5 steps to ensure responsible use of AI
As your organization creates an AI strategy, here are five steps you can take now to ensure responsible use:
1. Adopting a “responsible AI by design” approach to mitigate risks. Integrate responsible AI principles into your overall framework, building clear boundaries and priorities into your development lifecycle. “For example, create technical controls for development teams, conduct impact assessments, and regularly perform fairness testing,” says Vanvaria. “Orchestrate all of these tasks with an operating model that works for your organization, with the right roles coming together at the right time. »
2. Establish a responsible AI framework based on industry standards. Develop a deep understanding of existing and emerging industry standards for AI. “Make sure your AI framework takes into account different AI usage models,” says Vanvaria. “For example, using ChatGPT in-house and developing GenAI internally are different types of AI use.
3. Invest in technology capabilities for continuous monitoring. Establish systems that monitor your AI models and data sets continuously, checking for inconsistencies, biases and anomalies that could indicate a cybersecurity threat. “Once your models are operational, how are you going to have controls in place to ensure that no model and data drift occurs?” said Kapoor. To offset risk, create technical guardrails that highlight problems and train your algorithms to minimize bad outcomes. Some examples include ModelOps platforms, automated testing, and other monitoring solutions.
4. Work to ensure continued transparency and accountability. At all levels, keep the lines of communication open to ensure trust in AI systems. “Inform users that they can interact with AI systems, explain how decisions are made by the AI system, and leverage trust scores and the human-in-the-loop to evaluate the AI system’s decision-making. ‘AI,’ Vanvaria explains.
5. Create a rigorous training program anchored in real-world scenarios. Create a culture of awareness within your organization, with AI training sessions that consider real-world scenarios of what could go wrong and how to mitigate those risks. “The more practical the training, the less anxious employees will be,” says Kapoor. “And the more you give them access to AI tools, the more they will know what to expect and how to add value to the organization.”
The future of AI governance
As businesses continue to integrate AI at all levels, effective governance will depend on ensuring that legal, compliance risk, IT and business leaders have a seat at the table when decision making. “Due to the increased risks associated with AI, they must act collaboratively to ensure all angles are understood and addressed,” says Kapoor. Many businesses and large corporations are adopting a hub-and-spoke model for using AI across locations and branches. “Companies need to have some sort of central governance to make sure all these pieces of the puzzle fit together,” Kapoor says.
While it may seem ironic, AI itself could be a useful tool for AI governance. Algorithms can be used to test each other for bias and errors, and with AI-related cybercrime exponentially increasing, organizations may benefit from using AI-based cybersecurity tools. AI to detect malicious intentions. Nonetheless, keeping humans in the loop will remain a crucial part of any responsible AI framework. “It’s important to keep human oversight at the forefront,” Vanvaria says. “This is part of maintaining transparency, which is a key part of building trust in AI systems.”