MAY 2024CIOAPPLICATIONS.COM 19Raymond Kentbe able to recall them for comparative analysis against new variables within a given situation thereby improving the rate of response and accuracy of outcomes. This improvement, coupled with human training, can even better analyze specific activities weeding out false positives or negatives giving the security team the best opportunity to make the final judgement call.Not all is sunshine and roses either, as bad actors are also harnessing the power of AI for their own benefits at speeds that humans can't keep up with. Hackers, for example, can use the same machine learning algorithms to target specific data and train their attack on anticipated warning flags. Additionally, hackers can use the power of neural networks and deep learning to develop mutating zero-day threats that can evade detection, particularly if that threat was brought in on a transient device or through sophisticated phishing software also developed by AI. AI can also be used to overload a system's defenses by flooding it with massive amounts of potential breaches, much like the War Games Supercomputer running nuclear war simulations until it finds the vulnerability and quickly takes advantage of it. Even a company's own AI solutions can be corrupted if the data sets are infiltrated undetected, often making it impossible to recover the correct data sets, opening a giant hole in any defenses. Lastly, bias and discrimination in the decision-making process of AI open further vulnerabilities as these can be exploited by various sources. These biases can also lead to false positives and discriminatory practices against employees or customers, often having significant consequences.Decisions about what AI tools to use, including custom-built tools over commercially available options, are still harder than they seem. Some organizations have placed moratoriums on commercially available products like ChatGPT, Dali-2, Mid-Journey, Google Bard, and others out of fears of private data becoming public in addition to security concerns of accessing corporate databases without consent. This is also coupled with the risks of using AI tools to generate instruments of service, such as documents, drawings, legal briefs, and more, that can run a company afoul and open to litigation or other business disruptions. Deep fakes are also a reality now, leveraging AI to generate misinformation and vulnerabilities that can penetrate a corporate network or cause reputational harm to that corporation if misused or misinterpreted.Several key factors in moving into what seems like the Wild West need to be considered and having the right voices at the table for making the decisions of what strategies to deploy and, more importantly, why you are deploying them, is critical to success. This is not a world where a Jurassic Park "No Expenses Spared" moment should happen. It is a "spend the most amount you can afford on the best quality tools in a thoughtful manner" moment. Pay attention to not only the quality of the data set that you will train your model on but also the problem you are trying to solve so you select the right model. Consider the hardware that will support the process you are working through with the necessary resources built-in for current use and some expansion should the model develop. That scalability will be critical as new models become relevant as technology evolves. Inventory on a regular basis what AI tools the team has deployed and assess their relevance and effectiveness. Are you getting what you thought you would, or does the model need to be tweaked or abandoned altogether? Pay particular attention to the security, privacy, and ethical implications of any solution you decide on. Reducing bias and mitigating threat potential can save the company time and resources in the long run. Lastly, don't forget to budget for maintenance and operations. It is great to have a shiny new car, but if you can't get the oil changed or know how to drive it, it is just a shiny object in the driveway. Expect systems to require this and expect the right personnel to manage it. Now, let's go play a game of chess. The biggest advancement of AI that most companies can take advantage of is in the growth of machine learning
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