How We Learn Through Machines

11:14 PM Kapil Kumar 0 Comments

Because of rapid advances in information technology, it’s likely that machine learning will affect how we work. Let's break this down to the nuts and bolts. According to H. James Wilson, Allan Alter, and Prashant Shukla's piece in the Harvard Business Review, "Powerful machine-learning algorithms that adapt through experience and evolve in intelligence with exposure to data are driving changes in businesses that would have been impossible to imagine just five years ago." They describe this trend as the current incarnation of the re-engineering movement of the 1990s. Now, companies use these algorithms to update their business models, essentially making strategic decisions based on consumer trends and other patterns. Look here.

The Significance of Machine Learning

This trend of businesses learning from artificial intelligence relates closely to how people will learn differently in 2016 and beyond. Today, we expect our knowledge workers to learn at a faster pace. We must make decisions based on many types of data, including trends from consumer-based software, in our daily work. We must learn at a faster pace than ever before. It’s understandable that, as modern knowledge workers, we often feel frustrated with this level of cognitive demand. We can only learn so quickly and adapt to our employer's changing expectations. We are not machines and do not run on predictable algorithms.

Finding the Happy Medium

The resulting dilemma for employers is how to maintain a culture of learning without overloading employees with information. Employers must support employee learning while recognizing we aren't machines. Organizations that pressure workers to increase their technical knowledge at a pace that's too demanding quickly reap the ramifications of that pressure. One way that organizations can improve employee learning is to continuously consider the impact of machine learning on how we work.

Towards the Right Model of Organizational Learning

Contemporary organizations often focus on how to build the right model for employees to learn. These organizations want to use machine learning as an option for securing a high ROI on training solutions. Building the right model for organizational learning must account for the ways that people learn in a knowledge economy. Organizations should build a learning model that truly benefits employees and enhances the workplace culture. This is especially challenging when many of an organization's workers telecommute or work in offices far from headquarters.

Choosing Information for Learning

One way that machine learning affects our work process is how we consume digital content. Many of us are accustomed to consulting certain sources of information on a regular basis, whether for professional or for personal use. Because we continuously view information through the perspectives found in these information sources, they can shape the direction of our thinking. Within each website, such as for business professionals, we consume trends and ideas on a topic of interest. Much of this content is already filtered, often according to the ways that we've searched for information in the past. The way that intelligent search features on our favorite websites choose content for us limits our understanding of any subject.

Moving Past Limited Perspectives

To become more knowledgeable on a topic in our industry, we don’t have to limit ourselves to machine learning. We can seek information that challenges our thinking as well as the facts and opinions expressed on our favorite websites. We can physically learn information from other professionals at industry events and conferences. We can search for new websites related to our profession. We can maintain email correspondence with our colleagues. We can ask their opinions on any topic before we finalize our own opinions. Machine learning is just one way to study a topic and provides a springboard for expanding our knowledge on that topic.

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