Many businesses are achieving real breakthroughs with AI, which are changing how they operate. At the same time, there are also some misconceptions on what AI can actually do. Here are some.
Common Misconceptions with Artificial Intelligence

Forbes magazine recently published a list of the most promising artificial intelligence companies in the United States. I recommend you read it. The list may open your eyes about some businesses flying under your radar screen. It also underscores how much AI is shaping the future of multiple industries ranging from healthcare to transportation. The article does something else, too: confronts misconceptions about AI. In a companion column, “AI 50 Founders Say This Is What People Get Wrong About Artificial Intelligence,” some of the executives from the profiled businesses speak out misconceptions that affect how people view AI more broadly across society.  

In my role at Pactera, I work with businesses to implement AI, and I talk to many more companies who are considering AI. Many businesses are achieving real breakthroughs with AI, which are changing how they operate. At the same time, I also encounter some misconceptions. Here are some.

Misconception 1: AI Is Autonomous

Sarjoun Skaff, CTO and cofounder of Bossa Nova Robotics, discusses how companies often forget that AI requires human intervention. He says, “AI is a very good pattern-matching tool. To make it work well, though, scientists need to understand the details of how it internally works and not treat it as an ‘intelligent’ black box. At the end of the day, making good use of great pattern matching still belongs to humans.” As we have shared on our blog, AI requires human intervention, for instance to train AI-powered machines to correct errors. 

Misconception 2: AI Is New

AI is not new. It has been around for several decades. AI algorithm and models have been well known for a while, I still remember the time when IBM’s Deep Blue chess computer beat  Garry Kasparov, the grandmaster of chess, back in 1996. Deep Blue versus Garry Kasparov triggered a wave of interest on AI. Nowadays, the new wave of AI mainly contributes to technology advances with hardware and computer power, which make a computer learn/evolve at the speed we can’t image.  The AI in specific areas such as chess and video game has reach the advanced level that human being can’t image and will not be able to catch.  (To computer program AlphaGo, even a well trained professional seems like an infant.)

But it’s important to make a distinction between AI – a machine’s ability to emulate human cognitive abilities such as problem solving – and artificial general intelligence (AGI), which is machines actually becoming as smart as people are in every respect, such as a robot walking into a random home and having to figure out how to make coffee on its own by reasoning where the all the necessary ingredients might be stored based on judgment and knowledge (this hypothetical scenario, developed by Apple cofounder Steve Wozniak, is known as the Coffee Test.)  AGI is in a childlike phase. AGI understands rules and logic, but AGI still needs human guidance to achieve complex scenarios. 

Misconception 3: AI Is Plug and Play

Another misunderstanding I encounter often is that AI is a technology that you can purchase and install. AI is not like a supply chain management software you can buy from a vendor and install. AI is actually a term for a complex set of data modeling and analysis software that requires (as noted) human intervention to develop and manage. 

As Algorithmia CEO Diego Oppenheimer told Forbes, “The systems you need to implement and manage machine learning in production are often much more complex than the algorithms themselves. You can’t throw models at a complex business problem and expect returned value. You need to build an ecosystem to manage those models and connect their intelligence to your applications.” 

Misconception 4: AI Will Steal Your Job and Take Over the World

But the biggest misconception is that AI is going to destroy jobs and upend companies, even societies. Frankly I see a lot of outright fear of AI, as if the machines from The Terminator are going to become self-aware and wreak havoc everywhere. But we are very far off from AI evolving into AGI, which assumes a higher level of intelligence, as discussed. And remember, The Terminator is a work of fiction.

As for AI itself: it is no different than any technology. Waves of technology typically free people from repetitive work they don’t want to do and open up new opportunities to develop skills, which is what IBM predicts with AI

The fact is, AI can improve the way people are trained, provide engineers with better data to help design new features and launch new products, and help physicians treat patients more effectively, among many other benefits. For an example, here’s a case study from our own website about how a leading insurance, banking, and financial services company in China used AI to improve training and reduce staff turnover.

Addressing the Misconceptions Around AI

In my view, we can address these and many other misconceptions through business-to-business education can set more realistic expectations, which is why we blog about AI at Pactera Edge. In addition, nothing succeeds like success. The more companies share how they are using AI to improve themselves, the more willing their peers will become to employ AI. 

Businesses like ours have a responsibility to advance the state of the art with AI. And businesses across the world have a responsibility to learn and adapt. AI is not going away. Overcoming misconceptions and learning is not only important, it’s also essential for your future growth. 

Advancing Our Understanding of AI

To help businesspeople overcome fear with knowledge, I’m going to do my part by blogging about AI. In a forthcoming series, I’ll tackle different aspects of AI, such as conversational AI, cognitive AI, the relationship between AI and blockchain, and how AI relates to robotic process automation. Stay tuned.

Pact.AI Can Help

With Pact.AI, Pactera provides a complete end-to-end portfolio of data science and data engineering services, AI application enablement, AI solution accelerators, advanced AI frameworks, and end-to-end delivery that will establish, elevate and enable your AI product vision. Pactera is helping clients in high tech, banking/financial services/insurance, telecom, retail, consumer packaged goods, manufacturing, and healthcare solve various business challenges with AI. Contact us to learn more.


About the author:

Yong Liang is Associate Vice President and Product Lead for AI related solutions at Pactera.  He works on several up and coming AI technologies that support enterprise business.