Artificial Intelligence to Boost Productivity
Artificial Intelligence (AI) technology can sense the environment, comprehend what’s happening, and take action. A 2016 Accenture report studied 12 countries and estimated that AI could provide a 40% increase in productivity by 2035. Shown in the graph below, the Accenture & Frontier Economics forecasted that the employment of AI could lead to a jump in U.S. economic growth from 2.6% to 4.6% during that time. In an article from CNBC, Accenture’s CTO Paul Daugherty is quoted saying that AI, “frees up employees to do things that they get more satisfaction out of, which is solving more complex problems, and dealing with the more complex issues that arise in business.” However, critics of AI, cite many potential drawbacks of employing the technology. The same CNBC article also quotes a Forrester report that forecasts 6% of jobs in the U.S. will be cut due to AI technologies in the next five years. That’s well over 7 million jobs at risk.
Uses of AI
Experts believe we do not yet know all of the possible uses for Artificial Intelligence. However, AI is already being used daily in the following ways, and further advancements are coming fast:
- Natural Language Generation: Siri, Cortana, and Google Assistant use speech recognition technology and are currently being used daily by hundreds of millions of people across the globe. Baidu’s Chief Scientist Andrew Ng says that “we’ve seen about 100% year-to-year growth in the daily active use of speech recognition across our assets.” Natural language generation is a slightly different concept, wherein machines produce text from computer data. This technology will transform customer service and report-generating tasks. One example of this application is when a service called Attivio returns search results for New Jersey when the user types “NJ.”
- Virtual Agents: You’ve probably seen the Amazon Alexa commercials where someone can ask the machine a question or to perform a simple task. Alexa is already assisting consumers with small requests. Mark Zuckerberg spent 2016 learning more about AI for himself, creating his own in-home Agent that he called “Jarvis.” In his summary, he highlighted that while it is exciting to think of the possibilities that could come with an in-home virtual agent, further development is needed before it is fully commercialized.
- Deep Learning Platforms: Intel’s website notes that “as a scientific community, we are just beginning to understand the potential of machine learning.” This area of AI would lead to machines that learn based on experience, solving problems for humans as they take in large sets of data. This is applicable in Carnegie Mellon University’s Libratus, an AI poker player that can pick up on human poker players’ strategies.
- Biometrics: This technology will allow machines to better understand humans by helping them read body language and better understand speech and images. This could be applicable in market research as well as security.
- Robotic Process Automation: This technology automates simple human actions, helping free up humans to do more complex jobs. Machines will complete repetitive tasks in a more efficient and cost-effective manner.
- Text Analytics and Natural Language Processing: Sometimes when humans speak, there is an inexplicit meaning or intent to their sentence structure and delivery. These analytics will allow for better understanding of speech through machine learning and statistics.
Still So Much to Learn
Artificial Intelligence is being discussed as the next Industrial Revolution. Experts believe hundreds of daily tasks, whether business or personal, will be altered by the development of AI. However, there is still much to learn as many business leaders are still unsure how it will affect their industry. Forrester’s 2016 survey found that 39% of business respondents are not sure what AI would be used for and 29% think they need to invest in data management systems first, in preparation for a possible application.
Although some business executives may be unclear about AI, the reality is that companies like Google, Microsoft, Facebook, Amazon and many others are refining the technology at rapid speed. This focused development will lead to a simplification of tasks, displacement of employees, and advancement of science.