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Last month the New York Times published an article titled “The Great A.I. Awakening” that detailed how machine learning is changing technology. As AI becomes more powerful, not only will it change how computers function, it will also have a profound impact on society. To learn more about how AI will change the world, take a look at four of the top 2017 AI trends.

More Access to AI Tools

Research shows that while many organizations are interested in using AI, only a fraction of them have incorporated AI into their businesses. However, there are a number of frameworks that are making it easier to adopt AI. Two examples are Facebook’s and Howdy’s Slack bot. Both frameworks make it relatively easy for developers to create conversation applications. This type of technology is great for customer service applications like chatbots. (Learn more about chatbots by visiting

Specific AI

For the moment, AI will continue to target specific systems. In 2017 expect to see AI become even more specific with the systems it targets. For example, AI will be applied to robotics, self-driving cars, personal bots (such as Amazon Echo), and specific industries. The finance and health industries, in particular, stand to benefit from AI systems. AI can be used to analyze trading patterns or even point out anomalies in MRI images.

Serious Discussion of AI’s Impact

Science fiction has popularized the idea of AI as a potentially malevolent technology that will end up destroying humans. The reality is a lot less sensational. This year more experts will begin to seriously discuss how AI will impact the economy. While it’s true that AI has the potential to eliminate a significant number of jobs, there needs to be more discussion about what that will actually look like.

Fundamental AI Problems May Be Solved

There are a number of issues that AI technology needs to solve in order for it to become as powerful as most technology professionals expect it to be. Here are some of the issues that researchers will tackle in 2017:

  • AI researchers will continue to learn about natural language and how to implement it into AI systems.
  • More systems that reflect the properties of the human mind will be developed. This means incorporating things like psychology and causality into AI technology.
  • Further research will be done on systems that require less labeled data. Most AI systems require large amounts of data in order to recognize patterns. Last year, however, Google’s DeepMind developed technology that could view a single object and begin to recognize it immediately. In 2017, researchers will further develop this breakthrough.