Overview of AI Technology Risk Factors

• AI Technology Factors and Bias
• Overdependence on AI without human oversight can create blind spots and make systems susceptible to manipulation.
  • Algorithmic Fairness and Bias If AI algorithms are not designed and deployed ethically, they can exacerbate social inequalities and discrimination.
  • Loss of control and accountability  When complex AI systems make critical decisions, understanding and attributing responsibility for those decisions becomes challenging.
  • Data dependence AI’s effectiveness heavily relies on the quality and quantity of data it’s trained on. Biased or incomplete data can lead to inaccurate results and unreliable predictions.
  • Black box problem Some AI models lack transparency in their decision-making process, making it difficult to understand why they flag certain events as threats and potentially hindering troubleshooting.
  • False positives  Overly sensitive AI systems can generate a high number of false positives, leading to alert fatigue and diverting resources from genuine threats.
  • Adversarial attacks  Malicious actors might exploit vulnerabilities in AI algorithms by manipulating input data, potentially compromising security measures.