My uncle once claimed he could magically tell you the day of the week if you gave him any calendar date (day, month and year). He said he could visually see the answer in his head and swore he didn’t have any quick calculation or trick. My father was skeptical. He bet my uncle $100 that he could develop an algorithm to do the same.
The next day, my father produced a page of calculations that, lo and behold, would produce the correct answer. I was in awe; my uncle was not as impressed. But, my dad still won the money.
What Is AI?
Algorithms have been around for thousands of years and are an essential and critical element behind artificial intelligence (AI). Algorithms are structured, step-by-step instructions, and computers are excellent in using algorithms at exceptional speeds. Scientists discovered that computers are not only fast with completing the calculations, but that they can also “learn” from them.
This is what’s called “machine learning,” which is a subset of AI. People give the system a goal and provide feedback along the way — an error for wrong behavior and a reward for favorable outcomes. Through these reinforcement signals, the system is able to “learn” an optimal approach to achieve the desired goal.
Because computers have the ability to scan vast amounts of data, process calculations and assess probabilities at lightning speeds, machine learning is quickly proving to be an incredible advancement that will tremendously impact our lives.
How Can AI Improve Workplace Learning?
Workplace learning — the ongoing leadership and skills development that takes place within a company—could stand to greatly benefit and improve with the right applications of AI. Here are three key ways I predict AI and machine learning will positively impact the experience of employees as learners:
1. Personalized and More Effective Learning Experiences
For many years now, the learning industry has touted the advantages of a more personalized learning experience. Now, with AI, this can be realized. Supported by back-end machine learning delivered through speech recognition and more intelligent user interfaces, the learner can experience more adaptation and tailoring to their specific needs and preferences.
Computers can do the behind-the-scenes data analysis and provide real-time feedback during a training experience, modifying a course path based on progress and response. Tests and quizzes can adapt to the learner’s inputs and intelligently recommend a tailored curriculum path. The learner gets a more efficient and personalized experience. Imagine: No more sitting in a five-day class if all the learner needs is just a portion of it.
2. Training Reinforcement
Surprisingly, we still don’t do a great job in training reinforcement. Yet, reinforcing the learning after a training event is critical to learning retention. (See my article on effortful recall for more details.) This is where machine learning and AI can make tremendous strides where humans have fallen short.
We don’t take time to reinforce learning — but computers can do it for us! Already, intelligent apps and systems are popping up in the marketplace that offer this. Like reminding us to take our vitamins, intelligent systems can engage us and help reinforce training, helping make the learning “stick” and increasing overall learning effectiveness as a result.
3. Measuring Effectiveness and ROI
Organizations have also failed in the area of measurement. With AI, we will have no excuse. Intelligent systems will be able to easily and quickly scan large quantities of data and pull from multiple sources, not just online assessments and course surveys. By correlating on-the-job activity in different existing systems with training programs, and even by matching employee profiles to create “buddy systems” and mentorships, AI will be able to help us modify training programs based on success and failure points. This will continuously improve the learning experience, so employees and trainers can focus on learning that actually produces results.
Make More Time for Meaningful Connection
All of these potential advancements will free up time for a company’s team that handles learning and development to focus on human interactions with employee-learners and think of new innovations and ideas in learning. The best strategy: Determine where computers and systems can automate the tedious tasks and analytics, so the team can provide more valuable human interactions with learners.
The potential is not far from reach: Different systems and authoring tools are already working to incorporate elements of machine learning. In addition, IBM Watson, Google Cloud Platform, AWS and others are providing developers with the ability to leverage these technologies to develop AI apps and engines that can feed into existing learning and development systems.
As David Clark, a senior research scientist at MIT’s Computer Science and Artificial Intelligence Laboratory, says, “I like to consider [in using AI]…what problem needs a solution.” I believe making learning more personalized, reinforced and measured are three key “problems” or areas where machine learning, AI, and all the algorithms behind the two can make a huge impact in workplace learning. And, this would ultimately improve productivity and free up time and space for humans to focus on new ideas, innovations and each other.
My father would be proud of the advancements in AI and machine learning, and I know he would gladly hand over his algorithms to a computer. As a teacher himself, he’d say he preferred the human interactions over the time-consuming grading and tedious administrative tasks that kept him from focusing on new ideas and ways to inspire and teach.
I predict that AI won’t replace the teachers, but teachers who find ways to embrace AI will outlast, and be more effective and satisfied in their work, than those that don’t.