Artificial intelligence-based systems are becoming ubiquitous in our lives. Their rapid growth raises concerns about the global impact, ethics, governance, and accountability of these systems. There is a need to bridge the knowledge gap between AI experts and the wide variety of users that interact with AI and those impacted by it. We must make use of the potential of artificial intelligence systems while ensuring they do not worsen existing inequalities and biases. Arthur Cole speaks about how AI can complicate enterprise risk management in this article at VentureBeat.
The Advent of AI and Its Misuse
If not managed properly, artificial intelligence is more likely to ruin business processes and profits. OnCorps CEO Bob Suh provides a good overview of the harm artificial intelligence can cause using the example of social media. Regardless of whether AI is used with good intentions, it can still provide misleading or unfortunate results. The reinforcement learning agent (RLA) includes simple rewards that encourage the agent to improve in its goal to achieve the desired results. In the case of social media platforms, RLAs are used to maximize profit. However, a lack of balancing rewards will cause the agent to improve even when it may produce unrelated and undesired results. Social media bots in many instances achieved their intended profit objectives at the expense of inciting public opinion and weaponizing public opinion around the world.
Artificial Intelligence Is a Form of Risk Management
McKinsey partners Juan Aristi Baquero, Roger Burkhardt, Arvind Govindarajan, and Thomas Wallace say that implementing good controls over AI represents risk management at its core. However, AI’s autonomous nature suggests that the controls need to be more robust than those associated with standard IT. As AI becomes decentralized across the enterprise, it poses many new risks across compliance, operations, legal, and regulatory disciplines.
Additionally, the author shares best practices to manage risk associated with AI using up-front management.
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