Workshops
Module 3: Safe and Responsible Use of AI at Work
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Curriculum content
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This course begins by establishing a solid foundation in LLM security, focusing on key challenges such as prompt injection and sensitive information disclosure. Through case studies and real-world examples, learners understand the significance of secure LLM development and the common threats faced by AI systems today. The course then delves deeper into advanced security topics, including supply chain vulnerabilities and data poisoning. It emphasizes effective prevention strategies, such as input validation, output filtering, and combining security measures for robust defense. These modules provide practical skills for detecting and mitigating potential risks. In the final modules, learners explore emerging threats like misinformation and excessive system autonomy. They will also learn how to implement privacy-enhancing technologies, secure design principles, and regulatory compliance. By the end, you’ll have a comprehensive understanding of securing LLM applications for real-world deployment.
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This four-module course is designed to help attorneys and legal professionals understand and navigate the intersection of artificial intelligence (AI), data privacy, and cybersecurity. As the legal field increasingly integrates advanced technologies like ChatGPT and other generative AI tools, it's crucial to remain aware of both the opportunities and risks these innovations present. This course provides a comprehensive look at how AI can be effectively used in legal practices while addressing the challenges of maintaining data security and ethical standards in the face of emerging technologies. The course begins with a live, interactive webinar on using ChatGPT and generative AI, where participants can ask questions and get real-time answers tailored to their specific legal needs. Following this live session, participants will explore pre-recorded webinars covering data privacy, cybersecurity, and ethical issues surrounding AI. These recorded sessions will provide detailed guidance on how to protect sensitive information, guard against cyber threats, and navigate complex moral and legal questions as technology evolves. This course is ideal for attorneys, law firm managers, paralegals, compliance officers, and any legal professionals who are interested in integrating AI into their work while ensuring their practices are secure, compliant, and ethical.
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This course offers a thorough exploration of the ethical issues and best practices involved in implementing Artificial Intelligence (AI) within business settings. It starts by establishing the Foundations of AI Ethics, providing a solid understanding of key principles like fairness, transparency, and accountability. The course then moves into the Responsible Use of NLP Tools and Large Language Models, helping participants learn how to apply these technologies ethically and manage potential risks. In the AI Implementation in Internal Business Operations section, the focus shifts to how AI can be integrated into business processes to drive efficiency without sacrificing ethical standards. The course also covers Ethical Considerations in Customer-Facing AI, guiding businesses on how to use AI responsibly to build trust and safeguard user privacy. As AI systems can be biased, we explore strategies for Mitigating AI Risks and Biases, teaching methods to identify and address these issues. The course addresses Governance and Documentation, offering tools for managing AI projects and ensuring regulatory compliance. The Crisis Management and AI Incidents module prepares businesses to handle and resolve AI-related challenges swiftly and effectively. Looking toward the future, we cover Future-Proofing Ethical AI Practices, ensuring businesses stay ahead of evolving technologies and regulations. Finally, the Course Conclusion provides actionable insights for embedding ethical AI practices into organizational culture, ensuring long-term, responsible AI use.
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This module outlines the key obligations of Deployers—organizations that use AI systems in a professional or commercial capacity. While the strictest requirements apply to Providers, Deployers also have significant compliance responsibilities.
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With new tech trends comes new tech terminology. When Web 2.0 became big in 2005, we had to learn about as-a-Service models, user experience, and centralization. When DevOps became more popular in 2010, we had to learn about agile techniques, cloud computing, and automation. The latest tech trend of artificial intelligence (AI) is no different. A lot of us are faced with learning new concepts, like neural network architecture and machine learning models. On top of learning those foundational concepts, many of us have to figure out how to apply these concepts to our jobs (and how to do so securely). It is a lot to learn! In this seminar, join Erica Anderson (SafeStack Co-Founder and COO) as we set those foundational AI concepts together. We will go through the terminology, share resources you can use and share after, and then highlight the important parts where we need to focus our time on when it comes to security. This will be a helpful primer for anyone on your development team so you can all be talking the same language!
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Balancing the use of data with human problem solving requires a nuanced approach that recognizes the strengths and limitations of both. By integrating data with human judgment, fostering cross-functional collaboration, and building a data-literate culture, organizations can solve problems in a more informed, ethical, and sustainable way. This course introduces Artificial Intelligence (AI) and its role in solving real-world problems. Participants will explore key AI concepts, tools, and technologies such as machine learning, data-driven decision-making, and popular AI platforms. The course covers practical aspects such as building and integrating AI models, ethical considerations such as bias and privacy, and the future impact of AI on industries and employment.
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Artificial Intelligence (AI) is transforming the way we work, offering powerful tools that improve productivity, streamline communication, and assist in decision-making. However, these same tools also introduce new cybersecurity risks that can compromise sensitive information, expose organizations to phishing attacks, and create opportunities for malicious actors to exploit unsuspecting users. AI Cybersecurity for End Users is a practical training program designed to equip employees with the knowledge and skills needed to safely and responsibly use AI-powered tools in the workplace. This course emphasizes the critical role of end users as the first line of defence against AI-related threats, ensuring that everyone from entry-level staff to managers understands how to recognize risks, follow organizational policies, and escalate concerns appropriately. Through a structured learning journey, participants will learn to identify both obvious and hidden AI tools in their daily workflows, distinguish between safe and unsafe data sharing practices, and adopt secure usage habits such as verifying AI outputs and maintaining strong account protection. Learners will also gain the ability to recognize AI-generated phishing attempts, deepfakes, and other synthetic content that could pose threats to organizational security. By the end of the course, participants will have a practical AI security checklist they can apply every day, along with the confidence to make informed decisions when working with AI systems. This training not only strengthens individual awareness but also contributes to building a culture of security across the organization.
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Learn practical steps for guarding data privacy while using Generative AI tools in the workplace. Generative AI tools are revolutionizing the way we work. To use them effectively, we must be diligent in keeping sensitive information protected. In this Bigger Brains course, we outline how large language models work, explore how Generative AI tools use our data, discuss where that data may come from, and highlight the data privacy risks that should be considered. You will learn specific ways to protect your data as well as your customer’s data. You’ll also learn how to evaluate privacy policies to help determine which AI tools are safe to trust and which might misuse your data.