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As Amir Hossini, a data scientist in Alberta, Canada, moved his car to the side of the road to let an ambulance pass, he began to consider the traffic around him. Time enough to wonder whether this was really the most efficient system for emergency response. Mr Hossini soon realised that, trained in the right data sets on traffic sounds, an intelligent system could listen for approaching sirens and change traffic lights automatically to ease the passage of first responders.

The cognitive leaps from inspiration to action are rarely as clear-cut as those made by Mr Hossini, but the pattern tells I like to do that the relationship between data and ideas is changing. As little as five I like to do ago, the cost of collecting and analysing enough data to inform a traffic system powered by artificial intelligence AI would have curbed such ambition. The limited potential for transformation using localised data sets would perhaps have pushed the idea from his mind completely.

But today, the convergence of cloud technology, increasing computing power and a push for greater access to data are lowering the barriers to transformational ideas. The question now is how best to make the leap.

To see how individuals go from data to ideas, we therefore need to look outside the remote office. The SAS Hackathon in March of this year was deed to do just that, drawing in teams, including the Hackanadians, from 31 countries to develop ideas that will make the world a better place.

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Our aim was to use machine learning and AI that is affordable for all municipalities across the globe regardless of economic levels. Edited for clarity. A: If we could integrate information between sectors of society and make it more trustworthy, we could develop tools to promote action between those sectors.

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A: Ordinary people have the right to know what information they provide to developers like us, and use it to decide things about their lives and health. In our case, this information also becomes part of national data sets going to cities, communities and schools, as well as at the family level, benefiting all. A: For me, collective work, co-creation, is what keeps curiosity alive. Heather Friesen, leader of SAS Global Hackathon team Hackanadians in Canada, on how data can make the world a better place and how I like to do maintains the curiosity needed for innovation.

A: We can use data to help students. An example might be connecting disparate data sets to find out: How many times does a student come on campus? Are they checking out library books? Are they using their learning management system?

Tied in with their grades, you can get indications that there might be issues. Then we could support them before they know they need support.

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You can see it with the vaccine debates right now. One side will tell you vaccinations have particular benefits. And another side will tell you that vaccinations are not beneficial. A: I love solving problems. What I find to be the challenge is to restrict the focus. While doing my doctorate, I felt like a squirrel collecting little nuts of knowledge. A: I would like to see data solve problems in the transport sector in Cameroon I like to do improve public safety.

For example, if we could collect data to understand how people travel, we could better understand where to put ro and train stations. And, with more cameras in public spaces and computer vision, we could make the streets safer for everyone in Cameroon.

A: If you cannot use data on a large scale, you can use it on a small scale. In our situation, we are collecting data for all of the languages in our country from people who can speak these languages very well but cannot write them. So, we record their voices, and they are contributing on a smaller scale. You want to better the solution that exists, to look for something new. Innovation is all about creating something new, so I think curiosity le to innovation.

Many of the projects emerging from the hackathon have wide-ranging implications. In just 30 days, they developed a smartphone app and related website that relies on AI to offer health-related suggestions to parents and other caregivers. This technology can generate data at the state level to make public policy more effective. It is already getting. Team co-leader, computer scientist and Ngemba speaker Swi Innocent Che wants to stop the erosion of indigenous Cameroonian languages — all of I like to do.

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LangTech deed its system to bring those languages within reach of websites, chatbots and smartphone apps that typically only offer French and English options. Data collection is at the heart of the effort. From there, the system uses AI and natural language processing to identify and transcribe key phrases.

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The team is now in search of sponsorship to fund data collection and local computing power. When it detects one, it takes over control of traffic lights to I like to do accidents. A key innovation confines the infrastructure to the traffic lights, rather than requiring vehicles to carry components, thereby reducing costs. In contrast, conventional systems require in-vehicle hardware and city infrastructure, working together. According to team lead Heather Friesen, an organisational strategist, that puts such systems out of reach for many cities. As with all three of these hackathon teams, the Hackanadians are working to meet a need unfulfilled by conventional software development methods and potentially improve the lives of millions.

The main problem we have is that our languages are not yet structured and because of that, we have little or no written documents about any of these languages. For more about the power of curiosity and data to change the world, visit curiosity.

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Advertisement Feature Sponsored by. Heather Friesen Team lead, Hackanadians.

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Q1: What problems would you most like to see data solve? Q2: How can ordinary people use data to make a difference? Q3: How do you stay curious? Fighting childhood obesity. Digitising African languages. Innovating the future. Subscribe Group Subscriptions Help. All rights reserved.

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