How to Secure AI Business Models. Watch video here. 
AI cybersecurity → https://ibm.biz/your_secure_ai
The power of AI Security → https://ibm.biz/the_power_of_AI_security

Thx for this post :)

How to Secure AI Business Models. Watch video here. 
AI cybersecurity → https://ibm.biz/your_secure_ai
The power of AI Security → https://ibm.biz/the_power_of_AI_security

Great video (love the whiteboarding skills) - implied within bit about classification but might need to be emphasized more - banks need to have a much stronger AI governance framework and an AI taxonomy even ahead of data classification.  While they are of course interrelated concepts, and having that well-defined taxonomy is usually the prerequisite for effective data classification, genAI has taken the dire need to a greater imperative by orders of magnitude for both the need for hierarchy and framework but also fundamental consistency - topics that David Kliemann and I brought up at the Fast Company Accelerate conference in San Francisco this weekhttps://www.linkedin.com/feed/update/urn:li:activity:7128160871930867713/

Thx for this post :)

How to Secure AI Business Models. Watch video here. 
AI cybersecurity → https://ibm.biz/your_secure_ai
The power of AI Security → https://ibm.biz/the_power_of_AI_security

I'm really glad you liked the video, Weiyee! You're absolutely right about governance and taxonomy and I think these are two areas that are not well understood or appreciated at this point. Clearly more work to be done in this space.

BTW, if you want to see more, here's a playlist of all the lightboards I've done to date (and will be updated as new ones come out): 

• Complete List
• AI & Cybersecurity

Great video (love the whiteboarding skills) - implied within bit about classification but might need to be emphasized more - banks need to have a much stronger AI governance framework and an AI taxonomy even ahead of data classification.  While they are of course interrelated concepts, and having that well-defined taxonomy is usually the prerequisite for effective data classification, genAI has taken the dire need to a greater imperative by orders of magnitude for both the need for hierarchy and framework but also fundamental consistency - topics that David Kliemann and I brought up at the Fast Company Accelerate conference in San Francisco this weekhttps://www.linkedin.com/feed/update/urn:li:activity:7128160871930867713/

Thx for this post :)

How to Secure AI Business Models. Watch video here. 
AI cybersecurity → https://ibm.biz/your_secure_ai
The power of AI Security → https://ibm.biz/the_power_of_AI_security

I'm really glad you liked the video, Weiyee! You're absolutely right about governance and taxonomy and I think these are two areas that are not well understood or appreciated at this point. Clearly more work to be done in this space.

BTW, if you want to see more, here's a playlist of all the lightboards I've done to date (and will be updated as new ones come out): 

• Complete List
• AI & Cybersecurity

Great video (love the whiteboarding skills) - implied within bit about classification but might need to be emphasized more - banks need to have a much stronger AI governance framework and an AI taxonomy even ahead of data classification.  While they are of course interrelated concepts, and having that well-defined taxonomy is usually the prerequisite for effective data classification, genAI has taken the dire need to a greater imperative by orders of magnitude for both the need for hierarchy and framework but also fundamental consistency - topics that David Kliemann and I brought up at the Fast Company Accelerate conference in San Francisco this weekhttps://www.linkedin.com/feed/update/urn:li:activity:7128160871930867713/

Thx for this post :)

How to Secure AI Business Models. Watch video here. 
AI cybersecurity → https://ibm.biz/your_secure_ai
The power of AI Security → https://ibm.biz/the_power_of_AI_security

How to Secure AI Business Models. Watch video here. 
AI cybersecurity → https://ibm.biz/your_secure_ai
The power of AI Security → https://ibm.biz/the_power_of_AI_security

The presentation does a fantastic job of highlighting the security challenges of generative AI. As we continue to integrate these advanced technologies into our daily operations, our approach to securing them must be as dynamic and innovative as the technologies themselves.

I'd like to add a few thoughts, particularly regarding the intersection of generative AI with traditional IT security practices.

1. Integrating AI Security into Existing Frameworks: While the presentation excellently outlines the need to secure data, models, and usage specific to AI, integrating these practices into existing cybersecurity frameworks is crucial. Organizations should ensure that AI security doesn't operate in silo but is a part of the broader IT security strategy. This integration helps in leveraging existing security expertise and infrastructure while addressing the unique challenges posed by AI.

2. Ethical Implications of AI Security: The discussion on governance is critical. However, beyond regulatory compliance and operational ethics, there's a need to consider the broader ethical implications of securing AI systems. For instance, how do we ensure that security measures do not inadvertently lead to biases in AI systems? Or, how do we balance the need for security with the ethical use of personal data in AI models? These considerations are as crucial as the technical aspects of AI security.

3. Collaboration and Knowledge Sharing: Given the nascency of generative AI, fostering a culture of collaboration and knowledge sharing is vital. Industries and academia must work together to develop best practices, share threat intelligence, and research novel security approaches specific to AI. This collaboration could also extend to regulatory bodies to ensure that AI security standards evolve with the technology.

4. Focus on Human Elements: While securing the technology is paramount, we shouldn't overlook the human element. Training and awareness programs specific to AI security are necessary to ensure that all stakeholders understand the risks and their role in mitigating them. It's not just about securing the system but also about empowering people to recognize and respond to AI-specific threats effectively.

5. Proactive vs. Reactive Security Posture: Lastly, the field of AI security should lean more towards a proactive approach rather than a reactive one. Given the rapid pace of AI development, waiting for threats to manifest before responding may not be sufficient. Proactive threat hunting, continuous monitoring, and predictive analytics can play a significant role in staying ahead of potential security breaches in AI systems.

How to Secure AI Business Models. Watch video here. 
AI cybersecurity → https://ibm.biz/your_secure_ai
The power of AI Security → https://ibm.biz/the_power_of_AI_security