Summer Cybersecurity Faculty Development
AI and Cybersecurity
6/10/23 - 7/8/23: Virtual Asynchronous (session 1) 6/16/23 - 6/17/23: Virtual Synchronous (session 1)
7/10/23 - 8/08/23: Virtual Asynchronous (session 2) 7/28/23 - 8//8/23: Virtual Synchronous (session 2)
From reengineering manufacturing to self-driving cars, to digital humans Artificial Intelligence and Machine Learning have created a new frontier of science and business. There are numerous technologies that fall under the general rubric of AI/ML that we cover in this class. The myriad technological advances based on AI/ML that have resulted in advances to society there are also potential societal dangers that need to be understood and mitigated as the societal footprint of AI grows.
The AI-based chatbots are generating credible content that matches up with human writing – with a potential for plagiarism. Generative Adversarial Networks have helped create indistinguishable deep fakes that can help in the manipulation of public opinion. Societal biases from the past have the potential for future discrimination through the codification of historic data in AI systems. The AI systems themselves are subject to cyberattacks – data poisoning, contrived data injection, etc.
X-ALT-DESC;FMTTYPE=text/html:Summer Cybersecurity Faculty Development
AI and Cybersecurity
6/10/23 - 7/8/23: Virtual Asynchronous (session 1) 6/16/23 - 6/17/23: Virtual Synchronous (session 1)
7/10/23 - 8/08/23: Virtual Asynchronous (session 2) 7/28/23 - 8//8/23: Virtual Synchronous (session 2)
From reengineering manufacturing to self-driving cars, to digital humans Artificial Intelligence and Machine Learning have created a new frontier of science and business. There are numerous technologies that fall under the general rubric of AI/ML that we cover in this class. The myriad technological advances based on AI/ML that have resulted in advances to society there are also potential societal dangers that need to be understood and mitigated as the societal footprint of AI grows.
The AI-based chatbots are generating credible content that matches up with human writing – with a potential for plagiarism. Generative Adversarial Networks have helped create indistinguishable deep fakes that can help in the manipulation of public opinion. Societal biases from the past have the potential for future discrimination through the codification of historic data in AI systems. The AI systems themselves are subject to cyberattacks – data poisoning, contrived data injection, etc.
LOCATION:Virtual\, CLASS:PUBLIC END:VEVENT END:VCALENDAR