October 13, 2022 – Member meeting: Reflexivity: The Cybersecurity Superpower You Haven’t Met Yet | Legislation Related to AI and the Lag in Compliance Guidance for Implementation of Necessary Controls

Registration required: October 13, 2022 7:00pm – 9:00pm Pacific Time

Co Leader – Reflexivity: The Cybersecurity Superpower You Haven’t Met Yet – Humble Science, PBLLC

Jodi Masters-Gonzales, FHCA Founder and Chief Futurist of Humble Science, PBLLC, PhD researcher and board certified Independent Auditor of AI Systems (IAAIS). Pending board certifications for Certified Expert In Cyber Investigations (CECI) (which includes Certified Cyber Intelligence Professional (CCIP), Certified Counterintelligence Threat Analyst (CCTA), Certified Organized Retail Crime Investigator (CORCI), Certified Social Media Intelligence Analyst (SMIA), Certified eCommerce Fraud Investigator (CEFI), Certified Forensic Hi-tech Investigator (CFHI)), and Certified All Source Intelligence Professional (CASIP). Recruited into InfraGard a few months ago, founding member and Vice Chair of newly formed INMA Digital Exhaust Cross Sector Council (announcement forthcoming.) One of ISC2’s newest members! Connect with Jodi on LinkedIn

Building upon industries’ general understanding of the current state of artificial intelligence, we explore indicators that reveal a wide range of algorithmic maturity throughout the entire ecosystem, including the cloud, IoT, supply chain, and the varied and various X-as-a-Service (Xaas) providers. As a result, threat landscape is expanding exponential into virtual and non-terrestrial spaces, forever blurring traditional protect surface boundaries. How did we get here and what are the critical skills required to build cybersecurity teams of the future? Learn the five key skillsets that will offset tomorrow’s threat landscape, and how to implement pragmatic solutions today so as to ensure agility and foresight capacities JIT.

About Humble Science, PBLLC

Pursuant to §§ 18-1202(a)-(b) of the Act, the LLC shall provide systemic, novel, and sustainable society-valued growth strategies and solutions to public and private stakeholders of the digital economy. In this era of data-driven intelligence, the LLC commits to approaching these uncharted areas of science with epistemic humility while striving to free the historically marginalized from unconquered systems of oppression. The LLC shall strive to strengthen the emerging digital economy—and its various markets—with checks and balances that incentivize positive-sum market innovation and a public return on public investments. The LLC shall have a positive effect on the centering of humanity in the exploration and discovery of sustainable artificial intelligence and quantum technologies capable of affecting the human condition at scale—with special emphasis on the economic, social and environmental challenges affecting the world’s poorest people.

Co Topic Leader – Legislation Related to Artificial Intelligence and the Lag in Ethics & Compliance Guidance for Implementation of Necessary Controls – Our Training Journey for AI/ML

Owner EnterpriseGRC Solutions, President, ISC2 East Bay, Certified Information Systems Security (CISSP), Audit (CISA), Governance (CGEIT) and Risk (CRISC-NA), ICT GRC expert and early adopter in both certifying and offering certification programs for Cloud Security and Virtualization, with industry experience in the management of systems, controls and data for SaaS (IaaS and PaaS), Finance, Healthcare, Banking, Education, Defense, and High Tech. Positions held include Technology Officer at State Street Bank, Leading Process Engineering for a major New England CLEC, Sr. Director Enterprise Technology for multiple advisory firms, founding, engineering product, and running two governance software companies, and most recently Director Enterprise Compliance for a major player in the mortgage industry, Ellie Mae. Recently full-time at Cisco, Unified Compliance and ISMS Program Manager, Robin provides voluntary support to social platform security to further social democracy. Connect with Robin on LinkedIn

Cybersecurity professionals understand the many benefits and potential for Artificial intelligence (AI) security defense systems. The obvious concerns about potential misuse or unintended consequences of AI, however, have prompted efforts to examine and develop standards, such as the US National Institute of Standards and Technology (NIST) initiative involving workshops and discussions with the public and private sectors around the development of federal standards to create building blocks for reliable, robust, and trustworthy AI systems. State lawmakers must evaluate AI benefits against their potential for harm. This hour covers a summary of some of the State level initiatives, with emphasis to our State of California, and asks how we as cybersecurity professionals balance what we monitor, what we learn, and what we protect (CIA), and how we advise our clients as they acquire and implement increasingly AI dependent processes and technology.

About EnterpriseGRC Solutions Inc.

EnterpriseGRC Solutions is a Governance Risk and Compliance company specializing in mapping cloud security and cyber security frameworks. We implement governance, ISMS, Risk Frameworks, and compliance automation products and programs. We emphasize system-based policies specific to security settings for secure configuration management. EnterpriseGRC is a women-owned small business offering compliance readiness, Security & GRC tools, Enterprise Security Architecture, Cybersecurity Risk Assessment, and a wide variety of resources for security and GRC technology support.

Our Guest Moderators and Future SpeakersFuture Topics involving Data Science, Critical Thinking and Predictive Analysis

Sean Lyons is the author of the influential book, “Corporate Defense and the Value Preservation Imperative: Bulletproof Your Corporate Defense Program”, which has been critically acclaimed by a host of distinguished corporate commentators. He has been internationally described as a value preservation activist, and a corporate defense author, pioneer, and thought leader. He is recognized as the first person to propose the umbrella term “Corporate Defense” to represent an organization’s collaborative program for self-defense. He is also acknowledged for being the first person to propose the extended “Five Lines of Defense” as a corporate oversight model which includes Executive Management and the Board of Directors as the all important 4th and 5th strategic lines of defense. As the architect of the cross-functional discipline of “Corporate Defense Management” (CDM), he is widely regarded as the foremost authority in this emerging field. Connect with Sean on LinkedIn
Brian Barnier is the co-founder of Think.Design.Cyber and the think-tank, CyberTheory Institute that bridges the gap between boards, business leaders, cybersecurity leaders and compliance. Brian has pioneered critical, systems and industrial design thinking in the cybersecurity discipline and the use of life-like scenario analysis to address critical issues of evolving threats/attacks, eliminate bad methods that cause breaches, waste money and resources and burnout cyber pros, affecting culture and retention. He is the author of The Operational Risk Handbook (Harriman House, Great Britain, 2011) used as a textbook by the London Institute of Banking & Finance. In 2020, Brian’s paper with expert Prachee Kale, “Cybersecurity: The Endgame — Part 1” was honored as the 2020 Article of the Year in the Taylor and Francis EDPACs journal. Brian has earned coveted achievement awards from two of ISACA’s most significant chapters. In 2021, he earned the highly distinguished Joseph J. Wasserman Award presented by ISACA New York Metro Chapter. In 2015, he received the V. Lee Conyers Award from ISACA Greater Washington DC. Deep in professional guidance, he is a co-author of ISACA’s Risk IT and COBIT, and the Shared Assessments Program. ISACA’s IT Audit Framework 2020 points to his work in risk assessment. He is one of the first three “Fellows” of OCEG — the Open Compliance & Ethics Group – the organization that created “Governance, Risk and Compliance.” Connect with Brian on LinkedIn

ISC2 offers three Professional Development Institute courses on the topic of AI. After several months of collaborating together, Jodi Masters-Gonzalves and I (Robin Basham) decided that whatever we present to the ISC2 East Bay community should align with content authorized for study by our parent organization. To access the full courses, go to Cybersecurity Certification Training | Exam Prep (isc2.org)

Sample Content from the evening
AI in Cyber Security as represented in the ISC2 AI PDI courses
Common vulnerabilities and AI security issues – derived from ISC2 PDI content

Resources list

These resources are mentioned during tonight’s presentation.

Blueprint for an AI Bill of Rights: A Vision for Protecting Our Civil Rights in the Algorithmic Age | The White House

eCFR :: 16 CFR Part 312 — Children’s Online Privacy Protection Rule

California Enacts the California Age-Appropriate Design Code Act | Blogs | Innovative Technology Insights | Foley & Lardner LLP

Towards a Standard for Identifying and Managing Bias in Artificial Intelligence (nist.gov)

The Malicious Use of Artificial Intelligence: Forecasting, Prevention, and Mitigation. Brundage, M. et al. (2018, February). Future of Humanity Institute. Retrieved from https://arxiv.org/ftp/arxiv/papers/1802/1802.07228.pdf

The Ethics Certification Program for Autonomous and Intelligent Systems (ECPAIS)

The goal of The Ethics Certification Program for Autonomous and Intelligent Systems (ECPAIS) is to create specifications for certification and marking processes that advance transparency, accountability and reduction in algorithmic bias in Autonomous and Intelligent Systems (AIS). 
The value of this certification process in the marketplace and society at large cannot be underestimated.  The proliferation of systems in the form of smart homes, companion robots, autonomous vehicles or any myriad of products and services that already exist today desperately need to easily and visually communicate to consumers and citizens whether they are deemed “safe” or “trusted” by a globally recognized body of experts providing a publicly available and transparent series of marks.

Artificial Intelligence Systems (AIS)

IEEE 7000™-2021 integrates ethical and functional requirements to mitigate risk and increase innovation in systems engineering product design and utilizes “Value-based Engineering” as its core methodology providing ways to elicit, conceptualize, prioritize and respect end user values in system design.

Global Artificial Intelligence Systems (AIS) Well-Being Initiative

The IEEE Applied Artificial Intelligence Systems (AIS) Risk and Impact Framework Initiative

Trusted Data and Artificial Intelligence Systems (AIS) Playbook for Finance Initiative

Developing an interoperable data infrastructure through extensible governance and metadata lifecycle framework

Digital Intelligence

Helping to advance individual and community-level prosperity; socially, politically, and economically

Artificial Intelligence Systems Archives – IEEE Standards Association

IEEE Global Initiative for Ethical Considerations in Artificial Intelligence (AI) and Autonomous Systems (AS) Drives, together with IEEE Societies, New Standards Projects; Releases New Report on Prioritizing Human Well-Being

The IEEE Global Initiative on Ethics of Autonomous and Intelligent Systems


  • ISO/IEC 23053:2022 – Framework for Artificial Intelligence (AI) Systems Using Machine Learning (ML)
  • ISO 9241-110:2020 – Ergonomics of human-system interaction — Part 110: Interaction principles
  • ISO/TR 22100-5:2021 – Safety of machinery — Relationship with ISO 12100 — Part 5: Implications of artificial intelligence machine learning
  • ISO/IEC 22989:2022 – Information technology — Artificial intelligence — Artificial intelligence concepts and terminology
  • ISO/TR 24291:2021 – Health informatics — Applications of machine learning technologies in imaging and other medical applications
  • ISO/IEC TR 24030:2021 – Information technology — Artificial intelligence (AI) — Use cases
  • ISO/IEC 38507:2022 – Information technology — Governance of IT — Governance implications of the use of artificial intelligence by organizations
  • ISO/TR 9241-810:2020 – Ergonomics of human-system interaction — Part 810: Robotic, intelligent, and autonomous systems
  • ISO/TS 5346:2022 – Health informatics — Categorial structure for the representation of traditional Chinese medicine clinical decision support system
  • ISO/IEC TR 24368:2022 – Information technology — Artificial intelligence — Overview of ethical and societal concerns
  • ISO/IEC TR 24372:2021 – Information technology — Artificial intelligence (AI) — Overview of computational approaches for AI systems
  • ISO/IEC TR 24027:2021 – Information technology — Artificial intelligence (AI) — Bias in AI systems and AI aided decision making
  • ISO/IEC TR 24028:2020 – Information technology — Artificial intelligence — Overview of trustworthiness in artificial intelligence
  • ISO/IEC TR 24029-1:2021 – Artificial Intelligence (AI) — Assessment of the robustness of neural networks — Part 1: Overview


Proposal for a Regulation laying down harmonized rules on artificial intelligence | Shaping Europe’s digital future (europa.eu)

Twitter Research

Introduction to Twitter data processing and storage on AWS – DEV Community 👩‍💻👨‍💻

Amazon Training

Discovering Hot Topics Using Machine Learning | Implementations | AWS Solutions (amazon.com)

One of many resources shared by Brian Barnier


Terms necessary to passing the three ISC2 PDI

Algorithms are processes for solving mathematical operations. In the field of computer programming, algorithms are used to define a set of processes that the program must take to determine outcomes.
Cognitive computing refers to the science of teaching a system how to comprehend problems, like a human, to find solutions in complex situations where not all the data gets incorporated into the data model. Present in many AI applications, cognitive computing, like VR, robotics, and neural networks helps to extrapolate situations and possible solutions by the program and system.
Natural language processing is a field within computer science that studies the interaction between humans and computers for verbal communication. This science focuses on understanding and processing syntax, semantics, speech, and dialogue, to name a few.
Visual Information Processing describes the ability of a system or program to understand and translate information gained by optical sensors in the visual and non-visual spectrums (ultraviolet and Infrared). This information translates to data that can be processed by the application to make decisions based on this type of data.
Supervised learning is an algorithm that analyzes data and returns the desired output. This is done by taking input and analyzing it with expected and pre-defined input-output data and defining the expected outputs of that data pair. The algorithm then infers the best (most reasonable) course of action based on the training data it possesses.
Unsupervised learning is an algorithm characterized by self-organizing unknown patterns in data pairs to model the probabilities and the outcomes based on the availability of the data. The model gets more precise, with more data.
Reinforcement learning is an algorithm that focuses not on the input/output pairs but on the outcomes that bring the best reward. Think positive reinforcement, without losing the “incorrect/not best” results.
Autonomic computing refers to an area of study in which systems and programs can self-correct and react to unexpected changes. This course of study was started by IBM in 2001 to help computer systems self-manage themselves when errors occurred.
Chatbots are artificial intelligence programs designed to carry out conversations and interact with a human via text or voice. These programs are designed to simulate how a human would speak or type, some are simple (like you see on websites), and some can be as complex as to attempt to pass the Turing test.
Data mining is the way programs discover patterns in large data sets. Data mining is a cross between computer science and statistics, to extract information and transform the information into an understandable structure for further use. Data mining is a buzzword and is usually used to describe the collection, extraction, warehousing, analysis, and statistics of data.
Predictive analysis describes the analytics performed on a data set to make predictions about future events. These analytics make use of data mining, statistics, and modeling. For example, the National Weather Service uses weather predicting models to provide weather forecasts around the country.

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