Demystifying AI in the Workplace: 6 Key Disciplines and Their Real-World Applications

It seems as though AI has a negative reputation many workplaces. A recent survey suggests nearly 50 percent of Albertans age 18 to 64 feel AI will replace more jobs than it will create. Just 16 percent believe AI is a net job-creator, while a fairly large proportion (27 per cent) are on the fence.

Getting to know how businesses are using (or planning to use) AI can help calm employee fears and move your workforce towards embracing the change that AI enables. Peter Breuer, a senior partner at McKinsey & Company says, “Transformation is 50 percent about AI and 50 percent about [changing employees mind-sets]. The second 50 percent, in many cases, is forgotten because everybody’s so excited about computers and robots.”.

To help your organization better understand,  here are the 6 major disciplines of AI and some examples to get you familiar:

1. Knowledge Reasoning: This is all about representing information in a way that a computer understands so it can make associations and apply ‘reason’ to questions.

Example: When you type ‘Mona Lisa’ into Google the search engine can then, using knowledge reasoning, associate this search with other facts about the Mona Lisa. Things like who painted it, its significance, etc.

2. Planning: The program is given a starting state, what the goal is, and possible strategies to get to the goal. Many very technical computing techniques and algorithms are then applied, leading to a sequence of actions from the start to the goal.

Example: This is  one AI discipline that autonomous vehicles use to drive from point A to B. They are given a start state, potential sequence of braking, accelerating, steering, and the end goal is to safely arrive at a destination.

3. Machine Learning: Instead of having humans create and implement the computer code needed to run the algorithms, the computer is given data and constructs outcomes and outputs from this data.

Example: The most famous example of this is Deep Blue. This was a system designed by IBM which defeated the Chess World Champion Gary Kasporov. It was fed large sequences of moves in prior chess games and used this data to predict the next best move.

4. Computer Vision: Uses large datasets of images to become familiar with the positioning of the pixels (the small squares of color in images on a screen). The computer can then identify what an object is, as well as where an object is in an image.

Example: Computer vision is used in Google Photos to help identify your friends and family (which is also kind of creepy. We’ll get into ethics later…).

5. Robotics: This is the combination of hardware (physical metal parts) and any AI process to bring the computers cognitive function to the real world.

Example: Watch this video from Boston Dynamics to see some of their robots at work.

6. Natural Language Processing: Similar to computer vision, this also uses large datasets of text to help predict the next letter, word, or phrase in a conversation.

Example: This has many applications such as chatbots and suggesting what word you are most likely to be typing next.

Aligning employees to any new corporate initiative is a key component to this process.This alignment is even more important when it comes to something as revolutionary as AI. By understanding the basics of the 6 disciplines you can get a head start in engaging your employees and making them allies in the organization’s change.

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