Kathleen Drum explains some of the more commonly used phrases when discussing AI and why Assistants need to know them
Artificial intelligence (AI) has been slowly creeping into the way we do business, but when ChatGPT burst onto the scene, suddenly the terminology moved from the IT department to being used more widely across organisations.
We often talk about “futureproofing” your role as an Assistant and understanding key concepts and phrases around AI can do just that. Here are some you need to know:
Algorithm
An algorithm is a step-by-step set of instructions or rules followed by a computer to solve a specific problem or accomplish a task. Every time you use the “sort” function in Microsoft Excel to arrange your data in ascending or descending order, you are using an algorithm. Algorithms improve data organization and analysis capabilities.
Machine Learning
Machine learning focuses on enabling computers to “self-learn” from data and improve their performance over time, without being explicitly programmed. Algorithms create models that can analyse data, identify patterns, and make decisions based on those patterns. The system “learns” from its errors and improves on its own, based on experience.
A prime example of machine learning in action is in personalisation – think Amazon or Netflix. With Netflix, machine learning algorithms analyse your preferences, viewing history, and ratings to provide personalised recommendations and increase the ease of discovering new content. With Amazon, personalisation encourages increased or repeat buying by providing recommendations via the “You might also like” prompt, based on your past interactions with the site.
Deep Learning
Deep learning is a more advanced and specialized form of machine learning that is particularly effective at handling large and complex datasets.
Deep learning algorithms can be seen in action on your phone’s photo gallery. The software utilizes deep learning algorithms to automatically recognize and categorize objects, people, and scenes in the photos. This allows you to search for specific items or create albums based on content, making photo organization and retrieval easier.
Natural Language Processing
Natural Language Processing (NLP) focuses on enabling computers to understand, interpret, and generate human language by developing algorithms and models that analyse and extract meaning from text or speech. NLP allows machines to comprehend and respond to human language in a contextually relevant and meaningful way.
NLP is used in voice-to-text transcription tools, such as Microsoft Word’s dictation feature or virtual meeting transcribers such as Otter.ai. NLP techniques are also used by Alexa, Siri, and other devices to understand and process voice commands or queries from users.
Big Data
Big data is characterized by its three V’s: volume, velocity, and variety.
Supermarket chains are among the most obvious generators and collectors of big data. They can gain insights into customer behaviour, improve supply chain efficiency, and deliver targeted marketing campaigns. Big data analytics can also help identify and prevent fraud by detecting both anomalies and patterns.
Conclusion
Embracing this new language will enable you to:
- communicate more effectively with executives, stakeholders and colleagues
- grasp the potential and limitations of AI technologies for your organisation
- facilitate discussions around AI strategies and the training required
- make suggestions for seamless collaboration between human and AI systems
- position yourself as a proactive Assistant, working to enhance productivity and efficiency in the organisation
