Digital Sensei: AI for Personalized Learning
Finally, a teacher that won’t get mad even if you ask the same question a hundred times. Literally.
Hurtling through a wave of continuous technological advances, the world is currently witnessing the unfolding of the fifth industrial revolution (5IR) while being on the cusp of a sixth one.
The impact of the fifth industrial revolution is marked by the rise in the popularity of such complex concepts as artificial intelligence (AI), machine learning (ML), quantum computing, cloud computing, Internet of Things (IoT). The fifth industrial revolution is also about the systematic and sustainable usage of these technologies.
Finding its basis in the possibility of mutually beneficial human-machine relationships, the broad focus of the 5IR is on the well-being of all stakeholders involved, including corporations, employees, customers, consumers, along with society at large.
Unlike the fourth industrial revolution that predominantly focused on competition and eliminating the human element from many industrial processes to increase efficiency, the fifth industrial revolution prioritizes a collaborative effort between humans and technology.
The vision of 5IR is to encourage a synergistic interaction between machines and humans where the strengths of both parties may be exploited while the weaknesses are simultaneously compensated.
For human resources professionals and departments worldwide, the implications have been profound, with elements of digitalization having seeped through all the domains that comprise human resource development and management.
Every day new forms of technology are emerging that are modifying the ways tasks are performed at work, with the fifth industrial revolution defining the manner in which people grow, learn, interact, and perform.
The fifth industrial revolution has impacted all existing industries and sectors globally. In the education and learning domain, too, the impact of 5IR has been far-reaching.
In recent years, a growing body of literature has focused on artificial intelligence, one of the key elements of the current, ongoing technological advancement.
While the research on the application of AI for learning and education, especially at the workplace, is scarce as yet, a few studies have formed the ground by providing nascent insights into the possibility of AI-driven tools and technologies providing learning and educational opportunities for people at work. Moreover, the content delivered by AI-based technologies is highly learner-centric, personalized, and can be accessed on-demand.
Quite a few corporations have already started incorporating and delivering AI-based learning content to their employees, including Air Methods, Baidu, and International Business Machines [IBM], to name a few.
While not a huge number of companies currently provide AI-driven training and education to their employees, a number of corporations have emerged that are rendering AI-driven learning content to their customers by identifying their pain points and tackling them through personalized modules that are delivered on-demand.
The success of such firms as LinkedIn Learning, Cornerstone OnDemand, Degreed, and Eightfold, to name a few, attests to the significance of on-demand, personalized learning content in the current world where unpredictability and skill redundancy have combined to form the zeitgeist of the century.
Current State of AI-based Technologies at Work
Artificial Intelligence is rapidly gaining popularity in today’s technologically advancing world. The ability of AI to learn from data it collects and provide results based on that data is gathering interest from corporations.
Organizations are keen to adopt AI and ML-based software to determine if these technologies could help reduce operating costs, amplify profits, and boost organizational efficiency.
Corporations all over the globe are experiencing a digital evolution. However, there is growing apprehensiveness among employees about this digital transformation, and a major portion of the employees is averse to this change.
This aversion can be attributed to the uncertainty regarding job security, suspicions regarding the capabilities of AI-powered software, and concerns regarding data privacy. As such, it has been accepted that this digital revolution will be a slow process as employees adapt to this change.
The benefits of adopting AI-based applications are undeniable. AI has found to not only reduce redundancy by automating certain tasks but has also been found to improve customer satisfaction rates.
In the hospitality industry, for example, AI is being used to assist customers with self-service and bill payment. Large multinational organizations such as Hilton Hotels have been employing AI to provide necessary information to customers.
Focusing on the current research, however, a number of studies show that employees fear losing their jobs because of the incoming of AI-based technology, and this finding holds true across industries and sectors such as healthcare, banking IT, hospitality, etc.
Moreover, these fears are not unfounded. A study by Oxford University has estimated that nearly 47% of the jobs are expected to be taken over by AI-based software and humanoids by 2033. Considering an industry-wise breakdown, 40% of jobs in the hospitality industry, 4% jobs in healthcare, and 57% jobs in manufacturing are likely to be delegated to AI. For the finance industry, 30% of the banking jobs expected to become automated.
However, their are contradictions in the industry. A research study by McKinsey reports that less than 5% of jobs would become completely automated. Moreover, it is expected that AI would only take over monotonous, low-level occupations, whereas jobs that require a high level of expertise would only be augmented by AI and ML.
Nonetheless, the attitudes that employees possess regarding AI are going to be a defining factor in its adoption. Although negative attitudes toward AI are prevalent, positive attitudes exist as well.
Research has shown that employees are more accepting of AI-based applications if they perceive it to be beneficial or if they perceive it to bring about a boost in their performance. Amazon’s Alexa and Apple’s Siri have people much enthused about the prospect of AI.
The attitudes of employees can be looked through the lens of the technology acceptance model. The model proposes that a number of factors such as the perceived usability of an application influences people’s attitudes towards it.
If the employees feel that the application is easy to learn and use, they are less likely to have negative attitudes toward it. However, poor experience with the application can exacerbate existing negative attitudes.
Another key factor is autonomy. If the employees perceive that they have free will while adopting new technologies, there is a higher likelihood of them having a positive attitude toward it.
There is also a sense of mistrust regarding external technology, and a growing field of research is dedicated to it. A major portion of the employees also prefers to interact with a human instead of a machine, with the focus being on empathy and emotional intelligence, as demonstrated by the desire to converse with a human instead of a machine on the phone. However, these attitudes are quick to flip as people would prefer to have a machine talk on their behalf while receiving a call.
AI for Workplace Learning
Unpredictability is the zeitgeist of the twenty-first century. The markets and the business world are becoming increasingly dominated by the elements of the VUCA world. VUCA, an acronym, stands for volatility, uncertainty, complexity, and ambiguity. The VUCA elements require all aspects of an organization to be highly adaptable, swift, and flexible.
The Human Resources personnel have a chief role in assisting organizations in adapting to the current VUCA world. They need to be involved in a lot of self-directed learning, initiate the acquisition of new skills for themselves as well as others in the organization.
However, traditional methods of classroom training that are currently prevalent in corporations are not suitable for keeping with the constant changes that the corporate world is subject to.
Considering the fact that classroom training requires setting aside time by both the ;earner and the instructor, is unable to account for the individual differences of all learners, and may not be up-to-date with the ongoing trends, it cannot provide the competitive advantage a company requires to win the talent war that is continuously being waged in the corporate world.
As such, AI-based technologies which have the capacity to identify the skills that a particular employee or a set of employees need, deliver personalized, on-demand, highly engaging, and microlearning content is much more effective, time and cost-minimizing than traditional classroom training methods.
Further, psychological theories have provided bases for the applicability of artificial intelligence in workplace learning. For instance, Metacognitive theory posits that learners learn better when they are aware of how they learn, what concepts are naturally easy for them to grasp and what areas need special attention.
Engaging in metacognition-based learning involves brainstorming and specifying strategies to enhance learning. As AI is capable of analyzing a large amount of data in a very short span of time, it can determine the areas where the learner needs to put in more effort, highlight these areas to the learner, and customize the learning material in such a way that the learner’s weak areas become the focal point.
A number of corporations in a myriad of industries are incorporating AI-based applications into their training and development programs. These firms range from big, multinational organizations to startups in the initial stages of development.
When it comes to customer-centric programs, a number of ed-tech firms are providing AI-based learning content. For instance, LinkedIn Learning has taken a central position by utilizing AI to identify the learners’ pain points, determine the methods that are expected to be most effective, and then finally implement neural networks to provide the precise micro-learning that is required.
Other companies that are providing a similar sort of learning content include Cornerstone, Eightfold, SeekOut, and Degreed.
SeekOut, for instance, allows the upper management or learning agents to get a microscopic view of the specific skill set of the employees, group them together based on their skills, and then analyze the groups to understand the training requirements. SeekOut has been a pioneer in establishing team-based assessments. Similarly, Uplimit, an ed-tech startup providing technical courses, has used AI to build virtual training aides to facilitate learning for its users.
Companies with employee-centric training programs include IBM, Baidu, and Air Methods, to name a few. Out of these companies, IBM has been the most successful in the utilization of AI-based applications for employee education as covered by the Massachusetts Institute of Technology [MIT] in a recent study. By investigating the learning systems present in IBM from 2014 to 2019, the research scientists at MIT found how the learning methods followed at IBM affected the employees’ job performance and career prospects.
The learning systems at IBM are accentuated by a multitude of technologies, including cloud computing, artificial intelligence, and augmented reality. Specifically, AI chatbots are used to answer any questions or doubts users may have about the learning material, provide specialized recommendations to employees on what courses to take next, and use AI to segregate and tag the learning content available on IBM’s platform Your Learning.
Another previously impossible achievement is the real-time diagnosis of issues emerging on the platform and the implementation of their solution. IBM uses AI to identify problems by analyzing thousands of comments in real time, and the solution is implemented immediately.
Future Scope
The future scope of research in the realm of artificial intelligence (AI)-based personalized workplace learning is extensive and holds significant potential for addressing critical aspects of employee development and organizational dynamics. First and foremost, there is a need to delve into the impact of AI-driven learning on job satisfaction and retention rates, exploring whether the personalized and on-demand nature of such training contributes to a more content and engaged workforce.
Ethical considerations in the implementation of AI, encompassing privacy, bias, and transparency, warrant thorough investigation to ensure the responsible integration of these technologies into workplace learning. Examining the adaptability of employees to AI-based training and its correlation with skill development is crucial for understanding the long-term effects on workforce capabilities. Furthermore, research should explore how the adoption of AI in workplace learning influences overall organizational performance and whether it translates into a competitive advantage for companies in the market.
And that is it for the latest edition of The Channel. Hopefully you gained something out of this article. Let me know your thoughts in the comments below!
Until next time,