Beyond the Algorithm: Mitigating AI Risks — Lloyd Emerson Johnson

Talking Trends
3 min readApr 12, 2024
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Artificial Intelligence has emerged as a transformative tool, revolutionizing, and enhancing efficiency across various industries. With organizations increasingly integrating AI into their operations, it is crucial to scrutinize the potential risks associated with this technology. Understanding and mitigating these risks is crucial to ensure responsible and secure deployment of AI systems.

During my recent participation as a speaker at the Darla Moore School of Business panel, we delved into Generative AI and the Future of Business. We discussed both the risks and opportunities associated with the integration of artificial intelligence in the modern world. Emphasizing the need for strategic management, we highlighted the significance of effectively navigating the risks to maximize the potential benefits.

Transitioning from the broader context to practical considerations, one of the primary concerns with implementing AI systems is the management of vast amounts of sensitive data. As organizations leverage AI algorithms for decision-making, the potential for compromising privacy and proprietary data is apparent. Training and AI Governance and Use policies in addition to robust data protection measures, stringent access controls, and encryption protocols are imperative to guard against unauthorized access and data leaks and breaches.

The issue of bias within AI systems poses another significant risk that requires specific management strategies. AI algorithms are only as unbiased as the data they are trained on, and the perpetuation of societal inequalities is an ongoing concern. The need for continuous monitoring and auditing of AI models to identify and rectify biases are evident.

The “black-box” nature of some AI models presents another challenge that demands attention from a risk management perspective. Understanding how an AI system reaches a specific decision is essential for assessing risks and ensuring accountability. Efforts to enhance the transparency and understanding of AI algorithms are vital components in the risk management toolkit, thereby enabling organizations to better manage and mitigate potential issues.

A risk management approach entails developing comprehensive contingency plans, conducting regular system audits, and implementing robust cybersecurity measures to minimize the impact of any disruptions. While AI promises transformative benefits, its integration requires a vigilant risk management strategy. Organizations must collaborate with risk management experts to proactively identify, assess, and mitigate the multifaceted risks associated with AI implementation. Striking a balance between innovation and risk mitigation is essential to ensure that AI contributes positively to society while minimizing potential negative consequences.

Lloyd Emerson Johnson is a results-oriented strategic advisor. With over 40 years of international, broad-based experience, Lloyd considers various disciplines in his approach to management and board governance. Through effectively evaluating all corners of a business, Lloyd Johnson has reinvented the roles of a strategic partner and stakeholder champion. He is a creative visionary who transforms businesses to be effective throughout all of their operations and finances. The pragmatic leader specializes in risk management and ensuring that businesses are prepared for uncertain circumstances.

Connect with Lloyd Johnson on LinkedIn.



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