Artificial Intelligence (AI) and machine learning (ML) algorithms have grown extremely fast in the past decades. We hear about their great performance on the news, and social media is full of endless discussion about their risks and benefits. They are part of our daily life, whether we use maps to calculate the fastest way to work, stream videos or music, or perform simple searches using our favorite browser. AI and ML have also a key role in helping humans to understand and (hopefully) solve extremely complex problems, processing huge amounts of data that would be otherwise impossible.
Given the high impact these models have in our life, it is also important to understand a little about how they work, and what the theory is behind them. We do not need to become experts in the field, but understanding how they work can enable more efficient and secure usage of the tools.
Artificial Intelligence is a quite broad field generally referring to models and algorithms that try to solve problems in a rational, logical way. Machine Learning can be seen as a subset of AI, where computers are able to learn and improve their accuracy from data. Both AI and ML are built on the backbone of Mathematics and Computer Science.
What is important to understand here is that the fast and accurate solutions provided by AI and ML come from centuries of human knowledge. Evolution of science and technologies brought us to this stage. Humans are creating the algorithms. And humans are selecting what type of data to use to train the models. Human knowledge can drastically reduce the size of the data needed to train the model, improve its accuracy by using the proper equations or logic, and make it easier to identify and fix faults in the system.
We may feel overwhelmed and frightened by computers controlling everything around us, but ultimately we have control of what we give as input, of how we use it, and how we interpret the outcomes. We are the ones using and controlling the machines, and we need to have a good knowledge of what we are doing to make the most effective and secure usage of technologies.
At Praxis Security Labs, we focus on making sense of the human factors that pertain to security. Being able to combine subject matter expertise, or human knowledge, with smart tools like AI and ML is a key element to making sense of the large amount of User Behavior Data available. Being able to apply human knowledge to our algorithms and analysis makes it possible to identify patterns that can be used to improve the security posture of our customers. When it comes to AI and ML, it is not a question of if we should use it, but instead a question of how to make the most sense of it.
Praxis can help you in understanding how people, process and technology can work together to create a more effective organization. Get a free and personalized Security Efficiency Report from Praxis Security Labs to learn more!
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