Written by Sabrina Palme, AI Governance and Risk Expert at Palqee Technologies
As artificial intelligence systems become more ubiquitous, new EU regulations are in the pipeline to ensure they are developed and used responsibly. A core requirement of the EU's Artificial Intelligence Act (EU AI Act) is for organisations to implement a comprehensive risk management plan and system for high-risk AI applications.
But what exactly does an AI risk management plan entail to meet EU AI Act standards? This post will provide practical guidance for mid-size companies looking to establish compliant risk management protocols.
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What is an AI Risk Management Plan according to the EU AI Act?
At its core, AI risk management involves identifying potential hazards associated with your AI systems, assessing the severity of each risk, and establishing procedures to avoid or mitigate dangers - all requirements outlined in the EU AI Act. This applies to risks affecting health and safety as well as risks related to fundamental human rights and discrimination.
Key areas to evaluate include data inputs, training processes, model assumptions, and real-world usage. You must document all risks uncovered and how they are addressed according to the regulation's transparency rules.
1. Conducting an Initial AI Risk Assessment
The first step is conducting a thorough assessment of your AI systems to surface potential dangers as mandated by the AI Act. Look at risks that could arise from faulty data, poor development practices, technical failures, or unintended real-world consequences. Draw on domain experts across your organisation to brainstorm safety hazards and sources of unfair bias.
Consider using frameworks like Palqee's free EU AI Act Framework to help assess compliance requirements and Ivy or Monte Carlo simulation to detect risks. Clearly document all risks identified and estimate the severity of each one as stipulated by the regulations.
2. Devising Risk Mitigation Strategies
Next, develop a set of mitigation strategies to address the risks identified, meeting standards put forth in the AI Act. For example, you may need to overhaul biased datasets, improve model explainability, implement continuous testing protocols, refine the selected use cases, limit real-world exposure until risks are addressed, or append safety measures.
Consult with legal counsel, developers, users, and other stakeholders to create robust, tailored mitigation plans.
3. Creating a Risk Monitoring Process
Ongoing monitoring processes must be established to continually assess for new risks once an AI system is operational, as mandated by the EU AI Act. This includes tracking key risk indicators, conducting periodic audits, implementing incident reporting procedures, and updating strategies as new dangers emerge.
Consider using Palqee's automated monitoring solution to easily implement continuous oversight. Be sure to document all monitoring protocols and continuously improve over time.
Consider assigning risk management responsibilities to specific team members.
4. Meeting EU AI Act Documentation Standards
Thorough documentation is required under EU regulations. Be sure to compile full technical documentation covering the risk management system's design, processes, implementation, and maintenance.
The documentation should demonstrate to regulators you are adequately assessing and mitigating risks according to the transparency obligations in the AI Act. Store documentation in an organised, accessible repository.
The EU AI Act brings welcome oversight to managing dangers associated with AI systems.
While risk management presents new challenges, establishing rigorous protocols today will lead to safer, more trusted technology. Consult legal counsel and compliance partners if unsure how to craft an EU-compliant plan. With proactive efforts, mid-size companies can implement effective risk management capabilities meeting European standards.
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