Seeing is believing: data visualization is key for successful AI implementation
| AI is the art of effectively and efficiently analyzing data until interesting patterns or predictions emerge. But rows of numbers will not send out a maintenance team to the right issues, politicians will not adjust their policy, and doctors will not create personalised treatment plans. To move data from the data analyst's desk towards actual results, data visualisation is key. |
Companies and organizations collect huge amounts of data about customers, markets and trends. But what are you supposed to do with those millions of numbers and information? Through (interactive) maps, dashboards, equations, flow charts and other visual aids, data can become truly insightful and usable for people without data knowledge. Data visualization makes large amounts of data accessible and usable by non-specialists.
Why is data visualization so important to implement AI?
- Enlightening: An image says more than a 1.000 words: data visualization makes AI results understandable to non-technical users.
- Insightful: Visualizing data points makes it easier to identify patterns and trends.
- Steering: During the training of the system you can better monitor and adjust the performance if you "see" the results.
- Effective: Decisions can be made much faster on sight than on the basis of data lists.
- Impactful: With data visualization it is much easier to communicate findings to a wide audience and thus generate impact
How can I use data visualization?
Making research transparent
- language evolution: the way people laugh online, by The Pudding
- sociology: life expectancy and income over time
- economics: Big Mac Index
Instructions & steering of behaviour
- dashboards, such as the mobility dashboard of traffic centre Gent
- personalized exercises from the physiotherapist
- directing behavior, such as the crowd meter of an amusement park
Adjusting worldviews, opinions and policy
- making predictions transparent: global warming
- increasing understanding of the world: prosperity in the world
- Insight into technology: How the US generates electricity
Improved understanding of phenomena
- Fun ways to illustrate why certain phenomena occur (gamification!), f.e. bus bunching
- a full interactive website: Planet Virus
- letting a story speak: inequality in education (Florida)
Get started with data visualization!
Do you want to get started with data visualization? PUC KU Leuven Continue organizes a training on data visualization techniques in which you start with the basics and end with the creation of your very own interactive graphs.
Visualisation for and with AI
course - Bruges - PUC KU Leuven Continue
Isabelle Borremans
Isabelle is not an AI expert, but she has been communicating about AI (and AI training) for VAIA for four years. So, she knows exactly how to communicate effectively about AI training. Feel free to contact her with any questions on how to promote your AI course. She’ll gladly challenge you with questions like:
- Who is your target audience? Can you be more specific?
- What networks reach that audience?
- Where does your audience prefer to take courses?
- What AI skills does your audience need?
- Does your training match their needs?
Besides communication, Isabelle also works on VAIA’s strategy: Who is our audience? How can we reach them? How can we spark their interest in AI?
