Securing AI powered transformation - managing risk & supercharging productivity
Generative AI is eating the world. You need to master it while protecting your data, defending against attacks, and staying compliant.
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Course overview
After this course you will
Be equipped to enable your organization to embrace the power of generative AI while managing risks along the way. Whether you're dealing with privacy issues, improper data use, or teams building their own generative AI capabilities, we're going to cover how to integrate generative AI into your risk management, governance, and threat models.
Who is this course for
01
CISOs and GRC teams looking to empower and enable their organizations to innovate safely and securely.
02
Software development teams exploring ways to build and integrate AI-powered tools and bring their organizations into the future.
03
Professional services & consulting teams who are looking to advise their clients on the risks and opportunities of generative AI.
What you’ll get out of this course
Enumerate and assess the risks and opportunities
Describe the benefits and risks of generative AI in a way that is unique to your organization's industry, goals, and people. Build on this risk assessment to enable your organization.
Understand regulatory implications
Understand the regulatory and compliance implications of generative AI and how to incorporate it into third-party risk management programs.
Develop an actionable data governance plan
Incorporate generative AI into your organization's policy and governance structure.
Proactively communicate and engage
Communicate effectively with executives, auditors, regulators, and other stakeholders about your threat model, risks, policies, and more.
What people are saying
Mark Gill
Paola Garcia Cardenas
Ross Haleliuk
Chris Hughes
Rob Black, CISSP
Allison Averill
Course syllabus
3 live sessions • 25 lessons
Week 1
- The economic potential AI offers
- Data protection and privacy risks associated with AI
- Case studies of data leakage via AI tools
- Implications for compliance frameworks (NIST cybersecurity, AI RMF, GDPR, etc.)
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Session 1 Slides (Canva)
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Session 1 slides (PDF)
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5-day email primer course
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NIST AI RMF/CSF/Privacy Framework Mapping
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Scenario walkthrough survey
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FTC Demand Letter to OpenAI
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Dealing with AI as a creator
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How to stop ChatGPT from indexing you
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Session 1 Recording
- Develop and implement an organizational policy
- Implement a standard operating procedure (SOP)
- Integrate third-party risk management
- Mitigate common AI-related security and privacy risks
- Deal with realistic scenarios regarding AI use
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Session 2 Slides (Canva)
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Session 2 slides (PDF)
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Generative AI Security Policy Template
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AI Risk Management standard operating procedure (SOP)
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Threat Model Diagram
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Threat and Safeguard Matrix
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Session 2 Recording
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Auto-GPT Demo
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PRIDE cyber risk decision framework
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RAPID®: Bain's tool to clarify decision accountability
- Responding to AI-related incidents
- Managing security risk from locally-deployed models
- Methods for training employees and awareness
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Session 3 Slides (Canva)
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Session 3 slides (PDF)
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StackAware Artificial Intelligence (AI) Cybersecurity Archive
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StackAware Security Center
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Coordinated Vulnerability Disclosure Policies
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Session 3 recording
- ✍️
Final project
Submit by Dec 31
Oct
18
Balancing risk and reward when using AI tools
Oct
18
Establishing data governance to protect and enable AI
Oct
18
Protecting AI data flows
Balancing risk and reward when using AI tools
Like any new technology, AI is not all good or bad. In this section we'll look at:
Establishing data governance to protect and enable AI
Policy and governance represent the foundation of how an organization will harness AI. In this section, we'll focus on how to:
Safeguarding AI data flows and responding to incidents
Data is one of our core assets, no matter the organization. To leverage AI tools to their maximum benefit, you need to leverage data, safely. In this module we will look at:
Meet your instructor
Walter Haydock
Walter Haydock
CEO, StackAware
Walter Haydock is the Founder and Chief Executive Officer of StackAware, which helps organizations manage cybersecurity, compliance, and privacy risks while harnessing AI for business growth.
He was previously a Director of Product Management at Privacera - a data governance startup backed by Accel and Insight Partners - as well as PTC - where he secured the company’s industrial IoT product lines.
Before entering the private sector, he served as a professional staff member for the Homeland Security Committee of the U.S. House of Representatives, as an analyst at the National Counterterrorism Center, and as a reconnaissance and intelligence officer in the Marine Corps.
Course schedule
7.5 hours
Full day workshop
10:00am - 5:30pm ET
10:00am-12pm Session 1
12-1pm: Lunch
1-3pm: Session 2
3-3:15pm: Break
3:15-5:15pm: Session 3
5:15-5:30: Graduation
Final project
By end of 2023
Create a real risk management deliverable, like a:
- Policy
- Threat model
- SOP revision
Get 60 minutes of instructor review/consulting.
Learning is better with cohorts
Active hands-on learning
This course builds on live workshops and hands-on projects
Interactive and project-based
You’ll be interacting with other learners through breakout rooms and project teams
Learn with a cohort of peers
Join a community of like-minded people who want to learn and grow alongside you