CIO OPINION prefer analytics embedded within their natural workflows . Vendors must describe how their platforms include a large language model , LLM integration for data retrieval and prompt engineering , while buyers should assess what is available as a plug-in to a thirdparty application , such as ChatGPT .
Promote collective intelligence
Initiatives should be in place to encourage the sharing of analytics insights generated from GenAI chatbots , fostering a culture of collaboration and shared learning . Training must establish adaptive governance mechanisms to avoid hallucinations from AI chatbots and improve interpretability .
It is crucial for data and analytics leaders and their organisations to stay updated on the latest advancements in AI-enabled NLQ and chatbot technology . Otherwise , they may fall behind and face potential violations of data and analytics governance policies , as well as proliferation of content due to the constantly evolving analytics technology and digital landscape .
Ethics framework for predictive analytics
Automation is crucial for justice and public safety organisations as they navigate changing public expectations and cope with diminishing talent pools in many regions . CIOs must prioritise the ethical expansion of data and technology usage to increase productivity and guide their organisations towards achieving mission objectives .
According to Bill Finnerty , VP Analyst at Gartner , by 2026 , over 65 % of public safety organisations will establish an ethics framework to guide the use of predictive analytics for proactive incident response .
In recent years , advanced predictive analytics has been successfully used in different industries , such as healthcare and public safety . For instance , the Dubai Police have adopted predictive policing software called Crime Prediction .
This software was created to support the UAE ' s Smart Governance Initiative and is specifically designed to complement the modernised approach of the Dubai Police force in preventing crime and ensuring public safety .
However , in the public sector , there has been hesitation and concern surrounding the use of predictive analytics . The public ' s fears about potential overreach by law enforcement are heightened by the lack of transparency from public safety organisations regarding their utilisation of data and predictive analytics to enhance their mission objectives .
The growing opportunities to use AI for surveillance and advanced analysis present new risks to the ethical and proper handling of data by public safety organisations . Additionally , the absence of national or international standards leaves both these organisations and communities in a constant state of uncertainty regarding the appropriate use of data and technology in predictive and proactive service models .
Until ethics frameworks are established and normalised , government decision makers struggling to determine the appropriate use of predictive service models will err on the side of caution in evaluating related solutions and miss opportunities to understand the potential mission impact .
CIOs leading public safety and justice organisations must engage leadership or the governance board to establish a working group for developing an ethics framework for the use of predictive analytics in operational areas of the department , and including external parties such as community leaders , academics and industry professionals .
Government CIOs must also enforce a policy of transparency regarding any analytics or Artificial Intelligence models utilised for operational purposes . This can be achieved by requiring vendors to disclose the models they use in their solutions and making this information available to the public upon request .
It is essential to establish a process that allows the community to verify the use of predictive analytics and ensure adherence to department policies , in order to build trust in their implementation . p
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