{"id":12908,"date":"2024-06-11T07:00:00","date_gmt":"2024-06-11T15:00:00","guid":{"rendered":"https:\/\/formtek.com\/blog\/?p=12908"},"modified":"2024-04-01T10:27:17","modified_gmt":"2024-04-01T18:27:17","slug":"navigating-the-challenges-that-ai-poses-to-data","status":"publish","type":"post","link":"https:\/\/formtek.com\/blog\/navigating-the-challenges-that-ai-poses-to-data\/","title":{"rendered":"Navigating the Challenges that AI Poses to Data"},"content":{"rendered":"\n

It’s becoming increasingly clear that companies that harness the power of data are poised to thrive, while those lagging behind risk obsolescence. We are in the new age of data-driven decision-making, where artificial intelligence (AI) takes center stage.<\/p>\n\n\n\n

Traditionally, business decisions were made based on gut instincts, intuition, and historical practices. However, the advent of AI has revolutionized this paradigm. Data-driven businesses now leverage AI tools like ChatGPT to inform their strategies, predict market trends, and enhance customer experiences. <\/p>\n\n\n\n

But there are hiccups. Enter shadow AI\u2014the clandestine use of AI tools within organizations. Imagine an employee deploying an AI assistant during a confidential client call without IT\u2019s knowledge. Such unauthorized AI usage poses risks: data leakage, biased outputs, and regulatory noncompliance. Organizations must shine a light on shadow AI to protect sensitive information.<\/p>\n\n\n\n

Some of the problems caused by the often well-intentioned “shadow” use of AI include:<\/p>\n\n\n\n

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  1. Data Leakage<\/strong>: LLMs (Large Language Models) can inadvertently spill sensitive data. Proper configuration and access controls are crucial to prevent accidental disclosures.<\/li>\n\n\n\n
  2. Overly Permissive Configurations<\/strong>: LLMs should filter user inputs to avoid incorporating sensitive information into training data.<\/li>\n\n\n\n
  3. Bias and Error<\/strong>: Biased or erroneous training data leads to biased AI outputs. Vigilance is essential to ensure fairness.<\/li>\n<\/ol>\n\n\n\n

    Governments worldwide recognize the need for responsible AI. The Bletchley Summit<\/a> and the U.S. Executive Order<\/a> emphasize safe AI development. The EU leads in regulation<\/a>, with the EU AI Act focusing on consumer protection and risk-based classification.<\/p>\n\n\n\n

    AI is used widely for financial services, from anti-money laundering to credit modeling. However, the risks are real. The OWASP Top 10 for LLM Applications <\/a>highlights vulnerabilities like data poisoning and sensitive information disclosure.<\/p>\n\n\n\n

    Going forward, organizations must:<\/p>\n\n\n\n