{"id":53752,"date":"2023-03-01T09:04:42","date_gmt":"2023-03-01T09:04:42","guid":{"rendered":"https:\/\/www.techopedia.com\/?p=53752"},"modified":"2023-03-01T11:07:17","modified_gmt":"2023-03-01T11:07:17","slug":"4-principles-of-responsible-artificial-intelligence-systems","status":"publish","type":"post","link":"https:\/\/www.techopedia.com\/4-principles-of-responsible-artificial-intelligence-systems\/2\/34938","title":{"rendered":"4 Principles of Responsible Artificial Intelligence Systems"},"content":{"rendered":"

As AI becomes all-pervading, AI systems need to be more transparent about how they arrive at their decisions. Without a standard governance framework, however, the task of supporting explainable AI<\/a> is not easy. (Also read: <\/strong>Why Does Explainable AI Matter Anyway?<\/strong><\/a>)<\/strong><\/p>\n

Recently, Techopedia brought together the following leaders<\/a> to discuss how and why organizations are adopting Responsible AI<\/a> as a governance framework:<\/p>\n

Anthony Habayeb<\/a>, co-Founder and CEO of Monitaur<\/a>.<\/div>\n
Andrew Pery<\/a>, AI ethics evangelist.<\/div>\n
Alyssa Lefaivre \u0160kopac<\/a>, director at the Responsible AI Institute<\/a>.<\/div>\n

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The panel discussion produced some great talking points that you can use to inspire discussions about AI governance in your organization. They include the ideas that:<\/p>\n