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GUEST ESSAY: A primer on why AI could be your company’s cybersecurity secret weapon in 2022

Artificial intelligence (AI) is woven into the fabric of today’s business world.

However, business model integration of AI is in its infancy and smaller companies often lack the resources to leverage AI.

Related: Deploying human security sensors

Even so, AI is useful across a wide spectrum of industries. There already are many human work models augmented by AI. Understanding the established models before integrating AI is critical. For instance, here are a few common algorithm models that use data sets to detect patterns and make conclusions.

Linear regression. Using supervised learning, this finds relationships between input and output variables; for example a person’s weight based on known height.

Logistic regression. This is a statistical model for predicting the class of dependent variables from a set of given independent variables.

Linear discriminant analysis.  LDA commonly gets used when two or more classes have to be differentiated; it is especially useful in the field of medicine and computer vision.

Deep Neural Networks.  This refers to an Artificial Neural Network featuring many layers between the input and output strata; often used in image and speech recognition.

Naive Bayes. This is based on the Bayes Theorem and is commonly used for test classification, including multiple-class and binary classifications.

Decision Trees. Simple and effective, DTs divide data into smaller portions. DTs are applicable to regression and classification problems.

•Support Vector Machines (SVM): SVMs are excellent for limited data analysis. They’re faster than many newer models and best utilized for text classification problems.

Gurtu

Many companies are using AI to automate a variety of processes. The companies deploying AI in order to free-up their employees are reaping short-term productivity gains. While firms that have managed to develop a synergy between AI contributions and human contributions are experiencing significant performance improvement.

With collaborative intelligence, AI and humans can enhance each other’s strengths and bolster weaknesses in areas like leadership, teamwork, social skills, speed, scalability, creativity, and quantitative capabilities.

However, before that happens, it’s important to understand how humans can effectively augment AI — and how to redesign business operations to back up the collaborations. Below are areas that can help develop that interaction:

•Human assisting machines. It’s necessary for employees to train machines to perform tasks. Humans are needed to explain the outcome of tasks and maintain the responsible use of machines. This will get the best use from the machines, even when results are controversial or counterintuitive.

•Machines assisting humans. Conversely machines need to assist humans in expanding their capacities. AI can help amplify human cognitive strengths and interactions with customers and employees,  freeing humans from higher-level duties. AI needs to embody human skills to help extend employees’ physical capabilities.

•Checks and balances. The World Economic Forum (WF) suggests a holistic approach to implement ethics into AI usage. Three recommended approaches: The bottom-up approach, top-down approach, and dogmatic approach.

Bottom-up has machines learning how to make ethical decisions by observing human behavior. Top-down means the ethical approach is programmed into AI machines. Thereafter, AI can react when situations require making ethical decisions. The dogmatic approach involves programming  specific ethical schools of thought.

Knowing the above you can get started with the integration in a couple of key areas that can transform your business operations. The first is customer experience. AI can help to n enable highly personalized customer experiences –by ingesting and collating various customer data to drive customer behavior. Salesforce reports 50 percent of customers are likely to change brand if you fail to anticipate their needs. AI helps avoid that by providing timely, relevant information and marketing prescriptions.

The second area has to do with the cybersecurity talent shortage. AI digital assistants can help alleviate cybersecurity practitioners’ burnout and positively impact skill shortage and retention issues. Digital cybersecurity analysts, a new concept, can help practitioners enhance skills, improve decision making, and automate processes.

In fact, AI’s potential to enhance employee engagement and retention, across the board, is quite enormous. Sentiment analysis systems, for instance, can help companies better understand employee engagement and get insights into what drives employee behavior.

In short, AI is emerging as a  secret weapon considering its wide-ranging application. However, it’s necessary to apply the right and most effective model for your business to get the best value. Reports have shown that augmenting human action with AI is the most beneficial utilization for businesses. It’s advisable to create a beneficial synergy between employees and machines to achieve productivity gains.

About the essayist: Anurag Gurtu, CPO of StrikeReady, a California-based supplier of a cloud-based security operations and management platform that empowers and augments cybersecurity teams with institutional knowledge and automation.

*** This is a Security Bloggers Network syndicated blog from The Last Watchdog authored by bacohido. Read the original post at: https://www.lastwatchdog.com/guest-essay-a-primer-on-why-ai-could-be-your-companys-cybersecurity-secret-weapon-in-2022/