{"id":33555,"date":"2025-01-17T20:22:48","date_gmt":"2025-01-17T20:22:48","guid":{"rendered":"https:\/\/peraltafinancing.com\/aerospace\/responsible-ai-the-business-risk-of-doing-ai-badly-is-too-high\/"},"modified":"2025-01-17T20:22:48","modified_gmt":"2025-01-17T20:22:48","slug":"responsible-ai-the-business-risk-of-doing-ai-badly-is-too-high","status":"publish","type":"post","link":"https:\/\/fivemor.com\/?p=33555","title":{"rendered":"Responsible AI: The business risk of doing AI badly is too high"},"content":{"rendered":"


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Responsible Ai Can Give Companies A Competitive Advantage. Credit: Shutterstock\/irenar.<\/figcaption><\/figure>\n<\/p><\/div>\n

Most tech leaders agree that a technology business without an AI strategy is fast becoming a ship without a rudder. Once a strategy is in place, however, it is the task of senior leadership to ensure that responsible AI is integral to its design. Convincing enterprise stakeholders of the importance of responsibly designed AI strategy should not be difficult when presented with the alternative.<\/p>\n

\u201cNo business wants to make headlines because they have used or misused customer or employee information in a way that causes harm,\u201d says GlobalData enterprise practice director Rena Bhattacharya. And reputational damage is not the only potential outcome of poorly implemented AI, adds Bhattacharya, noting that in certain industries or regions, hefty fines or legal action could ensue.<\/p>\n

There are numerous ways this could happen, from failing to adequately safeguard personal information or incorporate guardrails that prevent the distribution of misinformation, to using AI in a manner that is biased against or withholds privileges from a particular demographic group, explains Battacharya.<\/p>\n

Five globally agreed principles of responsible AI<\/h2>\n

The principles governing responsible AI are broadly: fairness, explainability, accountability, robustness, security, and privacy. But assuring customers, employees, partners, and suppliers that an organisation is implementing these appropriately is hard to substantiate, according to Battacharya.<\/p>\n

While it is early days for AI global standards, there are best practices related to security, data governance, transparency, use cases, model management, and auditing, that organisations can strive to implement. \u201cBut the concept of responsible AI is still fluid,\u201d adds Bhattacharya.<\/p>\n

\u201cCompanies should look towards their corporate ethics policies for guidance and pull together multidisciplinary teams that track and review not only how AI is being used across the organisation, but also understand the data sources informing the models,\u201d says Battacharya.<\/p>\n

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