Top 10 Technology Trends of 2015 – #4 Smart Machines

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One of the more controversial and futuristic trends cited in Gartner’s top 10 technology trends for 2015 is the rise of smart machines.

What is a smart machine?  According to TechTarget, a smart machine is an intelligent device that uses machine-to-machine (M2M) technology, such as robots, self-driving cars and other cognitive computing systems that are able to make decisions and solve problems without human intervention.

Controversy around smart machines mainly lies in how rapidly they can attain human cognition and, once attained, how that will affect the workforce. Smart machines have been attempted for over 60 years. Recent advances in computing power, especially in the cloud, and the wide availability of data from the Internet have enabled ‘deep learning’, the ability for machines to learn complicated data.

Applications for smart machines cover a wide a variety of fields, such as:

  • Medical Analysis: Being able to distill a large amount of information allows machines to analyze the latest in medical research and provide a suggested course of treatment.
  • Customer Service: Increasingly, smart machines are able to answer questions about basic topics in natural language.
  • Reporting and Publicity: Distilling large amounts of financial information into a narrative report that informs decision-makers about a company’s financial performance and upcoming trends.

What binds all these examples together is a plethora of information that needs to be analyzed, indexed and regurgitated in a specific format. Due to their computing power, smart machines excel at these tasks.

So, will we see smart machines taking the place of humans?

The experts are split. Most hands-on experts and CIOs feel that replacing humans with smart machines is a far-off fantasy. They cite several hurdles:

  1. Lack of Decision-Making Capability: To be able to replace a worker, you have to reason like one. Smart machines are still not at the level of human cognition and probably won’t attain that status for quite a while. Although we have seen advances in current applications, they still need a human to make final decisions.
  2. The Scale of Effort: Building a complex smart machine actually requires a tremendous amount of effort. Training workers is still cheaper, with better results.

Instead, experts predict that smart machines will provide inspiration to solve new problems in new ways by analyzing data quickly and capturing trends that may have been missed. That intelligence within a certain task doesn’t translate to larger and more general intelligence, which is still the domain of humans.

However, other experts point to applications that present the opportunity for smart machines to process huge amounts of data to provide a human operator with the best scenarios. This application is already underway in call centers where CSRs can access company-wide expertise with a click of a mouse. Call processing is faster and more accurate, achieving a level of efficiency impossible without the pairing of smart machines and human operators. Similar decision support applications range from medical to financial implementations.

Do your product development, service offerings, or customer support processes in your organization require processing large amounts of data? How do you think a smart machine could help you?

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