OpenChain Webinar #56: Generative AI and Your Code

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Generative AI and Your Code:
Maximizing the Opportunity
While Managing the Risks
Anthony Decicco
Wael Nackasha
GTC Law Group
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• Introduction to GAI and “Demo”
• How Machines Learn
• Using GAI to Write, Test and Improve
Software Code
• GitHub Copilot “Demo”
• Community Reactions and Recent Litigation
• Benefits, Risks and Mitigation
• Best Practices for Policies and Procedures
Overview

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Introduction to GAI
Artificial General Intelligence (AGI)
- On par with humans
- Ability to understand, learn and reason
- Process a spectrum of cognitive ability
https://www.mangalorean.com/an
thony-daniels-voice-of-c-3po-on-
his-hurtful-star-wars-experience/
https://www.imdb.com/title/tt0088247/mediaviewer/rm774208512/?ref_=tt_ov_i
https://www.imdb.com/title/tt047075
2/mediaviewer/rm848491264/?ref_=tt
_ov_i

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Introduction to GAI
Artificial Intelligence (AI)
- Mimics human intelligence, usually for a specific
task
- Solve a problem in a specific situation or
environment
WIPO Technology Trends 2019 – Artificial Intelligence, pg 42

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Introduction to GAI
Machine Learning (ML)
sandserifcomics
- Brach of computer
science
- Algorithm learns from
dataset to generate a
model

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Introduction to GAI
Deep Learning (DL)
Hacker Noon – Big Challenge in Deep Learning: Training Data
- Requires a lot of data and
computation power
- Neural network is the
backbone of most deep
learning architectures
This Photo by Unknown Author is licensed under CC BY-SA

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Introduction to GAI
Deep Learning (DL)
Generative AI
(GAI)
- Ability to generate
data

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Some GAI Applications
Text
Generate text
content such
as for writing
assistance,
email content,
chatting from
text prompt
Image
Generate
artwork with
different
input: image
prompt or
text prompt
Code
Generate
computer
programming
code from
natural
language
input
Video
Generate
video content
based on text
input
Music
Generate
music based
on text input
Data
Generation
Generate data
when data is
scarce

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GAI in Action – ChatGPT and DALL-E
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Overview
• Using GAI to Write, Test and Improve
Software Code
• Community Reactions and Recent
Litigation

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How ML Works - Super Simplified
Hart, Peter E., David G. Stork, and Richard O. Duda. Pattern classification. Hoboken: Wiley, 2000.

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Supervised
Learning

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Unsupervised Learning
Cluster 1 Cluster 2

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Overview
• Using GAI to Write, Test and Improve Software Code
• Community Reactions and Recent Litigation
Scenari
o #1
I have some ideas to get
around some of the
problems with this GAI
tool…
Can I use this GAI
tool to generate
and augment
code?
What is happening with
the lawsuits in this area?
Is it safe for us to
proceed?
Not this
developer
again

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Background
GitHub Copilot
Amazon CodeWhisperer
GPT-4
Code
Generation
Code
Augmentation

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Deeper Dive: GitHub Copilot
June 2021
Technical review
June 2022
Subscription-based
for individuals
December 2022
Subscription-based
for businesses
• What is GitHub Copilot?
• Copilot helps a programmer write code faster
• Understands context of a programmer's code or comments and
suggests code
• Does more than autocomplete
• Extension for Visual Studio Code IDE, JetBrains, and Neovim
• How it works
• Powered by OpenAI Codex model - generates code from natural
language
• Trained on publicly available source code (including GitHub public
repositories)
• The extension sends a programmer's code/comments to the GitHub
Copilot service
• The service synthesizes and suggests individual lines of code or
even entire functions
• Better comments = better inferences

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Copilot in Visual Studio “Demo”: Code Generation
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GPT-4 via Perplexity “Demo”: Code Augmentation
• Prompt: add comments to the code
• Prompt: what does this code do?
• The comment wasn’t included

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Community Reactions
Support for multiple languages
Increased productivity and creativity
since Copilot can offer unconventional
and efficient suggestions that can
simply be accepted
Sigh of relief that Copilot won’t be
replacing developers any time soon!
Most reactions from the developer
community have been positive
Negative comments seem to focus on
Using and reproducing
code subject to copyleft
and permissive
licenses without attribution
Confidentiality
Infringement, including
copyright/copyleft
violations
Code quality
Morality
Security

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Overblown?

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Class Actions Against GitHub Copilot
• Two class actions were filed in November
2022, against Microsoft, OpenAI, and GitHub
for software piracy
• Likely were the first class actions in the US
challenging the training and output of AI
systems

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Issues
• Copilot ingests and distributes licensed material without including associated
attribution, copyright notices, and license terms
• Ingest: during training of Copilot, e.g., generating model using licensed materials
• Distribute: during inference-making, e.g., generating code that is subject to license
• Not clear how the training data was collected
• GitHub has been cagey on the source of the training data
• Only GitHub repositories or other public repositories?

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Claims
• Claims in amended complaint
• Digital Millennium Copyright Act violations (DMCA)
• Violation of Section 1202
• Remove copyright management information
• Contract-related claims
• Breach of open source contract
• Breach of GitHub’s Terms of Services and Privacy Statement
• Interference with prospective economic relations
• Unjust enrichment
• Unfair competition

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Certain Risks Associated with Using GAI to
Generate and Augment Code
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Conflicts
Bias
Quality
Privacy
License
Notice and
attribution
Patent
Copyright
Security Confidentiality
Insufficient
rights
Policy
violations

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Mitigation Strategies
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• Software composition analysis scanning tools
• Security scanning tools
• Human review
• Engineering/development
• Legal
• Downstream considerations
• GAI tooling safety features
• Structural reimagining
• Policies and procedures

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Policies and Procedures
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• Short
• Limit to approved GAI tools
• Tailor mitigations to use categories
• Use categories
• Mission critical
• Ancillary
• Internal use
• Sandbox
Stable Diffusion

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Poll: Request Topics for
Future Webinars on AI
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1. IP Legal Considerations for AI Technologies
- Copyright
- Fair Use
- Web Scraping
- Patents
- Privacy/Data Protection
2. Laws and Regulations Applicable to AI Technologies
3. Additional Lawsuits Relating to GAI
- Getty Images v. Stability AI
- Class Action Against Stability AI, Midjourney and DeviantArt
- Class Actions Relating to ChatGPT, Including the
Sarah Silverman Class Action Against OpenAI
4. Training Data and Dataset Licensing
- Rights in data sets needed for AI/ML applications
- Copyright Considerations, Including Fair Use and Derivative
Works
- Open Source Licenses Applied to Data
- Best Practices for Dataset Usage
5. Intersections Between AI and Open Source
- Open Source Licenses Applied to AI/ML and Shortcomings
- AI Specific Open Source Licenses
- Open Source Risks With AI
6. Contracting Toolkit for AI Technologies
- Legal Terms When Licensing AI Technologies to Customers
- Legal Terms When Procuring AI Technologies from Vendors
7. Government Procurement for AI Technologies
8. AI Governance
9. AI Risk Management, Including Risk Management Frameworks
10. Bias and Discrimination
11. Algorithmic Discrimination Laws
12. Algorithmic Disgorgement
13. Sustainability and AI Technologies
14. Any Other AI-related Topic You Would Like to Learn More About

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Q&A

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Appendix: Speaker Bios
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Anthony Decicco
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Tony is a member in GTC’s IP Strategy, Mergers & Acquisitions, and Business & Technology Transactions groups. He focuses on mergers and acquisitions, strategic
development of patent portfolios, valuing and commercializing intellectual property assets, and licensing and other technology-related transactions. In addition, Tony
founded and oversees the firm’s Open Source Compliance and Due Diligence practice and has extensive experience advising clients regarding the use of open source
software. He has reviewed the results of literally thousands of code scans.
Tony is also the Co-Lead of GTC’s Artificial Intelligence practice and has counseled clients regarding traditional AI/ML (i.e., algorithmic/rules-based) for many years and
has more recently focused on generative AI. He specializes in data set licensing and strategies for acquiring and collecting data, developing patent portfolios focused on AI
inventions and applications of AI technologies, developing AI-related contract terms, risk assessment and mitigation, and related policies and guidelines, in respect of
using AI to generate and test software code and the intersections between open source software and AI. Tony is the co-chair of the AI & Cloud Computing sector of the
Licensing Executives Society.
Tony’s clients range from individual inventors to Fortune 100 companies. Given his extensive experience on both the buy and sell sides of mergers and acquisitions, patent
purchases/sales and IP/technology licensing transactions, he is a trusted advisor to clients on all sides of the table. For acquirers, a key strength is his ability to leverage
this experience to quickly identify and assess IP-related risks. On the sell side, this experience translates to grooming clients and positioning IP assets to maximize value
and minimize issues during rigorous due diligence.
Prior to joining GTC, Tony was a member of the IP & Technology, Internet & E-Commerce and M&A practice groups at Skadden, Arps, Slate, Meagher & Flom. He has
research and professional experience in a diverse range of fields, including patent valuation, law and economics, molecular evolution, apoptosis, and lipid biochemistry.
Tony holds an Honors B.Sc. in Biochemistry from McMaster University, an M.A. in Economics and a J.D., both from the University of Toronto, where he was a law
review editor. He is admitted to practice in Massachusetts, New York, Ontario, and before the United States Patent and Trademark Office (with Limited Recognition).
Email: adecicco@gtclawgroup.com
Phone: (617) 314-7892

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Wael Louis Nackasha
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Wael focuses on M&A due diligence and technology-related transactional matters. Wael specializes in open source software licenses,
commercial licenses, strategic and commercially-sensitive NDAs, and IP strategy advice. Wael also has deep technical knowledge in
machine learning. Before joining GTC, Wael was an Associate at Ridout and Maybee LLP where he drafted and prosecuted patents for
various technologies, including electrical, machine learning, blockchain, telecommunication, and computer-related technology, before both
the USPTO and CIPO.
Before becoming a technology attorney, Wael was a research scientist and software programmer for several years. He published scientific
papers in conferences and journals in machine learning, biometrics, computer vision, signal and image processing, and statistical signal
processing. Wael holds a J.D. from Osgoode Hall Law School, and a Ph.D. in Electrical and Computer Engineering from the University of
Toronto with a dissertation focused on artificial intelligence.
Email: wnackasha@gtclawgroup.com
Phone: (416) 624-0877

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