The Pros and Cons of Implementing Deep-Learning AI

The International Data Corporation (IDC) predicts that the compound annual growth rate (CAGR) for global sending via artificial intelligence (AI) will be 50.1%, reaching $57.6 billion by 2021. And the three most in-demand AI-related skills are currently machine learning, deep learning, and natural language processing. Additionally, the deep learning market, which is a subset of machine learning and AI, is expected to exceed $18 billion by 2024 alone, growing at a CAGR of 42%.


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So, ready or not, it’s time to understand deep-learning AI and how to implement it.

What Is Deep Learning and How Does It Work?

Deep learning is a subset of machine learning that relies on neural networks that are modeled on the intricacies of the human brain and how it operates; it entails thousands and thousands of interconnected processing nodes.
Deep learning allows systems to process, handle, and learn large amounts of data—it’s when a large amount of data is given to a massive neural net with many layers within and across computer systems and platforms.
It’s currently being used the most in business intelligence systems and predictive analytics, as well as in more sophisticated learning management systems (LMS). And it is still very much in the “experimental” phase, although this is anticipated to change rapidly.

Benefits of Deep Learning for Workplace Learning

LMSs that rely on deep learning allow predictions, algorithms, data, and analytics to come together to create more personalized e-learning experiences. E-learning content will continue to become more personalized with deep-learning AI, and it will become more engaging. And it will be delivered in a timelier fashion and in the right context, for each learner across your organization.
As a result, learners will be more motivated to learn and more engaged at work and will remember more of what they learn because they’ll never encounter material that’s not useful to them or their career trajectories. In addition, e-learning courses and programs will yield much higher return on investments (ROIs) overall for your organization.

Drawbacks of Using Deep Learning AI

First, it’s important to recognize that while deep-learning AI technology will allow for more sophisticated and efficient LMS, it still requires humans to initiate it and monitor it. (Read Understanding the Limitations of AI for L&D Professionals for more details.)
Additionally, AI systems that rely on deep learning can actually inherit and perpetuate covert and overt biases. And deep-learning AI can be pretty pricey at the moment, although costs are anticipated to decrease as demand for the technology increases.
In tomorrow’s post, we’ll cover more information about how you can implement deep-learning AI, as well as a few upcoming trends.