Big Ben and Westminster Bridge in the Evening, London, United Kingdom
The city also plans future smart cities initiatives such as creating a cross-sector board of governance and greater sharing of data resources.
The city of London has outlined its vision for the future of smart cities through a series of charters. They outline innovation ideals and principles while also setting up boundaries to ensure all citizens remain protected.
The Emerging Technology Charter outlines the way London envisions innovation while minimizing risk. Emerging technologies like sensors can help the city make traffic safer, for example, but their use will require trust from the people.
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London will also create a Data Protection Impact Assessment to ensure that high-risk data use remains transparent to citizens. It provides guidelines for companies and entities to explain data use, develop transparent data models, and ensure future impact remains clear.
See also: AI Controlled Traffic Lights Tested in New Project
A charter from business groups also on the table
The business group London First also launched a data charter, providing guiding principles for data usage. It’s designed to help the private sector design data plans that offer the best of new technology for everyone while protecting privacy and security.
It also outlines ways companies can open up about their data, as fostering a culture of sharing provides collaborative approaches to solving current challenges. It ensures that the city can respond to these challenges quickly and efficiently.
See also: Technology for Good: Enabling Safety via 5G and Autonomous Solutions
Pilot smart cities programs on the way
The new charters will help guide pilot smart city initiatives, such as the use of data to place electric vehicle chargers in optimum locations. The city also plans future initiatives such as creating a cross-sector board of governance and greater data-sharing resources, such as templates and data-sharing agreements.
Elizabeth Wallace is a Nashville-based freelance writer with a soft spot for data science and AI and a background in linguistics. She spent 13 years teaching language in higher ed and now helps startups and other organizations explain - clearly - what it is they do.
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