Artificial Intelligence in Brief, Vol. 1:  What is it?  What is it for?

Artificial intelligence (AI) is seemingly everywhere these days, and discussions abound about how it will impact individuals’ daily lives as well as businesses from an operational and compliance perspective. In this series, Artificial Intelligence in Brief, the McDonald Hopkins Data Privacy and Cybersecurity Team will be providing the most current information and developments on AI.

To begin the conversation, we present an overview of what AI is and how it can be leveraged.

What Is artificial intelligence?

Artificial intelligence involves creating computer systems capable of a degree of human-like intelligence, such as learning from data, understanding language, and making decisions. AI analyzes data, finds patterns, and then uses patterns to make predictions. Common uses include natural language processing, image and speech recognition, automation, recommendation systems and healthcare diagnostics. New industries and applications for AI are created frequently. Properly implemented, AI can enhance efficiency and decision-making across diverse industries. At the same time, AI is resource-intensive, inflexible and may pose significant data privacy-related challenges.

What is AI used for?

The use of AI is growing as people and companies find new ways to use it to maximize profits, improve efficiency and perform numerous other tasks. AI is increasingly common in many fields including autonomous vehicles, advertising and cybersecurity, and is growing in popularity across other industries. For example, common uses of artificial intelligence in a professional or traditionally white-collar context include:

1. Machine learning applications - AI algorithms enable computers to learn from data, make predictions, and improve performance over time. This is widely used in predictive analytics, data mining, and pattern recognition.
2. Image and speech recognition - AI systems can analyze and recognize patterns in images and speech. This is utilized in facial recognition technology, voice-activated assistants, and medical image analysis.
3. Automation and robotics - AI-driven automation is employed to streamline processes in various industries, ranging from manufacturing to customer service. Robotics with AI capabilities are used for tasks such as assembly, packaging, and logistics.

Due to the explosive growth in and awareness of AI in recent years,  many commonly available programs and resources use AI. These include major programs like:

1. TensorFlow - An open-source machine learning framework developed by Google, which may be used for building and training deep learning models.
2. IBM Watson - A suite of AI services, tools, and applications offered by IBM, including natural language processing, machine learning, and computer vision.
3. Microsoft Azure Cognitive Services - A set of cloud-based APIs and services from Microsoft, offering capabilities including so-called ‘computer vision’, speech recognition, and language understanding.

Other as less-known, more specialized tools that use AI include:

1. Prophet - An open-source forecasting tool designed for analyzing time series data and making predictions.
2. Rasa - An open-source conversational AI platform that enables the development of chatbots and virtual assistants with natural language understanding and dialogue management capabilities.
3. DeepChem - An open-source library for deep learning in chemistry, which may facilitate the development of machine learning models for drug discovery and molecular design.

Human judgment and oversight remain an essential component for good AI. An AI is nothing without good data sets, which must be scrutinized and evaluated by people, particularly early in the training period for an AI, to ensure an AI is ‘learning’ correctly. As the volume of AI-generated data rises, to potentially incredible levels, good judgment as to what data is worthwhile training material will only grow more important.

Beyond the technical realm, the intangible ‘human element’ will always carry weight. For example, the ubiquitous ChatGPT was created by OpenAI, a company helmed by AI pioneer and CEO Sam Altman. Then in late November 2023, Altman was removed suddenly. Microsoft immediately began courting Altman, while a large portion of the OpenAI staff threatened to leave in solidarity. The future of ChatGPT, one of the darlings of the AI boom, was in doubt until Altman rejoined a mere five days later, underscoring how vital the people involved in AI remain.

In our next installments of Artificial Intelligence in Brief, we will address industry-specific concerns from both a business operations perspective and the ever-evolving legal dynamic.

The potential for AI remains tremendous and full of opportunities. If you have questions about how AI can enhance your cybersecurity posture, want to know how to prepare yourself for new privacy requirements, or think you might have experienced a cybersecurity incident, contact a member of McDonald Hopkins' national cybersecurity and data privacy team.