In this expert Q&A Datacom’s Ana-Mari Gates Bowey, who leads growth for Datacom’s SaaS businesses, and Katie King, CEO of AI in Business and a member of the UK’s All-Parliamentary Group Taskforce on Artificial Intelligence, discuss how AI can help local government organisations serve their stakeholders and communities, core areas of opportunity for councils and local agencies, and how to address some of the challenges to AI adoption.
A: There are numerous promising AI technologies being adopted by local government organisations, spanning areas like efficiencies in service delivery and decision-making. For example, natural language processing (NLP) and chatbots are widely used to provide 24/7 access to citizen inquiries in cities like San Francisco, New York, and Dubai. Predictive analytics is another key technology, used for law enforcement to identify crime trends and for optimising traffic flows in local councils. AI is also transforming public health initiatives by identifying trends and predicting disease outcomes. In smart cities, AI helps optimise energy and waste management, with examples in Barcelona and Copenhagen. Other applications include document management, budgeting, resource allocation, staffing, sentiment analysis, and urban planning. Automated data processing is another common technology already in use with local government organisations, speeding up processes like permit issuance. These technologies often work alongside other systems to enhance efficiency and service delivery.
A: Local governments are finding themselves facing several common challenges when implementing AI technologies. One major challenge is the availability and quality of data, as they often deal with fragmented and incomplete data from legacy systems and siloed departments. Cost is another significant challenge, with budget constraints making it difficult to balance innovation with the implementation of costly AI solutions. To address these challenges, local governments can start small, form partnerships, seek grants, and consider cloud-based solutions to facilitate the transition and help manage costs.
A: It’s important to break down the concept of AI into manageable parts to avoid overwhelming people. Start by analysing centralised services like HR, marketing, and sales, and then create a taskforce to implement these innovations. The ultimate goal is for AI to solve problems and enhance the quality of life for citizens, so local government needs to focus on identifying how AI can do that. It’s more practical to start with small integrations and adopt hybrid solutions. Setting realistic expectations and focusing on targeted areas where AI can have the most impact is crucial. Prioritising the top three areas where AI can support rather than trying to implement it everywhere at once is a good strategy.
A: The readiness of the local government workforce is another challenge. Training and upskilling employees, collaborating with partners, and leveraging citizen developers are essential steps. Breaking down inter-departmental silos is also essential so that information and learning is being shared across the organisation – and to address the issues around fragmented data.
A: Privacy concerns demand robust data governance, compliance with regulations, and cybersecurity investments. It’s crucial to adopt a privacy-by-design approach from the start. This includes anonymisation of data, access controls, and data minimisation. Strong data governance frameworks, including policies and audit trails, are essential. Compliance with relevant privacy regulations is also critical – for example, the GDPR (General Data Protection Regulation) in the UK and EU and HIPAA (Health Insurance Portability and Accountability Act) in the US. Organisations need to be full compliant with the relevant policies and standards that apply and need to keep up-to-date as policies and standards evolve – Australia and New Zealand. Using encryption and advanced security protocols, and ensuring human oversight and transparency, are key steps.
A: Building public trust and ensuring transparency are critical. This involves participatory decision-making, pilot programmes with citizen involvement, and addressing regulatory and legal barriers. Governments should engage in real-time [sentiment] monitoring and involve the public in policy activities. Incremental implementation is also really important.
A: While AI can have errors, properly designed AI can reduce human errors. Implementing human oversight and using explainable AI (XAI) for transparency can help. For example, in criminal justice, a judge would still make the final decision, supported by AI tools. Ethical concerns, such as bias, need to be addressed through ethical frameworks and bias audits.
A: One major misconception is that AI will replace all jobs in the public sector. In reality, AI is more about augmentation, enhancing human capabilities rather than replacing them. Another misconception is that AI is too complex for local government. Starting with small, targeted solutions and using cloud-based options can make AI more accessible and affordable.
A: AI can play a significant role in risk management through predictive analytics. By analysing historical data and trends, AI can help identify potential risks such as budget shortfalls, infrastructure failures, or natural disasters. AI-powered systems can provide real-time monitoring and alerts for threats, such as sudden drops in water pressure, helping to prevent issues before they escalate. AI can also help detect unusual patterns of behaviour that may indicate fraud. For example, in procurement, AI can identify duplicate payments or inappropriate spending, helping to prevent financial loss and reputational damage. AI’s ability to analyse large datasets quickly and accurately makes it a valuable tool for fraud detection.
A: AI-driven urban planning can revolutionise how we manage traffic flows, transportation, and reduce congestion. For instance, smart grids can significantly improve the quality of life in cities by optimising traffic and reducing congestion. This can have a profound impact on urban living.
A: AI can monitor data from hospitals, social media, and environmental sensors to predict disease outbreaks and guide public health interventions in real-time. This capability is crucial, especially considering predictions of pandemics every 5-10 years. AI can help us prepare for and manage such disruptions effectively.
A: It’s hard to limit it to three areas as there is huge scope for AI to support local government teams in their work. But here are some broad areas where AI could have a significant impact:
AI in Business CEO Katie King and Datacom’s Datascape team have also developed a new webinar: Harnessing AI ethically in local government.
