top of page
  • Writer's picturejmalrakeem

Executive Summary on GENAI Risk Management Strategies

with Tim Pelikan, CISO Advisor

Elevate Xchange April 17th 4:30p-8:30p

Roundtable Forum on Generative AI Presents Unprecedented Opportunities & Risks.


SUBTOPIC SUMMARY:

Risk Management Strategies: Provide insights into effective risk management strategies for enterprises adopting generative AI, including SEC guidelines & robust governance frameworks like NIST and continuous monitoring mechanisms. How can third-party’s aid in trust and accuracy?


Elevate Xchange April 17 Roundtable Forum with Tim Pelikan, CISO in for Alain Espinosa Global Director Cybersecurity Operations://www.linkedin.com/in/tim-pelikan/ SUBTOPIC SUMMARY: Risk Management Strategies: Provide insights into effective risk management strategies for enterprises adopting generative AI, including SEC guidelines & robust governance frameworks like NIST and continuous monitoring mechanisms. How can third party’s aid in trust and accuracy? Managing risks associated with Genetic and Artificial Intelligence (GENAI) requires a multifaceted approach that addresses the unique challenges posed by the convergence of genetic technologies and artificial intelligence. One critical aspect of risk management involves ensuring the ethical use of GENAI by adhering to principles such as transparency, privacy protection, and informed consent. Organizations must develop clear ethical frameworks that guide the development, deployment, and governance of GENAI applications, fostering trust among stakeholders and safeguarding against potential misuse or harm.


Another key component of risk management in GENAI is regulatory compliance. Given the sensitive nature of genetic data and the potential societal implications of AI-driven genetic analysis, organizations must navigate a complex landscape of regulations and compliance standards. This includes adhering to data protection laws such as GDPR and HIPAA, as well as emerging regulations specific to genetic and AI technologies. By staying abreast of regulatory requirements and implementing robust compliance measures, organizations can mitigate legal risks and maintain public trust in their GENAI initiatives.

Furthermore, effective risk management in GENAI requires proactive measures to address technical challenges such as data security, bias mitigation, and algorithmic transparency. Robust data security measures, including encryption, access controls, and regular audits, are essential to protect sensitive genetic information from unauthorized access or breaches. Additionally, organizations must implement strategies to mitigate bias in AI algorithms used for genetic analysis, ensuring fairness and equity in decision-making processes. Transparent documentation of algorithms and mechanisms for accountability further enhances trust and reliability in GENAI applications, fostering responsible innovation in this rapidly evolving field.


Watch, Listen & Learn from Tim Pelikan on this TOP-of-MIND Risk Strategy discussion.

5 views0 comments

Comments


bottom of page