Through our program in Learning and Performance Technology, UMBC is committed to creating trained professionals who can help others learn in the workplace.
In today’s industry news, we’re focusing on the many ways learning helps to advance our society, from top development trends to machine learning.
Top 11 Learning & Development Trends to Watch in 2022
Like any field, practices in Learning and Development evolve over time. With the COVID-19 pandemic creating a global wave of eLearning, how we learn in the workplace is changing faster than ever. Within the recent digital transition, experts have been able to identify nearly a dozen trends with potential to spark significant development in the field, including personalized learning, gamification, AI, and much more.
Multi-generational Collaborations in Tech
How will older generations keep up with the constant technological advancements of the modern age? A new study suggests that their children, grandchildren, and other relatives may be the answer. The majority of 70-94 year olds cite their younger family members as their primary resources when it comes to learning new technologies, an interaction that not only facilitates family bonding, but helps elderly people retain their independence.
Reducing Bias in Machine Learning
When it comes to machine learning, English is overwhelmingly used when training AI technology. According to a recent study, this monolingual method can leave some gaps in knowledge. By only using English, trainers may be unintentionally omitting cultural phenomena that exist outside of English-speaking countries, decreasing the overall amount of information stored within the AI. In response, a team of researchers spanning across the globe is working to fix this problem through image technology.
AI Training On-Demand
Machine learning is an expensive and complicated process, often requiring companies to design and build their own infrastructure from scratch. However, a new pair of systems by Hewlett Packard Enterprise (HPE) plans to bring AI training systems to businesses who require it – no assembly necessary. The team hopes to make AI more accessible and less expensive, as well as collaborating with their clients to create a decentralized database of information.