With AI, we can build solutions that seemed like science fiction a short time ago;
enabling incredible advances in health care, financial management,
environmental protection, and other areas to make a better world for everyone.
Learning objectives
In this module, you'll learn about the kinds of solution AI can make possible and
considerations for responsible AI practices.
Introduction to AI
AI enables us to build amazing software that can improve health care, enable
people to overcome physical disadvantages, empower smart infrastructure, create
incredible entertainment experiences, and even save the planet!
What is AI?
Simply put, AI is the creation of software that imitates human behaviors and capabilities. Key
workloads include:
Machine learning - This is often the foundation for an AI system, and is the way we
"teach" a computer model to make prediction and draw conclusions from data. Anomaly detection - The capability to automatically detect errors or unusual activity in
a system. Computer vision - The capability of software to interpret the world visually through
cameras, video, and images. Natural language processing - The capability for a computer to interpret written or
spoken language, and respond in kind. Knowledge mining - The capability to extract information from large volumes of often
unstructured data to create a searchable knowledge store.
Understand machine learning
Machine Learning is the foundation for most AI solutions. Let's start by looking at a real-world example of how machine learning can be used to solve a
difficult problem. Sustainable farming techniques are essential to maximize food production while protecting a
fragile environment. The Yield, an agricultural technology company based in Australia, uses
sensors, data and machine learning to help farmers make informed decisions related to weather,
soil and plant conditions.
Anomaly detection in Microsoft Azure
In Microsoft Azure, the Anomaly Detector service provides an application programming
interface (API) that developers can use to create anomaly detection solutions.
Understand computer vision
Computer Vision is an area of AI that deals with visual processing. Let's explore some of the
possibilities that computer vision brings.
The Seeing AI app is a great example of the power of computer vision. Designed for the blind
and low vision community, the Seeing AI app harnesses the power of AI to open up the visual
world and describe nearby people, text and objects.
Understand Responsible AI
At Microsoft, AI software development is guided by a set of six principles, designed to ensure
that AI applications provide amazing solutions to difficult problems without any unintended
negative consequences.
Fairness
AI systems should treat all people fairly. For example, suppose you create a machine learning
model to support a loan approval application for a bank. The model should predict whether the
loan should be approved or denied without bias. This bias could be based on gender, ethnicity,
or other factors that result in an unfair advantage or disadvantage to specific groups of
applicants.
Azure Machine Learning includes the capability to interpret models and quantify the extent to
which each feature of the data influences the model's prediction. This capability helps data
scientists and developers identify and mitigate bias in the model.
Reliability and safety
AI systems should perform reliably and safely. For example, consider an AI-based software
system for an autonomous vehicle; or a machine learning model that diagnoses patient
symptoms and recommends prescriptions. Unreliability in these kinds of systems can result in
substantial risk to human life.
AI-based software application development must be subjected to rigorous testing and
deployment management processes to ensure that they work as expected before release.
Privacy and security
AI systems should be secure and respect privacy. The machine learning models on which AI
systems are based rely on large volumes of data, which may contain personal details that must
be kept private. Even after the models are trained and the system is in production, privacy and
security need to be considered. As the system uses new data to make predictions or take action,
both the data and decisions made from the data may be subject to privacy or security concerns.
Knowledge check
1. You want to create a model to predict sales of ice cream based on historic data that includes
daily ice cream sales totals and weather measurements. Which Azure service should you use?
Azure Machine Learning Azure Bot Language
2. You are designing an AI application that uses images to detect cracks in car windshields and
warn drivers when a windshield should be repaired or replaced. What AI workload is
described?
Computer Vision Anomaly Detection Natural Language Processing
3. A predictive app provides audio output for visually impaired users. Which principle of
Responsible AI is reflected here?
Transparency Inclusiveness Fairness
Summary
Artificial Intelligence enables the creation of powerful solutions to many kinds of problems.
AI systems can exhibit human characteristics to analyze the world around them, make
predictions or inferences, and act on them in ways that we could only imagine a short time ago.
With this power, comes responsibility. As developers of AI solutions, we must apply principles
that ensure that everyone benefits from AI without disadvantaging any individual or section of
society.
