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AI is not science fiction when used to do good

By Shawn Rogers, Vice President Analytic Strategy, Tibco Software

When you place data in the hands of smart companies, wonderful things happen. This is the birthplace of AI for good. We have entered a world where the available data is bigger than the human brain. Whether that data is leveraged in a car that drives itself, to direct your online shopping behaviour, or to recommend where PPE equipment is needed, it’s the next step in data’s evolution.

AI is prevalent in business today, as it takes data analysis to the next level and helps analyze profound data-driven problems. However, the notion of AI for good is only now taking center stage. At its core, AI for good is applying the same level of enterprise technology and thinking businesses do, to derive something helpful to society and communities.

Data-driven insights can do a lot of good

In the old days, we could take a spreadsheet, analyze it, and make some decisions for the good of our teams and people. But today, as a result of the sheer size of the data, we must call on technologies such as machine learning, a component of AI, to help us as humans learn things from data that isn’t obvious to the naked eye. When you apply this to doing good, you can start building dashboards, like the one that TIBCO has built, which offers visual insights into the current global health pandemic.

In a world where AI and machine learning are foundational to how we look at the information we have available, we can put data-driven insights in the hands of a wider more diverse group of people, which speaks to the democratization of analytics. When you democratize anything, you extend its reach and open up who has access to it, making data more commonplace and its application more pervasive. You can’t turn a news channel on today without some form of visual dashboard presenting data to you in one way or another. 

A great example is a dashboard ranking of charities on how much of their financial contributions they use on charitable actions and how much they are spending on themselves. By unifying the massive amounts of available data on these charities, the public can decide where they want to spend their money based on what appeals to their charitable nature and makes them happy. An essential part of advanced analytics is that it exposes information to people that wasn’t there previously. When you apply this to doing good – exciting things happen. 

We did a project where we analyzed the impact of parking citations in a city, and the data highlighted the fee structure of fines was extraordinarily punitive when it was applied to people of lesser income. Meaning they were disproportionately punished by parking tickets in a way that people with more significant financial means weren’t. When we brought it to the attention of the city, they made changes to the process. Why is this good? When you start taking unfairness out of an equation, you’re applying analytics and AI for good.

Knowledge is power

Data isn’t always understood, and that can be a challenge, whether you are using it to innovate in a business or to fuel charitable actions. People still rely too much on technology and place too little emphasis on people and culture. While we are getting better at understanding data, and we are shifting towards a data in everything culture, people are still disconnected.

It is one thing to have the data to show a chart or a dashboard; it often takes humans to decide and act upon that data. The technology is there, the culture is shifting, and people are coming along, but when the three meet at the same point, that is when we will have the complete orchestra playing at the right time and all playing in the same key. This is particularly relevant when you are using AI for good because it revolves more around the people and the actions presented in the data than the technology.  

We recently worked with a company in South Africa called the Data-Shack, who are using advanced analytics to track the sales, distribution, and use of the weapons used in Rhino poaching. By getting to the source, they were able to create patterns in the data so that they could help authorities establish preventative measures to curb the poaching itself.

In short, AI for good lets companies better work out ways to engage not only their customers but their partners, vendors, and the communities that they live in too.

Partnering for the greater good

Those organizations doing great things with their data are those who partner to do AI for good. There are many moving parts in getting value out of data, and charities, nonprofit or educational institutions, don’t just need AI, they need partners. These bodies rely on an ecosystem to support them. 

AI for good relies on connecting data, unifying it intelligently, and then using it to confidently predict outcomes that lead to meaningful actions that impact our people, our communities, and even our environment.

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