Ali Rome’s top TED talks on data

The table above is meaningless. It shows names, yes and no, but not what yes/no relates to. The table to the right clarifies this by adding headers to the table, these categorize the data and allows us to make a decision if required. In this instance, it may be which students deserved a detention due to an unauthorized absence.

“Big Data” is no different to  any other kind of data – there is just A LOT of it, meaning that the information provided from analysing it can lead to much more accurate decisions being made.

Data is information that has yet to be categorised, and information is knowledge with no application. That means if someone says what the data is and figures out an effective way to use it, then it can provide knowledge.

In the wake of the Cambridge Analytica Facebook scandal, people are becoming increasingly aware of the power and influence that Big Data can have over our lives. Many people left the platform after this scandal, and Facebook were forced to make changes to their platform that gave more powers to users regarding their personal data.

For most people, the only time we hear about the power of data is when an organisation takes advantage of users’ lack of data literacy, and uses personal data for their gain, whether it be financial, political or both, like the Cambridge Analytica scandal.

As governments are under increasing pressure to advocate for data democracy, they make data sets available to the public. New York City is a great example of this, they have had a law in place since 2012 that mandated all public data has to be made available on a single portal by the end of 2018.

Access to the data alone does not build data democracy – the general public needs to not only have access to data, but they need a level of understanding of what that data is and how it is being, or can be, used. It is only through the general public being aware of these issues that  large corporations can be held accountable for THEIR use of OUR data.

Below are some TED talks that helped me understand more about data and encouraged me to start exploring and playing with open data, both as a hobby and in my job as a Service Designer for FutureEverything.

Jar Thorp talks about the importance and potential uses of data visualisation – of getting data to a place where it “makes sense” to people. Visualising data gives it context and shows patterns you wouldn’t normally see, these two things in combination transform that data into knowledge that can be used to make decisions.

Data artists interpret data sets and tell the data story through visual tools such as graphs, charts and animations. These visual tools allow others to understand complex ideas that use huge amounts of data; such as the movement of people within a certain space over a certain period of time, or even a group of people’s personal relationships to one another.

Data visualisation changes Big Data from a  big scary excel sheet full or numbers, into a visual tool that can be understood by many – it democratises the data used.

Cathy O’Neil de-mystifies algorithms through simple analogies and everyday examples. In this Ted talk, she talks about the general public’s fear of maths. This fear has led to their hesitancy to question the outcome of algorithms, which are complex maths problems.

Cathy describes algorithms as “opinions written in code” – they are a series of conditions or variables tested against one another, with a desired outcome. This desired outcome changes depending on the motivation of those running the algorithm.

If the public become aware of how algorithmic decision making works, then they have the opportunity to leverage that power for themselves. Why should large organisations be the only ones with this knowledge and advantage? It is in their benefit to keep the public uneducated and fearful, through simple explanations like this we can democratise and bring power to the people!

In this talk, Rebecca Nugent articulates the bare bones of data science. It is something that we do every day while making decisions – she compares different forms of data and different methods of analysis, that may not commonly be thought of as “Data Analysis”, to illustrate that many people are analysing and working with data without realising it.

Rebecca Nugent echos Cathy O’Neil’s point that the general public’s fear of maths, and lack of mathematical literacy, means that they are hesitant to approach or question data and its outputs. It is our own self image that actually prevents people from engaging in data – if we believe ourselves to be good at something such as art or languages, then we must be bad at maths and statistics, so we don’t engage with them. She argues that this perception is wrong and damaging – there is so much knowledge to be gained from contextualising all this data, and for that we need people from all walks of life to become involved with data.

Ben Wellington is a data storyteller – he is a data scientist, but also plays with data as a hobby. When the city of New York released a massive amount of public data, he set about comparing sets and visualising the data. With his wife, who is an urban planner, they run a blog where they collaborate and map information about the city of New York. With his data analysis skill, and her understanding of human behaviour around the city, they generated new insights and together were able to build stories around all this data.

There are so many experiences in life that are shared amongst the people living around us, storytelling puts these shared experiences in one place and creates a starting point for discussion around it. It creates interest in the data and encourages people to go out and look at the data their city is putting out – after watching this Ted talk, I searched what open data portals were available that related to my city, Manchester.

If you’re interested, here’s a link to Manchester City Council’s open data platform.

Citizen observatories create the space for ultimate collaboration, these are platforms where many people across the world come together to solve complex issues through collaborative  efforts. Allison Sagraves shows that contributing to citizen sensing/science projects can have some really impressive outcomes; one example she speaks of involves gamers solving complex protein mapping problems for molecular biologists. These gamers were so successful, that they solved their first protein in three weeks – a protein that molecular biologists had failed to map for over ten years. The power of the people is real through Citizen Science!

At FutureEverything we are involved in the GROW project – a citizen sensing project around soil. Now this may sound boring – BUT did you know that soil is a finite resource and we are killing it? A world with no soil means a world with no agriculture and no fresh food, no trees to provide oxygen, and no important layer of earth to manage water and gas flow between the planet and atmosphere. No soil = no life.

The more people involved in projects like this, observing our soil, the more prepared we can be to take action to prevent further deterioration.