At the core of GenAI's challenges lie three major flaws:

• Hallucinations
• Bias
• Authenticity issues

Hallucinations refer to the unreliability of AI-generated content, where the model may produce outputs that deviate from reality or intended use cases. Bias, stemming from the data used to train the models and the algorithms themselves, can perpetuate discriminatory outcomes and skew decision-making. Authenticity issues arise when AI-generated content lacks a “human touch,” potentially eroding trust and credibility among stakeholders.

A risk manager’s responsibility to proactively assess and mitigate these risks before integrating GenAI into an organization's technology stack. This involves conducting thorough due diligence on potential AI solutions, evaluating their hallucination rates, and setting up pilot programs to assess their performance in real-world scenarios. Implementing robust internal controls and monitoring mechanisms is essential to identify and address any vulnerabilities or unintended consequences.

An example of how easy it is to get this wrong can be seen in the cautionary tale of Zachariah Crabill, a lawyer who infamously cited fictional case law generated by ChatGPT, which ultimately cost him his job. Even after paying that steep price for failing to catch the hallucination before it reached his official court documents, Crabill is still a proponent of GenAI. “There's no point in being a naysayer, or being against something that is invariably going to become the way of the future,” he notes.

The misalignment of incentives among end users, software developers, and regulators further complicates the GenAI landscape. The rush to market and the prioritization of efficiency over accuracy can lead to subpar products and increased risk exposure. Risk managers must take ownership of ethical AI principles and quality assurance processes within their organizations, rather than solely relying on software providers to meet these standards.

Moreover, the regulatory landscape surrounding GenAI is still evolving, with governments grappling with the need to balance innovation and risk mitigation. The pressure to maintain competitiveness in the global AI race can sometimes overshadow comprehensive risk assessments and ethical considerations. "Regulators have no idea what they're doing, and the companies move so fast that nobody knows how to keep up," noted UC Berkeley School of Information professor Hany Farid in the Wired article GenAI Learned Nothing From Web 2.0. Risk professionals must remain vigilant and advocate for responsible AI practices that prioritize the long-term implications over short-term gains.

Despite these challenges, the potential of GenAI cannot be ignored. Organizations that successfully harness its power while managing the associated risks will undoubtedly gain a competitive edge. To navigate this complex landscape, risk managers should adopt a proactive and strategic approach grounded in three fundamental principles:

1. Understand and acknowledge the inherent flaws of GenAI systems.
2. Assess, mitigate, and continuously monitor AI-related risks.
3. Carefully consider potential vulnerabilities and their implications for critical systems and decision-making processes.

By adhering to these principles and applying standard best practices for operating a business, risk managers can effectively embrace GenAI while safeguarding their organizations from potential disruptions and compromised quality. The path forward requires a delicate balance between embracing innovation and implementing robust safeguards and compliance measures. "There's no point in being a naysayer, or being against something that is invariably going to become the way of the future." says Zachariah Crabill, a lawyer who infamously cited fictional case law generated by ChatGPT which ultimately cost him his job.

As the GenAI landscape continues to evolve at an unprecedented pace, risk management professionals must remain at the forefront, guiding their organizations through this transformative journey. By proactively addressing the challenges and seizing the opportunities presented by GenAI, we can unlock its vast potential while ensuring the responsible and ethical deployment of this game-changing technology.