Power Point Presentation: AI-Machine Learning Augmentation and Cybersecurity: Why Smart Minds Using Smart Tools Are Critical for Minimizing Risks, And, What You Can Do About It?
Presentation: 2019 New York State Cyber Security Conference, Albany, NY, June 4 - 5, 2019, Empire State Plaza , Albany, NY
94 Pages Posted: 21 Jun 2019
Date Written: June 4, 2019
The current presentation advances upon Artificial Intelligence and Machine Learning industry expert leadership for the MIT Sloan School of Management and the MIT Computer Science & Artificial Intelligence Lab, and, invited presentations at Princeton University conferences sponsored by firms such as Goldman Sachs and Citadel over recent four years. Latest related research papers and presentations with 63 Top-10 SSRN Research Rankings accessible from the author’s SSRN page are advancing worldwide strategies, practices, and, policies. Prior background research ranked and recognized among Finance-IT Nobel laureates for real world impact is also accessible from the author’s home page. The primary focus of the presentation is on helping advance intuitive understanding about AI-Machine Learning Augmentation and Cybersecurity for auditors, business managers, critical infrastructure owners, educators, executives, information security professionals, forensic specialists, IT professionals, law enforcement, process improvement managers, and project managers about the emerging contours. With great power comes great responsibility! In case of AI and Machine Learning technologies, the realization and application of such great power can yield unprecedented automation and optimization capabilities for developing more sophisticated cybersecurity and cyber risk management capabilities. However, the same AI and Machine Learning technologies also provide the ‘adversary’ with unprecedented deception, manipulation, and, attack capabilities to launch much more sophisticated cyberattacks with unprecedented destructive power. Furthermore, for designers, developers, and, users of AI and Machine Learning technologies, greater responsibility is needed not only for acutely recognizing the limitations of underlying mathematical models and algorithms but also for smartly deploying human imagination, intuition, and, insight to make up for the mechanistic limitations inherent in the design of the machines and related automation technologies. We shall advance upon the latest insights generated, hi-tech practices developed, and, lessons learned from leading global industry leaders at programs such as MIT and Princeton and industry conferences such as the latest Armed Forces Communications and Electronics Association (AFCEA) C4I conference. By doing so, we shall help you develop intuitive understanding about AI-Machine Learning Augmentation as well as its most critical role in minimizing the downside risks in ongoing and future Cybersecurity and Risk Management capabilities and practices development and deployment.
Keywords: AI, Artificial Intelligence, Machine Learning, Augmentation, Governance, Cybersecurity, Risk Management, Interpretability, Adversarial Risks
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