Guide to Navigating AI Compliance with Thoropass & Dynamo AI

The world is abuzz with advancements in AI technologies like ChatGPT and generative AI (GenAI). And as we see a significant portion of new companies entering the market being centered around AI in one form or another, this introduces a unique set of challenges and opportunities for the world of information security and compliance.

Sam Li, Thoropass’s Co-Founder, and CEO, recently sat down with Vaik Mugunthan, CEO of Dynamo AI, to discuss the key reasons regulation is urgently needed, what exists today, and how businesses can safeguard themselves.

You can watch the full video here:

New risks and challenges in the AI era

The proliferation of GenAI and large language models (LLMs) has created new risks and challenges for regulators, consumers, and industry practitioners alike.

As businesses embark on their AI journeys, it’s crucial to familiarize themselves with the evolving compliance landscape and understand the regulations on the horizon. Knowledge of these regulations is key to protecting both the company and its customers.

AI is advancing across industries at an unprecedented speed. At Dynamo AI, a major focus is tracking these regulatory changes to ensure that enterprises deploy AI models in a privacy-preserving and regulation-compliant manner. Their research and experience have identified four key areas that AI regulations aim to safeguard.

Dynamo AI’s four key areas of AI compliance

1. Security and Privacy: Traditional security policies and systems are no longer sufficient to address the complexities of AI. Enhanced measures are needed to prevent risks such as data leaks or breaches of personally identifiable information (PII). For instance, companies like Dynamo AI in partnership with other leaders in the field, play a key role in offering solutions that prioritize privacy and security.
2. Misinformation and Hallucinations: One of the critical concerns with AI is its potential to generate false or misleading information, commonly referred to as “hallucinations.” These fabricated outputs can seem deceptively real, posing significant risks if unchecked. It’s also crucial to guard against AI models spreading misinformation through deepfakes or other manipulative content.
3. Protection of Proprietary Data: Protecting proprietary data and intellectual property rights is another key aspect of AI regulation. Standards must be set to ensure AI systems are safe, secure, privacy-preserving, and trustworthy. Before deployment, enterprises must engage in robust testing, evaluation, and risk mitigation.
4. Safety and Transparency: Regulations like the EU’s AI Act enforce clear guidelines, prohibitions, and enforcement mechanisms for AI systems operating within the European Union. This framework categorizes AI systems into four tiers based on the sensitivity of the data involved and the specific use case, explicitly prohibiting practices deemed to pose unacceptable risks.

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Regulatory frameworks around the world

Globally, regulatory efforts are ramping up to address the complexities associated with AI. For example:

• The EU AI Act emphasizes transparency, privacy, and safety, introducing penalties of up to €35 million or 7% of an organization’s overall revenue for non-compliance.
• ISO 42001 focuses on ensuring AI systems are developed, deployed, and managed responsibly, with principles such as fairness, transparency, data management, and privacy.
• Local regulations are being introduced such as in New York and Colorado. These states have enacted specific AI regulations addressing pay transparency in job postings and preventing unfair discrimination from using external data and algorithms.

Thoropass’s steps for implementing AI safely and responsibly

As we explore global regulatory efforts, businesses must also consider how to implement AI technologies responsibly. Here are three foundational steps Sam suggests the following three key steps to get started:

1. Document AI Use Cases: Clearly define and document the AI use cases relevant to your organization.
2. Integrate AI into Your Compliance Program: Ensure AI-related processes are part of your existing compliance frameworks.
3. Conduct Technical and Compliance Assessments: Evaluate the risks associated with each AI use case to help prioritize efforts within your compliance teams.

Compliance frameworks such as SOC 2, HITRUST, and ISO are essential for setting a strong foundation to adopt AI safely and effectively.

Stay informed and ahead of the curve

AI is undeniably transforming the landscape of information security and compliance. As organizations navigate these rapid advancements, staying informed about global regulatory developments and integrating comprehensive AI governance measures is crucial. 

Watch the full video to gain valuable insights on how to align your AI strategies with emerging compliance standards and protect your organization in this new era of innovation or speak to the Thoropass team today to learn how we can help you embark on your AI compliance journey.

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