{"id":3846,"date":"2024-04-24T09:38:41","date_gmt":"2024-04-24T13:38:41","guid":{"rendered":"https:\/\/dfpdigital.com\/?p=3846"},"modified":"2024-04-24T09:38:41","modified_gmt":"2024-04-24T13:38:41","slug":"building-ethical-ai-4-strategies-for-mitigating-bias-in-systems-design","status":"publish","type":"post","link":"https:\/\/dfpdigital.com\/building-ethical-ai-4-strategies-for-mitigating-bias-in-systems-design\/","title":{"rendered":"Building Ethical AI: 4 Strategies for Mitigating Bias in Systems Design"},"content":{"rendered":"
We are at an exciting time in AI development. 49% of the general population uses generative AI, and 34% uses it every day, according to a <\/span>2023 Salesforce survey.<\/span><\/a> Businesses are leveraging AI to obtain <\/span>competitive advantage<\/span><\/a> by automating processes, supporting cybersecurity and fraud management, and enhancing customer experiences. With growing demand, companies like OpenAI, Google, and Minstral are racing to release new and <\/span>advanced LLMs<\/span><\/a> (Large Language Models) that outperform the competition.<\/span><\/p>\n AI is a part of our present and is the future. Yet as we navigate this pivotal era in AI development, we also face existential and ethical concerns. How can we ensure we\u2019re creating the \u201cright\u201d future? Who gets to decide what this future looks like?\u00a0<\/span><\/p>\n This discussion builds upon topics from my previous blog posts on AI,<\/span> 3 Myths of Artificial Intelligence<\/span><\/a> and <\/span>How to Use AI Responsibly<\/span><\/a>. In this exploration, we dive deeper into actionable strategies that developers, engineers, designers, and organizations can employ to design AI systems that prioritize bias reduction and ethical implementation.<\/span><\/p>\n<\/div>