Name: How to Customize Models for Clients, Securely
Start: 2024-10-30T14:00:00Z
End: 2024-10-30T14:00:37.000Z
Location: BrightTALK
Rating: 0

Duality is the leader in privacy enhanced secure data collaboration, empowering organizations worldwide to maximize the value of their data without compromising on privacy or regulatory compliance.  Founded and led by world-renowned cryptographers and data scientists, Duality operationalizes privacy enhancing technologies (PETs) to accelerate data insights by enabling analysis and AI on encrypted data, while preserving data privacy, compliance and protecting valuable IP. 

On our channel, we'll be featuring our team of world-renowned cryptographers and data scientists and exploring 3 key areas relating to PETs: the vision (how data is changing as a concept), the business side (practical applications), and technical walkthroughs. Enjoy!

New laws and standards around the world are defining responsible, secure, and trustworthy AI (E.g., USA - EO on AI, NIST Gen AI, UK AI Act, EU AI Act, etc.). This webinar will discuss the impact of recent developments and trends on corporate data and AI strategies as well as the role of PETs in these new regulations and frameworks.

Learn how regulators and business leaders are embracing new technologies to accelerate growth while satisfying modern data and AI regulations.

- Regulatory Overview
- The merger of data, AI, and sec ops
- What regulators are recommending
- How new privacy technologies (PETs) satisfy regulations & accelerate growth

ABOUT THE PANELISTS:

*Daniel J. Weitzner* is the Founding Director of the MIT Internet Policy Research Initiative, holds the 3Com Founders Senior Research Scientist chair at the MIT Computer Science and Artificial Intelligence Lab, and teaches Internet public policy in MIT’s Electrical Engineering and Computer Science Department. Weitzner was the US Deputy CTO for Internet Policy in the White House, leading initiatives on privacy, cybersecurity, copyright, and digital trade policies promoting the free flow of information. 

*Paul Comerford* is a Principal Technology Adviser at the UK Information Commissioners office (ICO). The ICO is responsible for regulating data protection law (and other laws). Paul previously worked in academia as a lecturer in Computer Networks and Cyber security. Since joining the ICO in 2018, he has led the development of UK GDPR guidance on anonymisation, pseudonymisation, and was the lead author of ICO PETs guidance published in 2023.

*Caroline Louveaux* is the Chief Privacy & Data Responsibility Officer for Mastercard driving Privacy and Data Responsibility Strategy; leading the global teams responsible for privacy, data and AI governance, in terms of legal compliance, policy and regulatory engagement as well as data management, governance and platforms.

AI & Data Regulations: Key Insights, Strategies, & Technologies for Growth

Learn how Mastercard has taken the lead in effective anti Fraud, KYC, and AML efforts with a privacy protected workflow via Duality (as published by the IMDA).

Fighting financial crimes is a data game. Crime fighters need answers quickly and must ensure their investigations remain confidential, as not to leak their progress to suspected organizations or individuals. However, criminals continue to evade authorities and slip through the cracks despite efforts around KYC and AML.

Why? Because data protection requirements slow and limit what data can be shared, and with whom. The criminals know this and hide behind our own processes, and they're winning.

However, those hindrances are eliminated when advanced encryption for data in-use is operationalized into these processes. 

The result is a near-instant, self-service means of gathering and using information instead of waiting for weeks or months for an answer about a transaction, identity, or other.

See how Mastercard and other financial institutions have upleveled their internal KYC and AML efforts while also improving their response time when collaborating on government investigations.

Workloads shown: secure query (all data types)
Workloads discussed: query, analytics, machine learning
Technologies used: fully homomorphic encryption (FHE), confidential computing, federated learning
Solution shown: Zero Footprint Investigations
Solutions discussed: Confidential AI & Zero Footprint Investigations

Tech Talks: A Modern Approach to Fighting Fin Crimes: Fraud, KYC, & AML

Governments around the world share a common goal: make better use of data by increasing data sharing while increasing data protections.

The traditional means of satisfying regulations and agency policies are typically done with checkpoints to anonymize or otherwise obfuscate both the data and the use of the data. These traditional methods strain budgets, slow progress, and limit the accuracy of data insights.

Instead, Duality offers quantum-secure data guardrails that accelerate and grow the speed and scale of sensitive data operations while also eliminating as much as 90% of costs for high-security environments.

This means faster and greater collaboration across agencies, with coalition partners, and streamlined use of PAI/CAI while maintaining Operatonal Security.

The Key to Digital Transformation: Privacy-by-Design

The practical applications of privacy technologies today go far beyond compliance and ethics. While those things are important, PETs will unlock massive growth potential for today’s data-driven and AI economies.


AI is about as disruptive as a technology gets. Behind the tremendous amount of benefits that can be achieved with AI, lies significant risk–and world leaders and regulating bodies are working hard to find answers to difficult questions. Theory aside, we have real methods for responsible AI model development and training available today. For many organizations, the first challenge in AI development is data acquisition and governance. Data quality, diversity, and volume is critical throughout the AI SDLC and extends into monetization when customizing models for clients. In this webinar, we’ll discuss how privacy technologies are being operationalized to fill risk gaps in the wake of AI, enabling greater growth at the same time.


- Why the Imperative around privacy? Ethics, growth, regulation? 

- How do PETs unlock growth? Examples?

- How is AI reshaping the roles of security, privacy, and data experts in business growth strategies?

- How to find solutions to unlock growth in AI and future proof data compliance


Join our esteemed panel as they share and discuss expertise in AI, Data, Privacy, and Regulations.

Unlocking Growth in AI and Data with Privacy Technologies

Duality's Zero Footprint Investigation and Intelligence solutions utilizes fully homomorphic encryption to satisfy cross-border and cross-domain data sharing security, privacy, and legal obligations by default. This solution greatly benefits those needing answers to questions from 3rd party, sensitive data sets: KYC, AML, investigations, intelligence activities. Learn how it works from system requirements to setup and use.

This session includes:
- Overview of common use cases
- Infrastructure requirements
- Data set support (structured and unstructured)
- Demo explaining and showing how it works
- Q&A

Tech Talks: Zero Footprint Investigations & Fully Homomorphic Encryption (FHE)

Use AWS Nitro Enclaves and Duality’s Privacy Protected AI Solution to futureproof, secure, and scale data acquisition for model development, tuning, testing, and customization while protecting model IP and maintaining the privacy of data inputs.

The recent executive order from the US Whitehouse and the current NIST RFI for guidelines in developing and using AI securely while maintaining the privacy of data inputs have raised many questions. Fortunately, the combination of AWS’s Nitro Secure Enclaves with Duality’s Privacy Protected AI Solution provides critical answers to tough data questions facing AI Engineering Teams: How do we acquire data at the scale and diversity needed to move models quickly to production? How can we collaborate with 3rd parties to validate and tune our model on real data versus mock or synthetic data? How do we coordinate with data from multiple parties? How do we prove to clients that our model is valuable to them? How do we do all that while protecting our IP and the privacy of data?

Join Duality’s Head Data Scientist and AI Engineer, Zohar Duchin, and Sr Partner Solution Architect, Ashok Mahajan of AWS, to hear how this joint solution can help AI Engineering teams overcome data acquisition, training, inference, customization, and monetization challenges while protecting model IP and the privacy of data inputs.

Accelerate AI Development with Privacy Protected AI Collaboration

We have collaborated with industry experts to create a new, exclusive webinar that unpacks the fundamental need for, and challenges that surround, data in the global fight against financial crime.

In this webinar, expert speakers delve into public and private sector organisations’ need for data to turn the tide against financial crime, as well as the challenges that surround acquiring this data as a result of privacy regulation, data regulation, and operational security concerns.

These range from acquiring and collating it to extracting meaningful insights without exposing the subjects of inquiries to third parties, and from collaborating with multiple stakeholders to ensuring that privacy and data security are maintained, especially where sensitive data is concerned.

Financial Crime Risk: Balancing Data Needs and Privacy Concerns

Analysts and investigators in law enforcement, intelligence, and national security benefit by utilizing publicly available and commercial datasets to conduct investigations of many types. However, the sensitivity of both the investigation and the data required pose challenges. The first being that the subject of the investigations must remain 100% private and confidential, without having to “trust” any vendors or infrastructure. This ends up forcing the public sector to purchase, store, and protect large amounts of sensitive data - even if it is not directly pertinent to a given investigation. The risk, lift, and expense of such a workaround is the second challenge. The result is that such datasets aren’t utilized as much as they should, which negatively impacts investigation, risk awareness, and national security outcomes. 

Attendees of this webinar will learn:
- Common challenges in conducting investigations on commercial data
- How to achieve zero footprint investigations with privacy enhancing technologies
- Additional benefits and getting started

Accelerate Government Investigations & Screenings with Duality

Regulatory changes, rulings, and ICO guidance. What you need to know to ensure your competitive advantage.

We're just over halfway into 2023, and it has already been a year of massive shifts in the world of data protection and data privacy. From the reforms underway across a number of countries, to court rulings on data anonymization and data processing, to regulators like the ICO providing landmark guidance on privacy technologies, it seems like the rules around how data can be used (and how it must be protected) have never been in such flux.

Join our expert panel discussion as they discuss recent developments on the intersection of data privacy law and technology, where regulation is headed, and how organizations across the public and private sectors can be best positioned to respond - or better yet, be ready.

Taming the Regulatory Whirlwind

Technical and specialty roles like CISOs, CDAOs, and CPOs aren’t traditionally regarded as drivers of business growth. Often, they are perceived as mere supporters, necessary evils, or worse, blockers.

Understanding which technologies support growth while balancing security and privacy requirements means a good portion of the C-suite has to provide input - including those that don't typically have a seat at the business table.

Join our panelists as they discuss the evolving roles of security, data, and privacy professionals and the new technologies that will propel innovative organizations to become market leaders by unlocking valuable data and insights.

Attendees will learn:
- Why these roles are evolving - including Technology Adoption, Data Maturity, and Regulatory considerations
- How technology can reduce risk and streamline processes when sensitive data is required
- How organizations can implement new strategies by unlocking collaborations, monetizing data, and building collaborative AI/ML Models

Why Data, Privacy, & Security Leaders are Key to Growth & Innovation

At Duality and at Team8 Health, data scientists and industry experts work every day to introduce innovation that can help solve these issues - in this case enable authorized users the ability to conduct advanced analytics on linked genomic and clinical data. To explore the different aspects of genomic data sharing, biopharmaceutical data sharing and analysis, and the powerful outcomes that can be reached by linking different types of sensitive health data, Duality’s CEO and Co-founder Dr. Alon Kaufman and Team8 Health Managing Partner Dr. Kinneret Livnat-Savitzky sat down in the Team8 office to discuss how privacy enhancing technologies, machine learning & AI can help.

Genomic Data Sharing: The Potentials of a Privacy-Preserving Approach

Prof. Shafi Goldwasser (Chief Scientist and Co-founder, Duality and Prof. Suchi Saria (Founder, Bayesian Health) discuss topics including healthcare statistics and machine learning.

Data and Trust: In our Opinion (episode 5)

Data is paramount in all organizations today. However, disparity exists on who in an organization is the topline owner, and how privacy and regulatory compliance weigh in - it also exists across how a data driven enterprise should collaborate on data across business units, geographies and the c-suite.  

Let’s imagine a world where sharing your private information is rooted on the trust that those collecting it will act responsibly and with increased benefits to all. Take a global health entity for example, that has several business units, all collecting different forms of data, across several of their lines of business about one individual. What if they were presented with proven technology and methodologies that would enable them to privately share data across their entire entity, empowering them to help their partners, ecosystem and the very individual who agreed to allow their data footprint to reside across their business? Imagine a scenario where regulatory compliance is achieved, enabling you to drive insights from your data, while enriching your business and customer experience. 

In this webinar, join Duality Co-founder and Chairwoman, Rina Shainski and our Chief Business Officer, Michael Hughes as they examine a “What If” scenario, taking a household name and applying a platform approach to their data strategy to show how privacy preserving data collaboration could enable them to implement an actionable data strategy across their entire business that:

- Performs analysis on data without ever decrypting or exposing sensitive data
- Is HIPAA Compliant - collaborate across business units, cross-borders, on disparate data
- Personalizes and improves customer experience to promote retention

Extending Privacy Preserving Data Collaboration Across your Entire Organization

As an enterprise's data footprint continues to expand, so does the role of the business owner who is challenged with extracting value from data, no matter the location, source, or type, - all while ensuring regulatory compliance is maintained and business policies are adhered to. Imagine having the ability to orchestrate data sharing initiatives from a single pane of glass console, securely and efficiently. 

Join Zohar Duchin, Head of Advanced Solutions, and Ronen Cohen, VP of Strategy, at Duality for a practical demonstration of how the latest in privacy enhancing technologies come together in one unified data platform to open up a new world of data collaboration. Previously considered impossible due to strict security requirements and rigid regulatory environments, data-driven enterprises are now able to perform collaborative data analysis on multiple data sources, across borders, employing multiple privacy enhancing technologies (PETs).

During this webinar, the presenters will demonstrate:
- How Duality Collaboration Hub enables the analysis of decentralized data sets while preserving privacy
- Case study - Investigating and preventing trade finance fraud
- Sensitive data flows, what is protected and from whom?
- Live demonstration of Duality Collaboration Hub

A One-Stop-Shop for Privacy Preserving Data Collaboration

Duality Chief Scientist and co-founder, Shafi Goldwasser, recently met with Prof. Michael Jordan - UC Berkeley to discuss data privacy and the internet.

Data and Trust In our Opinion (episode 4)

Recently, Professor Shafi Goldwasser, a co-founder of Duality Technologies, a Turing award and two-time Gödel Prize winner, interviewed Professor Daniel J. Weitzner, to discuss Internet privacy and public policy. Weitzner is the Director of the MIT Internet Policy Research Initiative, principal research scientist at the Computer Science and Artificial Intelligence Lab CSAIL, and professor of Internet public policy in MIT’s Computer Science Department.

Data and Trust: In our Opinion (episode 3)

Jules Polonetsky is the CEO of The Future of Privacy Forum (FPF), a think tank based in Washington DC. FPF aims to serve as a platform for policymakers, industry leaders, and academics to come together and discuss emerging technologies and the privacy challenges that they pose.

Data and Trust In Our Opinion (episode 2)

"How can we customize models on sensitive client data that we can't have while protecting our model IP?"

Today, we'll show you how our Confidential AI solution operationalizes advanced technologies and techniques (confidential computing, federated learning) into a plug-and-play software solution that AI and data teams can trust, and use.

Many organizations today have been developing proprietary models (e.g., risk models, predictive models) that are useful in guiding internal decisions and improving client services. Today, these clients are demanding customized models using their sensitive enterprise data.

Unfortunately, traditional methods of protecting data and software aren't enough to turn this demand into a new, scalable stream of revenue.

Join us as we discuss and show how our clients are accelerating time to market for ML/AI focused initiatives.

Protect the data. Protect the model. Leap ahead of the competition.

How to Customize Models for Clients, Securely

secure ai

trusted execution environments

confidential computing

model customization

genAI

risk models

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How to Customize Models for Clients, Securely

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