UiPath's AI Trust Layer: Governance Layer around AI powered Automation

Ethical Concerns of Adapting GenAI within an Organization

In the ever-evolving landscape of technology, the integration of General Artificial Intelligence (GenAI) within organizations raises significant ethical concerns. The potential misuse of AI, biased decision-making, and the impact on employment are just a few of the ethical dilemmas that organizations must navigate. Addressing these concerns is paramount to ensure responsible and sustainable AI implementation.

Why Setting up an Ethical Policy is Important?

To mitigate the ethical challenges associated with AI adoption, organizations must establish clear and comprehensive ethical policies. These policies serve as a guiding framework, outlining the principles and values that govern the development and deployment of AI technologies. Ethical policies not only foster trust among stakeholders but also contribute to the responsible and accountable use of AI within the organization.

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Introducing UiPath AI Trust Layer

To address these concerns and instil confidence in users, UiPath introduces the UiPath AI Trust Layer. This addition to the UiPath Business Automation Platform is designed to provide a comprehensive solution for data privacy, transparency, and control when leveraging GenAI capabilities.

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What is UiPath AI Trust Layer??

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The UiPath AI Trust Layer is founded on three core principles:

Trust

UiPath pledges the highest level of integrity, security, and privacy for all data interacting with UiPath products and third-party LLMs. Maintaining an audit trail of data usage is essential for upholding ethical and compliance standards.

Transparency

Complete visibility into the use of GenAI features, models, and data transfer from the UiPath Platform to third-party models is granted. Dashboard audit tools, cost controls, and zero data sharing outside customer-managed UiPath tenants ensure responsible AI practices.

Control

UiPath customers gain administrative control over sensitive data sent to LLMs, along with role-based policies for managing developer access to GenAI features. This ensures a secure and governed environment for AI-powered automation.

The UiPath AI Trust Layer empowers organizations with:

• Generative AI Feature Controls: Administrative controls at the organizational and tenant levels, including default opt-out training policies for third-party models.
• PII/Sensitive Data Filtering: Masking personally identifiable information, encryption of data at rest and in transit, and a commitment to not using data to improve third-party GenAI models.
• Usage Auditing and Cost Control: Visibility into GenAI feature costs, usage distribution, and a secure LLM gateway for confidential data transfer.

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Why UiPath AI Trust Layer is Crucial for UiPath AI Solution?

UiPath's commitment to data privacy and ethical AI is not just a promise but a set of concrete policies and practices embedded in the very fabric of their AI solution. Here's why the UiPath AI Trust Layer is indispensable for ensuring the responsible and secure use of AI within the UiPath ecosystem:

1. Data Usage Governance:

UiPath's enterprise policies explicitly state that customer data passed through the UiPath Platform is not used for training third-party Language Model Models (LLMs). This ensures that your data remains confidential and is not utilized in unintended ways, providing a clear and stringent governance structure.

2. Transparent Data Transmission:

Customers often wonder where their data goes and how it's used, especially when dealing with third-party LLMs. UiPath addresses this concern by securely sending data used as context for prompts only to third-party LLMs within the UiPath trusted ecosystem. This transparency in data transmission builds trust, assuring users that their information is handled securely and responsibly.

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3. Data Storage and Processing Assurance:

The location of data processing by third-party sub-processors is disclosed on the UiPath Trust and Security site. Customers have the flexibility to choose the region of tenants, ensuring that associated product use by users in those tenants is processed in the selected region. This aligns with UiPath's commitment to data residency, and the assurance that no customer data is stored outside the established UiPath "trust boundary" by third-party models.

4. Governance Over AI Lifecycle:

The importance of governance over the lifecycle of data used with AI models cannot be overstated. UiPath recognizes this and emphasizes the creation of proper training programs and process protocols. This ensures that AI objectives align with ethical and compliance guidelines, providing customers with the confidence that their data is handled responsibly and ethically throughout its lifecycle.

5. Reliable, Accurate, Secure, and Explainable AI:

The UiPath AI Trust Layer goes beyond just data governance. It ensures that model predictions are reliable, accurate, secure, and explainable. This commitment to the quality and integrity of AI outputs reflects UiPath's dedication to providing users with a trustworthy AI solution.

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With the UiPath AI Trust Layer, organizations can embrace GenAI-powered automation confidently. Developers can build automations faster, business users can leverage their expertise, and administrators can govern with rich policies.

As the AI landscape evolves, UiPath's commitment to responsible AI practices ensures that users can harness the full potential of GenAI without compromising on ethics or security.

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