Case History on Embracing Opportunities of Disruptive Technologies and Creating Trust in AI Systems

12july1:00 pm2:00 pmCase History on Embracing Opportunities of Disruptive Technologies and Creating Trust in AI SystemsA Member-Exclusive Council Virtual Event

Event Details

Generative Artificial Intelligence/Machine Learning including Generative Pre-trained Transformers (GPT) present both challenges and opportunities that must be addressed by individuals and organizations.

Key Take-Aways:

  • Insight on opportunities in generative AI/ML systems to drive rapid knowledge discovery and innovation
  • An understanding of the challenges that must be addressed to ensure responsible adoption; workforce disruption, privacy risks, intellectual property leaks, and insufficient transparency and explainability
  • A guide for moving forward where individuals and organizations should implement policies, processes, and technologies to facilitate proper human-machine engagement and control during human-machine teaming; start with prioritizing broad education and training to promote AI/ML fluency

Some References for Further Reading:

 2023 Final Report of the National AI Task Force

2016 Defense Science Board Summer Study on Autonomy

National Security Commission on AI

DoD Policy 3000.09 – Autonomy in Weapon Systems

DoD Responsible AI Strategy and Implementation:

  • Responsible (judgement/care)
  • Equitable (un biased, e.g., early biased systems in resume selection, sentencing, loans)
  • Traceable (transparent, explainable)
  • Reliable (v&v, testing something that learns/changes, certification and accreditation)
  • Governable (detect and avoid unintended consequences)

EU AI Act (presentation here). Regulating use cases: complexity, opacity, unpredictability, autonomy, data which map onto safety, rights, enforcement, uncertainty, mistrust, and fragmentation. Codes of conduct.

NIST AI Risk Management Framework (RMF)

MITRE ATLAS™ (Adversarial Threat Landscape for Artificial-Intelligence Systems), is a knowledge base of adversary tactics, techniques, and case studies for machine learning (ML) systems based

Some Ideas on Integrity of Generative AI



(Wednesday) 1:00 pm - 2:00 pm , Eastern Daylight Time


Remote, Also To Be Available On-Demand

How To Join

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Office Location

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