Artificial Intelligence (AI) is increasingly being used to make decisions that impact individuals and society as a whole. As the use of AI continues to grow, there is a need to establish guidelines and regulations to ensure that it is being used responsibly and ethically. In October 2022, the White House Office of Science and Technology Policy (OSTP) published a Blueprint for an AI Bill of Rights (“Blueprint”), which shared a nonbinding roadmap for the responsible use of artificial intelligence (AI). In this webinar, we will examine the key principles that underpin the bill, such as transparency, accountability, and fairness, and discuss how they can help ensure that the use of AI aligns with the values and rights of individuals.

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© 2023 TrustArc Inc. Proprietary and Confidential Information.
Artificial Intelligence Bill of Rights:
Impacts on AI Governance

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Speakers
Lindsay Palmer,
Senior Privacy Research Specialist,
TrustArc
Paul Iagnocco
Customer Enablement Lead and Senior
Privacy Consultant,
TrustArc

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Agenda
▪ An overview of the AI landscape
▪ Opportunities being brought on by AI solutions
▪ AI Bill of Rights
▪ AI governance solutions to protect privacy rights
▪ Immediate Next Steps
▪ Q&A

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Legal Disclaimer
The information provided during this webinar does not,
and is not intended to, constitute legal advice.
Instead, all information, content, and materials presented
during this webinar are for general informational purposes only.

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Polling Question:
What is your comfort
level with using AI?

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Key Definitions - in a nutshell…
Applied AI
▪ Solves specific problems or performs specific tasks
Artificial Intelligence
▪ Simulation of human intelligence in machines
Automated Systems
▪ Use of computation designed to work with minimal or no human intervention to determine or help determine an outcome
(e.g., observations, decisions)
Generative AI
▪ Generative AI is a field that focuses on developing intelligent systems that can generate new content, such as images,
videos, and text.
Large Language Models
▪ Neural network (type of deep learning algorithm) trained on large quantities of unlabelled text using self-supervised
learning to predict and generate text.
Natural Language Processing (NLP)
▪ Machine learning technology that gives computers the ability to interpret, manipulate, and comprehend human language.
Regenerative AI
▪ Emerging field that focuses on developing intelligent systems that can adapt, regenerate or repair themselves.

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Evolution of Data & The Web
Transaction
Business
Intelligence
Machine
Learning
Machine
Intelligence
Machine
Consciousness
Rack-Mounted Infrastructure E-Commerce
ETL - Data Warehousing Reporting
User-Induced Machine Learning
Advanced Network
trained to build
Adhoc Models
● VR & AR (Metaverse)
● Blockchains
● Artificial Intelligence
● Interoperability
● NFTs (Tokens)
Web 3.0
● Social Media
● User Generated Content
● Mobile Access
● High Speed Comms
Web 2.0
● Basic Web Pages
● HTML
● E-commerce
● Javascript
Web 1.0

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3 Types of Artificial Intelligence
STAGE 1
Machine
Learning
● Specializes in one area and solves one
problem
Artificial Narrow
Intelligence (ANI)
STAGE 2
Machine
Intelligence
● Refers to a computer that is as smart as
a human across the board
Artificial General
Intelligence (AGI)
STAGE 3
Machine
Consciousness
● An intellect that is much smarter than
the best human brains in practically
every field
Artificial Super
Intelligence (ASI)
Siri Alexa Cortana

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Opportunities for Generative AI
Modality Application Example Use Cases
Text
Content Writing Marketing: creating personalized emails and posts
Talent: drafting interview questions, job descriptions
Analysis and Synthesis Sales: analyzing customer interactions to extract insights
Compliance: summarizing regulatory documents
Code
Code Generation IT: accelerating application development and quality with automatic code recs
Application Prototype & Design IT: quickly generating user interface designs
Image
Image Generation Marketing: generating unique media without copyright violations
Image Editor Marketing/Sales: personalizing content quickly for target audience
Audio
Text to Voice Generation Training: create educational voiceover
Sound Creation Entertainment: making custom sounds without copyright violations
3-D or Other
3-D Object Generation Video games: writing scenes, characters
Product Design & Discovery Manufacturing: optimizing material design
Drug Discovery: accelerating R&D process
Video
Video Creation Entertainment: generating short-form videos
Training: creating corporate/other presentations using AI generated avatars
Video Editing Entertainment: removing background images and background “noise” in a social media post
E-commerce: adding personalization to generic videos
Adapted from: McKinsey & Company

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Polling Question:
What is your current understanding
of the AI Bill of Rights?

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AI Bill of Rights
● Blueprint only
● Applies to automated systems
with meaningful impact
● Sector-agnostic
● Set of 5 guiding principles:
○ Safe and effective systems
○ Protection from algorithmic discrimination
○ Data privacy
○ Notice and explanation
○ Human alternatives, consideration and fallback
Key takeaways

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AI Governance Landscape
USA
● Blueprint for AI Bill of Rights
● NIST AI Risk Management Framework (AI RMF)
● EEOC AI and Algorithmic Fairness Initiative
● Regulator enforcement statements
EU
● EU AI Act (draft legislation)
● Member State-level scrutiny
● EDPB ChatGPT task force
Global
● OECD AI Principles
● Global Partnership on AI
● 60+ countries have a national AI strategy

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Privacy Challenges of AI Solutions
● Transparency and explainability
● Black box systems
● Stakeholder consultation
● Exercise of individual rights
● Bias and discrimination
● Data abuse practices

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Internal AI Governance
● Stick to privacy principles
● Scope out your processing
● Top-level accountability
● AI and Data Ethics committees
● Test and report

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Impact of AI on
● Innovation
○ xxx
● Data Privacy
○ xxx
● Ethical Decision Making
○ xxx

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Immediate Next Steps
▪ Develop “guiding principles” on the use of AI
▪ Gain C-Suite accountability/sponsorship
Principles
▪ Develop workflow that will enable AI opportunities to be
reviewed in design and final product or service
Workflow
▪ Conduct inventory of AI:
1. In use today 2. In consideration in the future
Inventory
▪ Conduct Privacy Impact Assessment on AI in use:
Remediate privacy and data security gaps
Assess
▪ Conduct annual training for roles designing and developing AI
solutions
Train

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Q&A

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Interested in TrustArc Solutions for AI?

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Thank You!
See http://www.trustarc.com/insightseries for the 2023
Privacy Insight Series and past webinar recordings.
If you would like to learn more about how TrustArc can support you with privacy and
data security compliance, please reach out to sales@trustarc.com for a free demo.