Artificial Intelligence has been broadly defined as the science and engineering of making intelligent machines, especially intelligent computer programs (McCarthy, 2007). AI can use different techniques, including models based on statistical analysis of data, expert systems that primarily rely on if-then statements, and machine learning.

Machine Learning is an artificial intelligence technique that can be used to design and train software algorithms to learn from and act on data. Software developers can use machine learning to create an algorithm that is “locked” so that its function does not change, or “adaptive” so its behaviour can change over time based on new data.

Some real-world examples of artificial intelligence and machine learning technologies

– An imaging system that uses algorithms to give diagnostic information for skin cancer patients.
– A smart sensor device that estimates the probability of a heart attack.

How Are Artificial Intelligence and Machine Learning transforming the future of devices and technologies as we know it?

Artificial Intelligence (AI) and machine learning (ML) technologies have the potential to transform the Tech and Health Care industries by deriving new and important insights from the vast amount of data generated during the delivery of services every day. Tech Innovators and Medical device manufacturers are using these technologies to innovate their products to better assist end-users and health care providers and improve overall client experience.

One of the greatest benefits of AI/ML in software resides in its ability to learn from real-world use and experience, and its capability to improve its performance.

When reviewing AI capable systems and in order to determine the best applicable regulatory pathway, we look at the (5) most common types of AI

Interactive AI

– Chatbots
– Smart Personal Assistants

Functional AI

– IoT Solutions
– Robots

Analytic AI

– Sentiment Analysis
– Supplier Risk Assessment

Text AI

– Text Recognition
– Speech-To-Text Conversion

Visual AI

– Computer Vision
– Augmented Reality

Regulating the use of Artificial Intelligence (AI) and Machine Learning (ML) comes down to implementing and abiding by privacy laws. Ensuring that data extraction isn’t used to discriminate, invalidate, and put at risk the user’s private information:

– ISO 27000 Implementation
– PIPEDA Compliance
– Cybersecurity Assurance Planification (CAP)
– GDPR Compliance
– SOC 1, SOC 2 Compliance (when applicable)

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